[This Transcript is Unedited]

Department of Health and Human Services

National Committee on Vital and Health Statistics

Workgroup on Quality

November 18, 2005

Hubert Humphrey Building
200 Independence Avenue, S.W.
Room 705A
Washington, D.C. 20001

Proceedings By:
CASET Associates, Ltd.
10201 Lee Highway, Suite 180
Fairfax, Virginia 22030
(703) 352-0091

PARTICIPANTS:

Workgroup on Quality Members:

  • Robert H. Hungate, Chair
  • Justine M. Carr, M.D.
  • Carol J. McCall
  • William J. Scanlon, Ph.D.

Liaison Representative:

  • J. Michael Fitzmaurice, Ph.D.

Staff:

  • Margaret Greenberg
  • Debbie Jackson
  • Susan Kanaan
  • Jon White
  • Scott Young

TABLE OF CONTENTS

P R O C E E D I N G S [9:10 a.m.]

Agenda Item: Call to Order and Introductions — Review
Agenda/Intent of Hearing

MR. HUNGATE: We are still missing John Lumpkin from the first panel, but
his plane wasn’t arriving until 9 o’clock and we all know the vagaries of
arrivals at DCA. So, he will get here when he can.

I want to welcome everybody to this hearing. It has been preceded by a lot
of discussion and comment and time and there has been a lot of background that
has gone into this and before we go into that, let’s go around and introduce
ourselves.

We are on the Internet, I believe. Is that right, Donald. So, all that we
say and do is available to the general public if they wish to avail themselves
of that. At some time in the future, it will be summarized into comments and
observations.

I am Bob Hungate. I am the chairman of the Quality Workgroup, a member of
the National Committee on Vital and Health Statistics, which is charged with
the advice to the Secretary on health information policy and our specific
charge relates in the quality area. I am also the principal of Physician
Patient Partnerships for Health, which is really an advocacy directed at
patient participation in the health care system and broadening the dialogue
between physician and patient.

With that, let me pass around and ask each to — I don’t think there are
likely to be conflicts of interest on this, but if you have such, please
identify it. No need to recuse yourself if you don’t.

MS. MC CALL: Good morning. My name is Carol McCall. I am vice chair of the
Quality Workgroup and a member of the full committee for NCVHS. I am vice
president with Humana. I run our Center for Health Metrics and I have no known
conflicts.

DR. SCANLON: I am Bill Scanlon. I am a member of the Quality Workgroup, as
well as the full committee and have no known conflicts. I am also with Health
Policy R&D.

DR. FRIEDMAN: I am Dan Friedman with Population and Public Health
Information Services.

DR. FITZMAURICE: I am Michael Fitzmaurice, senior science advisor for
information technology to the Agency for Healthcare Research and Quality and
liaison to the full committee.

DR. KIBBE: Good morning. I am David Kibbe. I am the director of the Center
for Health Information Technology at the American Academy of Family Physicians.

DR. VILLAGRA: Good morning. I am Victor Villagra. I am president of Health
and Technology Vector, a consulting company that concentrates on disease
management and technology assessment. I don’t think I have any conflicts.

DR. LANSKY: Good morning. I am David Lansky with the Markle Foundation.

DR. ORTIZ: Good morning. I am Eduardo Ortiz. I am staff to the NCVHS
Quality Workgroup and I am at the Washington, D.C. VA Medical Center, where I
am the associate chief of staff. I am also director of clinical informatics and
I am also a staff physician on the inpatient and outpatient medical services.

MS. KANAAN: I am Susan Kanaan, a writer for the committee.

MS. GREENBERG: I am Marjorie Greenberg from the National Center for Health
Statistics, CDC and executive secretary to the committee.

MS. HOLMES: I am Julia Holmes and I am a staff member of the Quality
Workgroup and I work at the National Center for Health Statistics.

DR. CARR: I am Justine Carr, member of the committee and the Quality
Workgroup. I am a physician at Beth Israel Deaconess Medical Center and a
director of health care quality there.

MS. JACKSON: Debbie Jackson, National Center for Health Statistics, CDC,
committee staff.

MS. JONES: Katherine Jones, CDC, National Center for Health Statistics and
staff to the committee.

MS. MATHEWS: Erin Mathews, American Society of Clinical Oncology.

MS. BOYD: Lynn Boyd, College of American Pathologists.

PARTICIPANT: — program associate, Robert Wood Johnson Foundation.

MS. CHRISTIANSON: Susan Christianson, health information technology group
at the Agency for Healthcare Research and Quality.

MR. ROHDE: Dan Rohde, American Health Information Management Association.

DR. HUFF: Stan Huff with Intermountain Health Care and University of Utah
in Salt Lake City. I am a member of the full committee, just a visitor today in
this subcommittee meeting.

MR. HUNGATE: All right. That is great.

Is there anyone on the phone? Not yet. There will be later. Thank you for
reminding me.

John Lumpkin had a plane that arrived at 9:00. I have already covered that,
I guess, but he will be here soon.

Today’s hearing really has two purposes. One is a very long range kind of a
visioning purpose and the other is kind of an immediate do we need to get
something taken care of now that we will be glad we did later if we do it now.
Let me try to characterize those two this way.

This workgroup started out looking at improving the claims information by
adding more information into the claims transactions in order to improve the
measurement of quality at the administrative end of the system, the pay for
performance side, if you may use that in the broader context.

We conducted hearings on that and found a real conflict between
expectations on the provider side in the provision of information and the
payers in the use of that information. From that set of observations, we
concluded that it was probably not going to be very productive to continue to
work on trying to improve the claims information, that it was better to move
toward the electronic health record and put our efforts forward toward where
that is going to come out.

So, that is the background that has put us to this point. That is a pretty
big — when you start to try to look forward, it gets to be harder and harder
to make everything work. So, we had a one day retreat basically. We drew in a
lot of people, whom we have had before us or participating with us before and
talked about this broad topic and the content. Brent James was there. Steve
Jenks was there. Don Detmer, a past chair of this committee, was there. So, we
drew on their experiences in debating this subject as well.

That created, I think, a fair amount of excitement within the group, in
terms of the potential to really try to position the kind of things that need
to take place over the transition to electronic health records in order for us
to really do the job of quality improvement that we think is possible in the
system.

I think it is pretty universally accepted that electronic health records
are necessary in order to deal with the information content that is so rapidly
growing, that there really isn’t any alternative but to do that among those
that work closely with the system. That said, getting your expectations right
and understanding what you have to do in between to make it come down to where
you get the answer that you want is another game. That is where we felt the
visioning might fit.

Central to the expectations and the firmest conclusion really coming out of
the retreat was that the secondary use of clinical data was the clean element
and the critical element in terms of improving the coherence across the
measurement system for quality for health. So, that is a central kind of
content that should be kept in mind as we go through the context of today’s
hearing. That was quite adequately covered by our own Stan Huff in the just
past NCVH full committee meeting. So that we have just had a recent dose, if
you will, of where does this fit.

The secondary uses raises a lot of content issues. Did you collect enough?
That kind of really led us into the short term question of whether the
electronic health record is being looked at sufficiently carefully to
understand the breadth of what you have got to have in there on downstream as
you go through the learning curve of understanding what you really need to have
versus what you thought you need to have.

There are institutions that have been on this learning curve for a long
time and there are a lot of folks that are just starting. So, we are trying to
understand that kind of a content. The longer term content is directed at let’s
call it the goals for the measurement system. We have had discussions within
the workgroup about is it quality per se we are talking about? Is it health per
se we are talking about?

We have been advised by some of our testimony to speak in terms of
performance measurements and these are semantically different terms. They are
all interrelated. We have tried in the positioning of this first panel to set
it up so that we got as good an understanding as we could of the individual
health, population health, the various perspectives within which quality might
be judged at the end user point. So, that is an understanding. I have invited
Dan Friedman to be a reactor to this comment from his vantage in the earlier
development of the health statistics for the 21st Century document that came
out of the NCVHS.

So, I am trying to make sure that we get a very broad understanding but yet
don’t lose sight of the fact that as Willie Sutton put it, you go where the
money is and there is an awful lot of health care expense and relationship to
health involved in inpatient health care, which is where much of the pay for
performance work tends to end up. So, that is the other piece, the short term
link into the content of this first panel.

Now, sometimes I confuse people by my expression of what I perceive to be,
but I hope that we have set this up so that the discussion, which follows
presentations is intended to be committee and panel so that there is room to —
and we have allowed more time for discussion than for presentations because I
think that the talking back and forth is where an awful lot of our gain will
come.

Justine, did you want to —

DR. CARR: I think I would just like to thank Bob for framing that and add
also that we — I think the real question that we are looking at is what
quality will come out of the electronic health record. I think in terms of
primary use, we know there will be efficiency, availability, timely — you
know, all of that, but in terms of the secondary uses, what is the — what do
we get in the current configurations of electronic health records and I think
we feel particular urgency as the growing member of required core measures or
pay for performance measures are being developed does not — clear crosswalk to
being able to respond to those growing — that growing list of metrics with the
electronic health record. I think what we are trying to say is that can we
anticipate the building blocks necessary within the electronic health records
so that we can achieve not only the primary quality goals, but the secondary
use goals that we will have configured it in a way that is dynamic and can
respond as new evidence comes out, new questions, new metrics, will we have an
electronic health record that will keep up with that, that will deliver on the
efficiency and also give credible information about quality.

MR. HUNGATE: The next is such that this morning you are kind of put here as
users of information representing that viewpoint. This afternoon we will go to
those who are providing the information to electronic health records and we
will try to work those two back and forth.

Are there any other background questions that should be covered now before
we begin? Okay. Do you have any preference, Panel, as to who goes first? Well,
David has got his stuff up. So, you get the honors.

Agenda Item: Users of Electronic Health Records —
Panel 1

DR. KIBBE: Why don’t I sit here and then I can advance the slides from here
sitting down, if that is okay with you all.

First of all, let me say on behalf of the American Academy of Family
Physicians, it is a real pleasure for me to be here and speak with you again.
Just by way of orienting everyone, the American Academy of Family Physicians
has about 60,000 active practicing members. It is an organization that
represents disproportionately small and medium sized medical practices.
Somewhere in the neighborhood of 70 percent of our members practice in groups
of five or fewer, although we certainly have members who are practicing in very
large practices as well.

The division that I run, the Center for Health Information Technology, was
established in 2003 expressly for the purposes of helping our members to
acquire electronic health records that are standards based and affordable. We
see a growth in the use of commercial electronic health record systems from
about 10 percent in 2002 to 30 percent now in 2005. I thought what I would do
in the context of your questioning and getting to this major issue was to first
of all acknowledge that from our point of view, we see the question that you
are getting at in terms of the infrastructure in small and medium size medical
practices, which is more than the electronic health record, but it is becoming
the combination of the suite of proper applications that are used in a practice
and what you can do with that and the opportunities there for a quality measure
collection for reporting and opportunities for feeding back to the practices
and getting the improvement cycle going.

I would agree with you that particularly in light of the rapid growth of
electronic health records, not only by large groups, but by very small groups,
if we don’t think this through in the manner that you are trying to, we will
end up without the capacity we want to be able to get the quality measures of
the routine use of these products.

I thought I would give you an update and comment on some of the rapid
growth in use of electronic health records among family physicians because I
think that this goes counter to some of the impressions and ideas currently in
conventional wisdom. This is a very rapid moving field and I hope this news
will be useful to you in your discussion. I also want to offer some commentary
on affordability and interoperability of the standards that are now making
their way into electronic health records and with the partners of informational
sources and that I think because that is so critically important in getting the
data out of these systems on thinking through how the data gets in and is
managed inside the system.

Physicians in small, medium sized medical practices using electronic health
records are not only users of information, but they are producers of
information. So, it is really a supply change model that I would suggest.
Clearly, there is no question the connection between electronic health records
and even small practices, the quality of care is becoming obvious. At the top
of the list really is this chief benefit of instantaneous access to medical
records by the doctor or by the nurse basically anywhere they are and that
includes home or at the hospital.

At the bottom of this list, you will see the collection of quality
performance data as a routine byproduct of the use of the system. The reason
that that is the bottom of the system is not because it is not important or it
is the least important issue, but in terms of a hierarchy of needs and medical
practices, it is probably the bottom one.

So, if we are going to raise it without any federal pay for performance
program that really changes the reimbursement system, we are going to have to
do some work with the vendors and with the physicians themselves. I want to
make the point very quickly that it is important, I think or we think, to
understand that HIT has the option and use issues in ambulatory care versus
those in the inpatient environment or large enterprises are very, very
different. On the left hand side of the scale of this chart you see the
ambulatory care picture where — which is characterized by a small revenue per
encounter, large, large volume. Whereas, in the hospitals, you have very large
revenues per encounter, but relatively small number of admissions.

So, the leverage here issue is enormous in the outpatient environment. I
want to point out to you that the vendors in the outpatient market are not the
same vendors in the inpatient market. The standards in some cases that are used
in the outpatient environment and the ambulatory care vendors are not the same
and the buying cycle and the infrastructure upon which they are building is not
the same.

Much of the business in the outpatient and ambulatory care market with
respect to information technology is new business. So, it tends to be more
innovative and that is an important thing to keep in mind.

Well, I am really sorry but we didn’t transfer that one slide. That is too
bad because that is a very important slide. This is a graph, supposed to be a
graph here, that shows that we did two surveys, formal web-based surveys, one
in 2003 and one in 2005, showing in the first instance that 24 percent of our
members were using electronic health records in 2003 and 46 percent in 2005.
Because those were web-based surveys, we discounted them significantly and
said, well, maybe it is half that But we also in 2005 did two surveys that were
paper-based, very large numbers of physicians that were paper-based, so you
would not expect a bias.

We asked a very simple question in both of those. One was physician profile
and another had to do with immunization. Are you using then a commercially
available electronic health record in your practice? Both of those surveys came
out right at 30 percent. In combination with a number of surveys that have been
done at the state level, we feel very confident that 30 percent of America’s
family physicians are now using electronic health records.

This information is very important to grasp, I think. And the slide did
come through. We asked the physicians in these surveys who aren’t using
electronic health records yet why not? What are your barriers? And notice that
the blue in 2005 and the red in 2003, in both of those years can’t afford and
electronic health record is over 50 percent of the respondents who don’t have
an electronic health record. But then note what happens versus in 2005 versus
2003 with these other barriers.

In each case, decreased productivity, risk of vendor going out of business,
security and privacy issues, worried about partners’ acceptance, the
respondents in 2005 are less worried about these barriers, even though they
haven’t purchased an electronic health record. This bears out a lot of
information that we have from the field that our members and perhaps just
physicians in general in the ambulatory care space are more ready to purchase
electronic health records.

As a matter of fact, if we were to grow much faster than we are growing now
in terms of adoption, the capacity would not be there because the major vendors
who are selling in this market are already at 4 and 5 and sometimes 6 months
waiting list. So, it is an important issue to consider in terms of the capacity
of the markets. This didn’t come through. I am sorry. This slide also shows
that overall satisfaction with EHRs is high, with a few exceptions. I would
reference the October issue of family practice management for these graphics
and I will certainly try to do something to help us get this — I should have
brought my own slides today.

This is another piece of good news and that is it is starting to address
the issue of ownership. We did a survey of 26 vendors in 2005. We asked them
and then we verified with some practices, what is the total cost of your system
for a practice of three doctors over three years. In other words, include not
just the software fees but the hardware costs, assuming you are starting from
scratch, the training fees, the implementation fees, the third party software
fees, because you always have to pay our friend, Bill Gates, something if you
are using a Microsoft environment.

To cut right to the chase, there is a figure here that is really quite
remarkable is it came out to about $7,200 per doctor per year over those three
years. I mention this because it is often quoted in Washington and other
meetings like this, that it is $30,000 a year per doctor or $40,000 a year per
doctor. Now, it can be. There is no question because the standard deviation of
this information is huge. If you want to pay a hundred thousand dollars a year
per doctor for an electronic health record system, you can do that. There are
vendors who will sell it to you but this is well under $10,000 now for most of
the available and reputable commercial EHRs. I think that while that is still
expensive, you can look at it — one data point to judge this by is if in a
smaller medical practice, we are doing transcription, we are paying eight to
ten thousand dollars per doctor per year just for the transcription.

If by implementing an electronic health record in the data entry now is
starting to be done by the office staff or the nurses and the doctors, you can
pay for it right off the top, not just for the software, but for everything.
So, the issue on return in investment is becoming much, much easier to justify
and I think that is why we have seen this really rapid growth, a tripling of
our members’ use.

Now I want to talk very briefly about exchange standards because
interoperability and connectivity is really the key driver behind the value
proposition for electronic health records in these practices. Physicians are
beginning to understand that this is no longer simply about documentation and
putting the beautiful paper into the computer. It is about transferring
information from A to B, getting it into your electronic health record, being
able to view it when you need it and making work flow changes in the office
that not only increase productivity and achieve cost savings, but provide
better value to the patient, more convenience, less waiting time, answering the
phone, getting refills done much more quickly.

There are several areas where this interoperability and connectivity
progress is being made that are worthwhile noting, I think, in the context of
this issue of quality because to the extent that that theses efforts allow data
to be gotten into the electronic health record, they also allow that
information to be stored and gotten out at some point.

The continuity of care records, one of those standards is now a fully
validated standard. It is known as ASTMCCRE2369 and it is a major advance
because it is an XML standard for interoperable exchange of core summary health
data between electronic health records and for portability of patient and
consumers and as patients and consumers start to take more responsibility as we
think they will for their own health information, they may also start to become
a source of this information electronically.

E-Links has made a good progress in promoting national industrywide
laboratory results reporting. We are not where we would like to be nationwide.
But this — and this has been an effort that has been more than simply a
standards issue. It has also had to deal with industry practices and problems
associated with the laboratory industry. But it is getting more dependable now,
that if you buy an electronic health record in Toledo, Ohio and you want a
contract with laboratory company A or B, that you will have and still interface
for your electronic health records.

I think we made extraordinary progress in e-prescribing standardization and
conformance of students over the last year or so. We have still got a long ways
to go but the same thing, if you buy an electronic health record in Toledo, you
can now get sure scripts, a computer to computer exchange transactions for
e-prescribing and for renewals of prescriptions, at least some of the major
drug stores in Toledo and other places.

As you are probably aware, Docket(?) has created a schema for physician
office, EHR and the national database connectivity with respect for downloading
quality and performance measures or uploading from the perspective of
electronic health records.

Although I think that there are some real problems technically with that
whole schema in the way that it has been set up and I say that as the project
director for Docket. So, part of the responsibility is mine in not getting it
right, I think it is still the right idea in that if we can work with the
electronic health record vendors in such a way that specific data sets that
need to go to a data aggregator that carry the particular reference,
performance, quality data can be done, but we need to make it a national
priority.

At the American Academy of Family Physicians, we are very, very
disappointed with this G code scheme that has been put forward as a voluntary
means in part because it backs off of using real data and collecting real data
from the practice and substituting made up codes for it.

So, in summary, I think the challenge with respect to this longer term
process of assuring that physicians and practices that use electronic health
records can reliably dependently and accurately export quality and performance
and cost information to data aggregators, is to really try to leverage the
early successes we are having now in EHR adoption, to assure that this quality
measurement capability is before us.

I think this is — several things I want to highlight. One is I think we
need to continue to work with the Federal Government and state governments and
private health plans to help finance affordable standards of ACHRs. If there
isn’t going to be financial help for small or medium sized medical practices, I
think the adoption and transformation is already going to occur and will occur
and will continue but it is going to be slower.

If we could find a way for even small amounts of financial help or tax
breaks to be made available to practices, we would speed it up. I think we need
to work with vendors and physician groups to pilot the automated export of
quality and performance data from practice electronic health records to data
aggregators.

I am a co-chair with George Isham(?) of the Ambulatory Care Quality
Alliances Data Sharing and Aggregation Subcommittee and we are working with CMS
and within ACQA to make recommendations regarding the pilot project that will
do just this. I think that there are a number of different ideas and
technologies that need to be tried out in order to get this additional robust
clinical information into a data aggregation, hopefully, all-payer database.

We need to continue progress within the AQA that has already been made to
standardize measures, standardize the measures. We have got a good starter set.
We need to get it out there and start using it and to develop policies and
standardizing procedures for data collection sharing and reporting. I think
this is a very, very important group. I think that we have made good progress
in a very collaborative fashion. There has been a lot of compromise and a lot
of progress in a short period of time.

I would encourage us to continue to see that group as a place where some of
this work can be done. I think I will stop there. I think that is plenty at
this point.

Thank you very much.

MR. HUNGATE: Thank you. That is very helpful.

I think we will try to get through all the presentations and then get into
discussion and questions. So, write down your questions as we go and keep them,
so we don’t lose them. But let’s go on in that way.

Who would like to go next? Would you like to go, John?

DR. LUMPKIN: Sure.

MR. HUNGATE: We would be delighted if you would do that.

I have to give John a few kudos before he gets to start because when I
joined the NCVHS, we had some work to be done that required a report to get
generated. Without John and Marjorie, whose institutional memory and
participation was critical to getting that done, we wouldn’t have made it. So,
welcome back to the Quality Workgroup and NCVHS.

DR. LUMPKIN: Great. It is a thrill to be back and see so many familiar
faces, get to sit on the table from this side. Although I am getting paid the
same amount as I was before.

Let me talk about a couple of things. I thought a lot about what I should
say when I was coming here and thought maybe it would be best to start off with
the context, what we are talking about improving quality within the electronic
age as we are seeing the transformation occur. It is a transformation, which
really is quite surprising. I think I saw a recent article that identified that
10 percent of hospitals now have some form of electronic health records and
they were lamenting the fact it was only 10 percent. I can remember the days
when we were sitting here saying, oh, my God, it is only 5 percent and we are
not sure about that 5 percent.

So, progress is being made and this becomes a very important time to
consider the issue of quality. I heard the end of David’s presentation. There
are some very important issues that we will need to address. But let me put it
within the context.

At the Robert Wood Johnson Foundation, we just completed a survey of
business leaders in 2005. We did this in relationship to the issue of covering
the uninsured. But the No. 1 issue — and when we asked this of leaders, what
is the most important issues to you related to health care, 52 percent said the
issue was affordability of health care costs. Twenty-five percent said covering
everybody because of the impact and only 12 percent for quality. Now, this is a
shift. It is a shift that is reflected by the rising cost of health care, the
fact that we have returned to double digit inflation in health care over the
last three or four years, although that seems to be moderating a little bit.

But basically a big shift in the link in 1990 is when business was really
pushing on the issue of quality, the issue of affordability has come there. The
impact, they believe is that 79 percent are concerned about their ability of
their employees to pay for their health care. Many expect their employees to
drop the coverage that they have because they can’t afford their portion of
that health care. If you paid any attention to some of the recent strikes that
have gone on in GM, the transportation staff in Philadelphia recently, as a
result of that settlement, employees are shouldering more and more of the cost
of their health care.

Now, we also completed a survey and this one has not been released, but
will be released soon. This is part of our approach to going out and querying
health care leaders in some target communities. In fact, we queried over a
thousand health care leaders. What are the issues they are seeing?

These health care leaders in these target tracking communities are seeing
health care expansions, primarily in the areas that are most lucrative,
cardiology, procedure-based facilities. They are also expecting to see
substantial cost increase in the future. What is most interesting, really in
contradistinction to the business leaders is that almost none of them are
looking at cost control strategies and cost control strategies can be done well
or can be done poorly and we have seen in the 1990s sometimes when the issue of
cost outweighs the issue of quality.

What is different is is that we have better ability to measure quality, but
we also have different tools. We know that quality is a challenge, the work by
Elizabeth McGuinn(?). Half of the care that is given doesn’t meet the standards
when you do a significant amount of chart review. The problem with quality,
this particular study, which involves close to 7,000 patients who had their
charts, they were called up, people said, you know, the researchers said can we
look at your charts and compare them to the quality of care that was given.

This was an extremely costly study. It cost in the neighborhood of about 12
to 14 million dollars to do this study. The data is overwhelming. Obviously, in
a different world, in a different environment, this kind of study could occur
almost with no cost if we, in fact, start shifting that data into data
aggregators. So, we have a quality problem where people are only receiving the
right care about half of the time and much of our health care spending has no
value, which ties into the issue of cost.

Now this is related to a project that is done by the Dartmouth Health
Atlas. If you are not aware of that project, this is where they take basically
Medicare data and they aggregate the Medicare data and they start looking at
the cost of care, not charges, but the actual cost of care and they look by
regions and there is great variation in these regions, from 15 percent above
average to 15 percent below average.

Now, the interesting thing is you can say, okay, well, I can understand. I
can go to a hospital or a health care provider and they are going to cost most
because I am getting better quality care. Well, we are not so sure about that.
First of all, there is a direct correlation in many of these areas when you
look at the records where the number of visits to cardiologists, for instance,
seem to be better correlated to the number of cardiologists per hundred
thousand in the population rather than the amount of cardiac disease. If you
look at a disease such as fractured hip, where there is really very little
discretion on whether or not you are going to put a pin in somebody’s hip. That
is going to be a line basically flat across the bottom. It is independent on
the number of orthopedic surgeons.

But other procedures, these sort of preference procedures are where you are
seeing the high cost of care. Now, is the quality the same? No. When you look
at the lowest region, in other words those who are charging the least amount in
the country and you compare mortality, it is slightly hire in those regions
that charge more. And if you compare it to those who are providing aspirin at
discharge in those regions, that cost more, not charges, actually costs of
care, adherence to providing aspirin at discharge after a heart attack,
myocardial infarction, is actually less in the higher cost regions than it is
in the lower cost region.

So, we have this great variation in cost of care with no associated
increase in quality. This is a huge problem to get our arms around. Then there
is another component and that is that the variation that occurs is not just
from region to region. There is also variations by who you are. This is an
interesting study that was done by David Narrin(?) in 2002 and what he looked
at, a whole number of quality measures, particularly looking at African
Americans and whites. As you see in this particular chart, on the left, the
African American — the white rate is twice that of the African American rate.
The principle is fairly simple. If a kid who is under 17, 5 to 17 years old,
has asthma, goes into the ER, the health plan ought to follow up with them
within a week. I mean, that is not an unreasonable thing.

Yet the rate for the African Americans is half that for the whites. The
interesting thing is a colleague of mine at the foundation when we were seeing
this presentation leaned over to me and said, you know, John, the real problem
is they both stink. But if we are going to be able to address quality and to do
the kind of measurement and to identify the issues related to disparities, then
we can’t do that unless we can also identify who is getting the care and what
their demographics are, not just enough to know the population as a whole.

It is interesting. Some of the critiques and the follow-up and the analysis
that is going on and the violence that occurred in France was because the whole
system in France, which they considered everybody is treated the same, had the
inability to measure disparities in their society and that our ability to
address these issues is not by sweeping them under the floor and assuming that
they don’t exist.

If you look by state, what is even equally interesting is if you look by
state and you take the states on the bottom axis, on the X axis, is the
percentage of African Americans in the state and on the Y axis are the
adherence to guidelines for use of beta blockers after myocardial infarction
and you plot that out, you get a straight line plot. The more minorities there
are in the state, the less adherence there is to those guidelines. I want to
say that very clearly, for everybody.

When you look at the data in communities, those communities that tend to
have higher rates of African Americans and other minorities in the communities
tend to have lower quality measurements for everybody who lives in that
community, not just for the African Americans in those communities. That is
related to the fact that over 80 percent of the care provided to African
Americans and other minorities, Hispanics and Asians, provided by 20 percent of
the providers and those providers tend to have less access to subspecialist
care, less access to other kinds of resources, which enable them to give the
kinds of care and, unfortunately, have the potential to have less access to
electronic health data.

When you focus on quality, the good news is there is increasing evidence
that not only — and you look at this particular chart and you say, okay, the
disparities over this ten year period of time — and this was not an effort to
reduce disparities. It was to improve the quality of care of people getting
hemodialysis. They went back and looked at the literature to see what was
different between whites and blacks. Basically, the gap narrowed, but the most
significant thing is is that for African Americans whose adherence to the
guidelines increased from 36 percent to 84 percent, almost a threefold
increase.

So, inherence and use of quality data to improve quality can have an impact
upon everybody in the community, as well as reduce disparities. Now, in order
to think about the model and the kinds of ways we want to aggregate data, we
also have to think about how we are going to address and improve quality. This
model was developed by Ed Wagner and his — ICIC, Institute for Chronic Illness
Care, for Improvement of Chronic Illness Care. This is what is called the
chronic care model.

This model looks at and says that it is more than just what is happening in
the delivery system and how it is designed, but you have to include decisional
support, clinical information systems and also involve what is going on with
the patient so that if you think about the best quality interaction, it is
between the informed, activated patient, through self-management and if you can
envision that with an electronic personal health decision support system and
the prepared proactive practice team, who is using electronic health record,
also with decision support, you can get the most high quality interaction and
providing that data is going to be an important component of it.

Well, why haven’t we solved the problem of quality? Well, there are a
number of factors. Individualistic culture of medicine. I can remember still my
senior resident’s voice in my ears when I was a junior student, the first time
on my floor saying you assumed, you relied on somebody else’s data. That is the
way physicians are taught.

The second is is that quality is invisible to consumer and providers.
Providers by and large, on the vast majority want to do a good job. They just
don’t know how well they are doing. There is no way to compare it and neither
can the consumers. There is no business case for providers to adopt quality
improvement because they just don’t know where they stand.

The fact that we have this whole system where all the different parts don’t
connect. I want to kind of end up with a couple of quick thoughts. First of
all, many of you may have seen this. David is probably a little bit upset
because this is like the old version of what Connecting For Health has said for
their motto, which is one of the four models adopted by the Office of the
National Coordinator. But I want to use this particular motto because it is so
much better at making my point than the new model.

This is that we have two things to talk about. We are going to talk about
this area that is shaded, which is aggregating data to measure quality, but we
shouldn’t forget that where we really want to be is here, assuring quality
where patients are getting the care.

Now, the challenge to us as we begin to develop it and to use the committee
and think about data standards in relationship to quality, it is kind of — you
know, I am not a baseball fan, but there is a book that was published called
Money Ball. If you haven’t read it, you don’t have to bother because I
am just going to tell you the important part of it, unless you are a baseball
fan, which I am not, but it is an interesting story.

Billy Dean(?) was the manager of the Oakland A’s, had one of the smallest
budgets in professional baseball. Yet, he was able to be extremely successful
because he began to collect the data and look at it in a different way. What
other teams looked at, they looked at, okay, who had a big name. Who was
athletic? How fast could they run? How strong were they? And, you know, how
fast could the pitcher throw the ball. Fast, young pitchers, expensive.

What he did is did a really intensive data analysis and rather than hiring
big name pitchers, he hired pitchers who had a lot of ground outs. So, it
wasn’t strike outs that he was — you know, if you could get a pitcher who
strikes out 60 percent of the players, that is great. But the other 40 percent
are hitting and getting on base, as opposed to a pitcher who 60 percent of the
time, they are grounding out and get strike outs 20 percent of the time, you
are ahead of the game.

He began to look at the data differently and the assumption was and what
they found out was is they were looking at the wrong thing in making their
decisions about putting together a quality team. Our challenge in health care
is to make sure that we are, in fact, looking at the right thing.

First of all, we have to design the systems, electronic health record
systems in the right way. In 1993, we put a system in Illinois called
Cornerstone, which is a paperless system to manage maternal and child health.
When we put the system in place, what we learned is if we designed a system to
meet the needs of the patient and the provider, the caregiver, the client, that
we had all the data we needed in order to measure quality. So, that has to be
one of the principles first and foremost that we do the systems, that we design
them in such a way that they don’t impede care.

Now, the data that is currently being collected, the National Quality
Forum, AQA, other kinds of organizations are developing quality measures and we
want to have a system that can do that in a reasonable fashion, in other words,
that bottom arc of the diagram. We have to recognize that data is going to be
collected for pay for performance and how that expands and how that works out
as other specialty societies are getting more granular, that we want to collect
data that is going to address the issue of disparities reduction. So, race and
ethnicity data, as the committee has said before, is important to collect.

But increasingly, the granularity and quality measurements is going to be
increasing and the kind of measures are going to move for unit of measure from
plan to provider, from plan to hospital, to plan to individual physician and
other caregivers. So, we have to think about this.

So, the final thoughts are quality measures and what we currently use take
that lower arc. In other words, their way of moving knowledge, patients should
be given beta blockers. The thought is is that if we measure it, then docs will
actually order beta blockers.

So, if I have a measurement that is done in 2005 and I will only order beta
blockers for the patients who are discharged from the hospital 40 percent of
the time and I realize I haven’t adhered to the guidelines, then maybe my
patients in 2006 will get better care. Very fudgy, the knowledge is that is the
right thing to do.

But it is much better than nothing and that has to be the first step. But
we also have to be aware of the Wayne Gretsky principle. Everybody asks him how
come he was so good and he says most people skate to where the puck is. I skate
to where the puck will be. So, we have to begin to think about how we can
measure and test our measurement systems because I know how most of these
measures got put together. There has been some analysis, but the data
collection costs are very expensive, which is you get a committee together and
say what seems like to be a reasonable set of measures.

Then we put them through a process, which is called a consensus process,
which is not that you collect data on thousands and thousands of patients, but
you have people sit around the room and say, yes, yes, that sounds like a good
measure. But we need to go beyond that. With the volume of data, it is going to
be possible through electronic system, we need to think about how we can begin
to measure the measures.

Then, finally, to move the unit of measure from provider to patient
centered measure. Instead of thinking of measuring quality in terms of what the
provider is doing, we need to think of how we can move that paradigm into
measure how the patients are receiving the kind of care that they need.

Then, finally, this always has to be kept in mind, Arthur C. Clarke, any
sufficiently advanced technology is indistinguishable from magic. Until it
looks like magic and until the providers can use it in order to get their — to
provide care to their patients and patients can use it in order to get the kind
of care and to manage their own health, it becomes an obstacle and not a
utility.

Thanks.

MR. HUNGATE: Very good. Thank you.

We need to have a copy of that for our archives and use.

DR. LUMPKIN: I will.

MR. HUNGATE: Very good. Thank you.

Who would like to go next? Do you two have any preference?

DR. LANSKY: Thank you, Bob. Thank, everyone.

I will try to take a somewhat different view, I guess. I want to try to
approach this from the point of view of the patient or the consumer and I have
been talking to consumer organizations and representatives for some time about
these issues. As a result, as John concluded, I would probably try to focus my
comments less on the settings of care and the technology that are in those
settings and more around the information needs of the patient and the society
as a whole.

I am not a big fan of the current measurement models and as John just
alluded to the consensus process and so on that has been around for the last
few years, having been involved in that for a long time, I want to make a
couple of comments about where we are in quality measurement and the degree to
which that is taking us in the right direction and whether or not the
information technology we are now bringing to bear will be if primarily applied
to the current quality measurement strategies, I don’t know that will be
terribly fruitful.

So, I think there is an opportunity for your deliberations to think about
the quality measurement framework in a broader sense and then the application
of technology to that, but first thinking about questioning some of the
assumptions we have in the quality measurement environment.

Finally, I want to talk a little bit about national policy as a whole and
try to keep at least my comments focused on whether we are getting as a society
value for our health care investment as a challenge to the measurement
community.

I think one of the broader themes I want to talk about is that we have
created a level of granularity and quality measurement that frustrates our
ability to make judgments about health care and health and I think the
opportunity again for this group is to add to the existing work, which is very
useful on an operational level, a policy, analytic level that I think is
missing right now.

First of all, I think that the current inadequacy of the technology
infrastructure, of the IT infrastructure, the shortage of electronic health
records and so on is not the principal problem facing quality measurement. We
have been at this for quite awhile now and it is important to keep in mind the
primary problem facing quality measurement is the lack of will to measure
important aspects of quality.

Similarly, I think the lack of introduction of IT in the health care system
has been the lack of will to commit to introducing IT into the health care
system. Other societies all over the world have been far more successful and
aggressive and major health systems have been successful and aggressive in
solving these problems. So, I don’t know that we should approach this as a
technology or architectural problem primarily.

So, will and strategy, I think, are the two things that need additional
attention. I want to just make a couple of comments from my years in the
quality measurement business on how it may pertain to the issue in front of us
today. First of all, the issue of human health should be a paramount one in the
discussion of measurement and of IT and it tends not to be. We had very little
discussion of how the IT infrastructure will measure improvements in health or
decrements in health or disparities in health.

Almost all of it has been again at a very granular level of data items,
coding systems, terminologies, vocabularies, which are difficult to aggregate
up to assessments of health and health improvement. I think that is an
important challenge that needs to be addressed. I do think this is a big moment
we are at right now; whereas, we are about to extend a large scale financial
investment in technology and in infrastructure and in burden and everything
else. If we do that in the pursuit of fine grained measures, which don’t answer
fundamental policy questions and resource allocation questions and social
commitment questions, it will be unfortunate. We will essentially aggravate the
silo fragmentation problem we all complain about and we will, in fact,
institutionalize it in technology, which I think would be a mistake.

On that same note, I think we have a conceptual fragmentation, which I
think this body has been successful in the past of addressing, with some very
important reports. I hope you can do that in this arena as well. Our
measurement strategies right now tend to be insensitive to the life continuum,
the movement of each of us through phases of life, health, illness and so on,
tend to be insensitive to the disease continuum stages of illness within a
particular disease paradigm or across multiple disease paradigms, tends to be
insensitive to hand off between settings. For the most part we are building
measurement paradigms that are setting specific or practitioner specific and
not around the continuum of experience in the health care system.

It tends to be insensitive to the interface between the patient’s family
and system and how well that interface operates, which is where most people
actually experience health care. And it tends to be insensitive to the
relationship between financing and care delivery, both in terms of availability
of care and types of care, but we tend to treat cost and clinical services as
if they are independent from a measurement point of view. I think it is
important in this design phase with the IT work to assess whether we can do
better at integrating those various things that we — I guess from our own
mental simplicity and for business reasons tend to fragment.

As I mentioned before, I think we should be very cautious in instituting
process measures as the fundamental mechanism of quality assessment. It is very
valuable for enterprises, who are in the business of delivering services to
understand their processes in minute detail and to do the best possible work
they can to optimize those processes and evaluate them and measure them and
approve them.

I don’t in any way want to diminish the importance of that. I am not sure
that is an appropriate role for the national policy structure to address, at
least not in the absence of having a set of national goals and measures that
address those goals and evaluate those goals. So, if we aren’t able in society
to measure health improvement and health gains from the investments we are
making in various sectors of health care. I think it is a distraction to then
suboptimize around at a national level identifying processes of importance even
though they are very important.

Through the IT work one other concern I have from my past experience is
that we are risking digitizing the silos that we have instead of creating a
digital climate, which could allow us to transcend those silos. Silos have
arisen partly for service delivery reasons, but now increasingly for business
reasons because we have institutions and categorical funding structures and so
on, licensing structures, which perpetuate a set of delivery models that may or
may not be well suited to the burden of illness in society. If we now
institutionalize an electronic environment, which reinforces that rigidity of
our current business structures, it will make it even more difficult to really
reengineer how care is delivered.

So, I think we should be cautious about that and that gets back to John’s
concluding point. It is a worthwhile thought exercise as you do the long term
part of your discussions here, to center your analysis on the person and say
the person is the ultimate source of every piece of information that we are
transacting in this health care environment. We should at least entertain the
thought of architecting the IT environment and the quality measurement
environment around that person, rather than around the various settings, which
institutionally have developed over the last 75 years or so and we are stuck
with.

Then to evaluate how to get from our current institutional environment to a
truly person centered information and measurement environment. If, as many
people are, if we are at a point where we believe this century needs to see
significant redesign of the health care system, then this is a key moment to
develop the metaphor or the model, as you said in your summer retreat, which is
based upon the person as being the central source of information and
decision-maker in the resource use in the system.

Let me change tacts and make a couple of other comments on a different
direction. That was kind of an overview of the past. I want to talk about what
is going on forward a little bit. There is an awful lot of digital data
available today that we are not yet taking advantage of and I want to at least
raise the question of whether the electronic health record as we tend to
discuss it in rooms like this is where the puck is going to be three years or
ten years from now.

My guess is that it is a worthwhile exercise to imagine a digital
information environment, which is not particularly reliant on electronic health
record as we now think of it in a physician’s office or in a practice setting,
that we are already seeing a very large proportion of the relevant health
information that is now available in digital forms, in distributed networks.
Roughly half of all the radiology images are now digital and available in
PAC(?) systems and similar systems. Laboratory, national laboratory systems
account for 50, 60 percent of all the laboratory data.

As we saw with Hurricane Katrina and the Katrina health strategy, close to
70 percent of all the dispensed medications are now available on national
digital networks. Those all exist now without having infrastructure per se in
the physician’s office, similar to what we think of as an electronic health
record.

If we extend that analysis and, of course, the claims data, which whatever
liability you want to assign to it has some information about diagnosis and so
on, procedure, treatment. It is worthwhile to think about a network metaphor
instead of an institutional metaphor for the availability of health information
that will constitute the platform on which we do quality measurement and other
things and it is certainly worthwhile to look at other sectors. I think my fear
at this point is we are taking with essentially a 10 to 15 year old
technological approach and electronic health information and now trying to fund
it and propagate it and have it widely disseminated while at the same time we
look at the world of instant messenger and the platforms that Google is
proliferating rapidly and see a much different approach to information
acquisition, dissemination, dissemination and reuse than we envision in this
setting specific electronic health record.

So, I think a more comprehensive analysis of network models of information
handling is timely if we are going to be where the puck is likely to be in five
years or ten years. Certainly, if we look around the world, the models that are
emerging for health record systems and health storage, health information
storage, are moving very rapidly in very interesting ways and, again, in our
society we are not doing nearly as much of that.

Let me close with one example specifically of where I think we could be
approaching the problem with a different mindset. When Congress was debating
the Medicare Modernization Act and the creation of the Part D Drug Benefit, we
did some work to evaluate what would be the appropriate quality measurement
infrastructure to put in place at the same time as the drug benefit was being
established and the kind of questions we were thinking should be asked.

But nowadays we estimate we are going to spend $720 billion on this
Medicare Drug Plan. It seems like a worthwhile question, whether there will be
a health benefit to the American public, to the Medicare population by virtue
of a very significant public investment. I certainly am not aware of everything
that is going on, but I am not aware of any public discussion of establishing
an evaluation framework for the health benefit that is going to be gained by
the Medicare population by virtue of this benefit.

In that case, in the case of the PBMs, prescription drug plans that are out
there, they have very sophisticated electronic information systems in support
of their existing business. They already have the ability and they already
practice with their commercial customers the drug interaction, dose checking,
age related dose checking. They do alerts. They do reminders. They communicate
with the patient. They communicate with the physician. They do generic
substitution. They do all kinds of administrative look-ups. They are also quite
good at doing administrative — doing operational measurement. So, for example,
they have good estimates of dispensing errors, more so than the retail
pharmacies typically are able to evaluate.

It seemed very reasonable as we looked at it to say from the existing
electronic infrastructure in the pharmacy dispensing business, it is possible
to evaluate both safety in the sense of dispensing errors and other errors
associated with the operational procedures of the organization, service quality
issues in terms of customer service and clinical outcomes in terms of whether
it is alerts, reminders adherence, whether people are successful staying on
protocols, complying with regimens, whether they are achieving desired health
outcomes.

Are people taking Lipitor, having their cholesterol successfully lowered at
six months or twelve months? Now, from the point of view of the government
spending a vast amount of money on these services, it seems like a basic
expectation that we would know whether this investment is achieving reductions
in cardiac risk factors or cardiac outcomes. In fact, I am appalled that we
don’t have in place an infrastructure to tell the public whether those effects
are being realized by virtue of this expense.

But there has been essentially no discussion about it. So, I think that —
to put in place a set of expected outcomes from major public investments and to
expect those who are contracting with the government to provide that
information as part of the service and to put in place the necessary
infrastructure to report that information would have been a discussion worth
having. That would not have required EHRs to be deployed across every
physician’s office in the country. It is something that could have been done by
alternative and essentially available information infrastructure.

The challenge I think is to articulate an appropriate role for public
oversight or evaluation of public expenses in this particular example. I think
differentiating what is the role of the public sector in defining criteria for
quality measurement and I would argue that that should be first on at a high
level of fundamental public value and then setting in place the measurement
infrastructure to support that and then evaluating how does the IT environment
need to be addressed to accommodate that public goal is the kind of pathway
that would be worth following.

Thanks very much.

MR. HUNGATE: Thank you. Very provocative thoughts as were the ones before.

Now it is your turn.

DR. VILLAGRA: Thank you.

First of all, I would like to thank the workgroup for distributing the
background paper that — I understand it was put together by Susan and I found
it very, very helpful. While I have to confess that I was very confused about
what the exact purpose of today’s iterations might be, having read that paper,
I remain confused, but now at a higher plane and that is —

MR. HUNGATE: Join the crowd.

DR. VILLAGRA: What I gather from reading the background is that the
workgroup has been engaged in a very impressive quest in terms of breadth and
depth to define the framework that will allow imbedding quality into the very
fabric of the National Health Information Infrastructure, more specifically
into the electronic health record. So, I will address very briefly four
dimensions of this electronic health record quality linkage. The first is in
agreement with you, David, is the need for an overarching driving force for
population-based quality improvement.

The second is a series of system attributes that immediately surround the
deployment of electronic health records that renders it a useful tool for the
advance of the quality agenda.

The third is the role of a payment system and its link to financing of
adoption of electronic health records and quality simultaneously and fourth is
the issue of access to aggregate data and the rules that govern their use to
advance the health of the public.

My experience with electronic health records has been through the lens of
disease management programs. There are no data that I know of regarding how
many nurses, health educators, pharmacists, nutritionists and other allied
health professionals are using electronic health records but from my empirical
experience, I can tell you that the number is growing very rapidly.

Examining the disease management phenomenon is useful, I believe, because
it emerged outside of the traditional delivery system and in doing so, it
escaped many of the financial constraints, technological barriers, cultural
legacy and the inertia inherent in affecting change from within. You can think
of it as an experiment designed by interdisciplinary teams of physicians, IT
professionals, financial experts or just actuaries, underwriters, lawyers and
marketers, all brought together to develop this model.

And the model, while far from perfect has been adopted widely by payers,
both in the United States and increasingly abroad in many versions. It is also
being adopted increasingly by hospitals and large group practices as a vehicle
to improve quality, to decrease disparities in health care, to improve bottom
line performance and to improve consumer satisfaction with the care experience.

DM, disease management, particularly in its early stages of when
significant portion of the fees were at risk based on the attainment of certain
goals and certain outcomes provides an especially valuable paradigm to
understand the link between electronic health records and population-based
quality improvement.

Electronic health records play a critical role in disease management. These
records are continually populated with patient derived information, information
supplemented with administrative data and more recently lab results. The work
group and the Subcommittee on Standards and Safety has already pointed out the
gaps in electronic health records gathered in this fashion, but in spite of its
shortcomings, disease management programs and with its core of this type of
electronic health records are driving real advances in quality on a large scale
and with the speed commensurate with a sense of urgency, we all feel is needed
to narrow the quality gaps.

Without electronic health records, disease management programs simply could
not operate on any scale or with the speed they do today. However, electronic
health records are decidedly not the driving engine of the system. The real
driving engine is driving quality, is shared values between stakeholders of, in
this case, disease management, service providers, patients and payers. These
shared values encode the utilities derived by each stakeholder by
participating. The shared value creates a non-zero sum gain of all involved or
the proverbial win-win arrangement. This system rewards demonstrable
improvements of clinical quality, patient satisfaction and cost containment.
When fees are at risk, the arrangement penalizes performance failures.

These shared values are intuitive. They are easy to describe and easy to
understand. They permeate all the actions in complex systems delivering these
programs, including improvements in the functionalities of electronic health
records and its supporting database analytic. A surveillance system while very
clumsy and slow at this point, but that aspires to look very much like the
equivalent of the Blumberg of health care or the tick tapes using financial
world to monitor performance is the aspiration of this particular model.

Reports generated from the surveillance system supports of accountability
of petition, collaboration and learning. As utilities are realized or missed,
then myriad of elements comprising the system respond usually in concordance
and in unison with corrective action for additional refinement as the case may
be to maximize those utilities all formed around the shared value that I spoke
about before.

These values and their corollary utilities become then the driving force
that direct the technological specifications of a electronic health record, its
functionality, supporting database and it pulls the system to higher levels of
organizational efficiency and complexity, expansion and self preservation.

This has to do a great deal with its ability to persistently survive over
the long term. So, for me, the first lesson learned is that the role of
electronic health records should be subservient to the attainment of broad,
shared value and objectives rather than the goal or a goal in its own right.

The second thing mentioned of electronic health record quality equation as
I have experienced it through disease management is that attaining superior
quality requires the deployment of a different organization of care and a
different delivery system than was readily available. The traditional delivery
system as organized today is conformed poorly to absorb the increased
information output and the increased efficiency derived from the adoption of
electronic health records.

Furthermore, tradition al settings of care, such as the physician office
could not possibly accommodate the activities of ongoing patient education,
motivation, support for lifestyle changes and so many of the quality imperative
that will be underpinnings of real change in the future. Without a concomitant
effort then to transform the delivery system, much of the promise of the
electronic health record to improve quality would probably be unrealized.

For example, our system more and better information will demand staffing
levels, rolled admissions, communication infrastructure and a physical plant
that must be capable of managing large scale coordinated actions. In the case
of disease management programs, these requirements demanded the deployment of
highly sophisticated call centers. These structures did not exist five years
ago. These are staffed by especially trained nurse, equipped with the most
advanced mass communication technology available, Internet-based, telephony,
electronic system monitoring and others. The sheer volume of information
available to clinicians through this admittedly imperfect electronic health
record could not find its way to patients without an organization of the type I
just described.

So, if the committee welcomes metaphors, as Susan pointed out in her
background paper, I would say that electronic health records that as we
conceive them today would be the equivalent of putting a Ferrari engine into a
Model T Ford and expect outstanding performance.

The third element related to shared values that I spoke before is really
the need for a dramatic change in reimbursement strategy in favor of
outcomes-based payment or reimbursement instead of production-based payment.
The theoretical underpinnings of such a payment system are in its infancy and
requires a great deal of attention. Payment reform that explicitly rewards
quality is one of the greatest allies for linking electronic health records and
in quality simultaneously and concomitantly.

A good example of how misaligned payment system can afford the best of
intentions and excellent technology is in the findings from a recent study by
Robert Miller called “The Value of Electronic Health Records in Solo or
Small Group Practices in Health Affairs.” I don’t know how many of you are
familiar with this.

The study looked at 14 practices that adopted electronic health records,
small practices, and it showed that, first of all, the primary stated reason
for implementing the health record was to improve quality. Only a few of the 14
practices, however, engagement in substantial quality improvement efforts. On
the other hand, several practices experienced significant and apparently
unexpected benefits in revenue generation and practice efficiency, allowing
them to recoup their initial investment and increase their net income.

This is then a very good example of how the quality agenda was at the
forefront of these groups implementing electronic health records. While they
realized some of these practice substantial financial improvement and bottom
line performance. The quality agenda seems to have been relegated to the
background.

The fourth dimension that I simply want to put on the table for discussion
perhaps is the ability to aggregate data as it collects itself in a network
environment such as the one you described, David. The disease management model
had the ability to aggregate data on discrete populations and had the
legitimacy to use it. Payers and their partners seem to have at least to my
knowledge had this legitimacy to use this information has not been challenged.
But with the accrual of the sparse albeit interconnected information, I think
one of the real challenges will be how are these data aggregated, how are the
leverage to improve the health of the public or uses such as epidemiologic
surveillance and I have not read very much about what would be both the
technological requirements, the requirements for the point of view of the
protection of privacy and security of these records, but this is another
dimension of the ability of electronic health records and electronic data in
general in quality and their linkage in terms of how they can be put to good
work to improve the health of the public.

Thank you.

MR. HUNGATE: Very good. Thank you very much. Very helpful content and I
look forward to first Dan’s reactions and then discussion between the panel,
among the workgroup. You know, I think the discussion is where we make our
greatest progress. So, looking forward to that.

DR. FRIEDMAN: Thank you, Bob.

In his introductory remarks, Bob more or less implied that I was here in my
role as institutional memory and I am a former member of the committee and I
can be either described as an emeritus member or an escapee member or an exiled
member, depending on ones perspective.

I am not comfortable in the role of institutional memory. Last week
actually I had a hard disk crash and it reminded me of the fragility of
memories both electronic and human.

I would like to reflect on five different themes that I have heard today
and these aren’t any original points, but they are more just quickly raising a
few things that were mentioned. The first is sort of inherent in the discussion
and inherent in Bob’s initial remarks were really three different issues, what
I think of as three different issues, and I just want to name those because I
do think they are different and I think they need to be differentiated.

One issue is the role of what I think of as the desk top electronic medical
record in improving the quality of health care of individuals. A second is the
role of desktop electronic medical records in improving the health of
individuals and the quality of health of individuals and a third issue that I
think is distinct is the potential role of electronic medical records in
improving the quality of health at a population level.

A second point that I would like to make is that I think that we need to
acknowledge, discuss, debate, whatever, the possibility that the desktop
electronic medical record can serve to improve the health care of individuals.
It can certainly serve to improve the measurement of health and of health care
of individuals, but that does not necessarily mean that it will improve the
measurement of health of populations.

A third point I would like to make relates to the role of what Dr. Kibbe
and what John Lumpkin referred to as data aggregators and in passing, Dr. Kibbe
mentioned the importance of all payer data aggregators. Certainly, if we are
going to talk about the possibility of a desktop electronic medical record in
improving the measurement of the health of populations, it is all about, quote,
data aggregators. You know, whether that is a national data repository, whether
it is a federated model, et cetera, et cetera, it is all about the role of data
aggregators and it is also, obviously, all about scaling up.

But the issues involved in scaling up are partially architectural. They are
partially technical, but they are also, I think, largely political issues and I
don’t mean political necessarily in the sense of partisan, but that is part of
it. I think we need to recognize that the discussions in other countries as Dr.
Lansky referred to, there is a lot to be learned from those. They are sobering.
They are thought provoking and the discussions change as the politics change
and as administrations change.

That is especially true when it comes to data aggregation issues. John
mentioned — and I don’t want to misquote you here. So, I am going to try to
state this very carefully. My interpretation was that it is difficult to make a
business case for quality. You want to restate that in a way that you are more
comfortable with, John?

DR. LUMPKIN: No, I wouldn’t say it is difficult. There is a difference
between the — I have to start someplace else to get back to explain what I
meant. The way a market works is that you have a free exchange of information
and that drives people to achieve a product that is an ideal product, depending
upon the state of the market. So, if you have a market that doesn’t value
quality, then you are not going to have that as one of the criteria. Volume may
be a criteria. We saw that at the end of World War II, where the focus was
let’s get out a lot of consumer products because we haven’t had anything for
the last four or five years. But the quality of those individual products
pretty much staying.

When the Japanese entered the market, then the basis of competition shifted
from how many products can you put out to how high the quality of those
products were. Right now, the market in health care is not — the competition
is not based upon quality.

DR. FRIEDMAN: I guess I would add to that that the competition certainly
isn’t based upon the secondary uses of desktop electronic medical records for
population health measurement purposes. I wish I could find a briefer way of
saying that, but I think that is a point that, you know, to the extent part of
this discussion is the potential use of desktop electronic medical records for
population health. I think that is a point that needs to be acknowledged and
discussed.

Fifth and finally, I want to get back to John’s about Michael Lewis’s book,
Money Ball. John said he isn’t a baseball fan and if we had had this
discussion a month ago, I would have said that is because John is from Chicago
and I am because I am from Boston and Chicago hasn’t won a World Series since
1917 and we won one in 2004.

But it is a month later. But I think one of the things that is really
disturbing and instructive is the extent to which even in baseball, there is a
more vibrant, active and public discussion of measurement, of lead quality
measurements of team quality measurement, of player quality, than there is
around population health. I mean, it is really quite remarkable and has quite
remarkable contrast.

I am sure one could — our current Supreme Court nominee could speak to
this, but, you know, this is a — let me just read you the names of a couple of
statistics. This is a book called Mind Game: How the Boston Red Sox Got
Smart and Won the World Series and Created a New Blueprint for Winning.
This is from a group that is one of the many groups that markets baseball
statistics very successfully. EQA, equivalent average, a completely new measure
that they have invented. Best single season equivalent average, career best
equivalent run, fielding runs above average; career best fielding runs above
average, pitching runs above replacement, et cetera, et cetera, et cetera. I
mean, there is — we just don’t have this going on in population health. We
don’t have this going on in population health. We don’t have this going on
certainly in the U.S. in terms of measuring the quality of population health
and we certainly don’t have the discussion going on around how electronic
medical records might be used to improve the measurement of population health.

Agenda Item: Panel and Workgroup
Discussion

MR. HUNGATE: This should be an interesting discussion. The range of content
is impressive and appreciated.

David.

DR. KIBBE: Can I start to make a couple of comments? Unfortunately, I am
going to have to leave. I have to catch a plane and I won’t be here for the
entire discussion. I apologize for that, but I couldn’t avoid it.

I think this has been extraordinary. I have been listening very
intensively. I think everybody here has something uniquely different to say. I
would like to make a couple of comments. One is I agree with David Lansky’s
criticisms of the desktop computer and what is happening with respect to some
of the inefficiencies that are occurring when every small institution, medical
practice, all the way up to a hospital has its own infrastructure and I would
love to see a world in which we had three or four very, very good companies
that were providing very low cost ASP model network systems.

The problem is is that I don’t see that happening very quickly. What I do
see happening is, one, even very small medical practices are very intensely
interested now in inquiring their own infrastructures. Some of them are buying
ASP model systems, but it is still their own infrastructure. I think that is
even more intense at the level of a hospital. So, I don’t think that we can
fight too hard up hill against that trend because that trend is really
motivated by a set of professionalism, of values. You know, the electronic
health record for physicians has been three years away for 20 years and it is
finally here. You know, it really is three years away.

The other thing is is that what worries me about some of the network
systems is that I see we are building around the country extensive, very
expensive private networks. The larger the organization, of course, the larger
their network is able to be and a lot more private it has to be. I think we are
going to expend amounts of money and effort and probably go through a lot of
pain over the next five to ten years as these private networks establish
themselves more and more vigorously and powerfully in certain parts of the
country and use that private network in some way the way Prodigy did when early
— before the Internet came along in a predatory kind of market-driven way.

The reason that I mention that is because I think both of those trends in
some ways are going to make it more and more difficult to get the data that we
want to do population studies on patients. So, we have to understand, I think,
that this situation in terms of what we want, that is, how can we get the best
quality, most accurate information in the very quick turnaround time into a
trusted and competent data aggregator so that we can now analyze it and get it
back to people so we understand what the quality is, efficiencies are and
compare.

I think actually it is going to get worse before it gets better. I think we
are at risk for things really falling apart.

MR. HUNGATE: What time do you have to leave?

DR. KIBBE: I have to leave in ten minutes.

MR. HUNGATE: So, let’s make sure that any questions that we are
particularly — for David, we get asked in the next ten minutes. Can we do
that?

Right now, I would like to pose an issue a little bit in advance. I am
wondering — and I think speaks to part of what David Lansky was talking about.
Is it going to be essential to have some kind of population-based measurement
system, which becomes a benchmark against which others can judge their own
performance? Is there an essential missing ingredient at the population level
that could be a better enforcing function for the change that we need?

DR. KIBBE: David’s point wasn’t — one of your points, we don’t have the
political will to do that and I think that is one of the issues. How do we get
that?

MR. HUNGATE: That is a question. Others?

DR. SCANLON: I wanted to ask you a question and it is related to what
Justine said about the issue of need for dynamic capacity within electronic
health records. Because I think of it as a threat. When you encounter the need
to retrofit because the demands of the external world are changing, it lowers
your enthusiasm for doing this. Given that you said that we are — I think you
are one of the more optimistic people I have heard in terms of the growing
enthusiasm for physicians adopting particularly small practices, the question
is how much of this has been a problem in the past, how much of it do you see
as a problem in the future as we — you know, pay for performance is now
getting a little bit of momentum and we are starting to think of sets of
measures and regardless of how ill-conceived they may be, it has gotten some
momentum and we may see reality there.

How much of a problem do you see it becoming and then I guess what can we
do about this? I mean, where is the fix in this?

DR. KIBBE: I am not sure I know the answer to the fix in this, but a couple
of comments about it. One is, I think David is right is that even if you have
the best electronic health record in your practice, let’s say you use one from
G.E. Centricity. I was just at the G.E. Users Group giving a keynote yesterday
in Dallas, or — you pay a lot of money for a system and it really has a lot of
information in it. There is still this enormous gap between what you have got
in your electronic health records database and what the health plan has. The
health plans aren’t sending you all of that data.

You understand what I am saying. So, there is this issue of where does the
data repose in any way that would allow for it to be aggregated in a
meaningful, all payer patients centered way. The approach that we have taken
the continuity of care record is to say look, focus on getting a set of data
about a patient in an Internet standard, XML and allow that to be extensible so
that we can create a vehicle, if you will, a vesicle or container for that
information, which would be completely independent of the electronic health
record or the database from where it came. That may or may not work, but I
think right now the problem is we don’t have any centralized, competent,
trusted entity to aggregate data from all these different sources.

If we took that upon ourselves, who would pay for that? That is a huge
issue.

DR. SCANLON: I think also in your slides when you talked about the uses of
a record in an office, the last line, which essentially was about how do we
retrieve this information for external purposes. It is one thing for a
physician to be able to review an electronic record. It is another thing to be
able to extract something for all patients. It is that capacity that I think we
are worried about some in terms of —

DR. KIBBE: I think the continuity of care record has enormous potential for
that in the future because it really creates a file format, a structure for
structuring data that is completely vendor neutral, completely information
system neutral. It really only cares about the data and the structure and it is
using an Internet standard that is well used and well understood and the tools
and skill sets are already developed in other industries. But I think that, you
know, what we will have if we aren’t careful is we will build these systems and
people will buy them and use them and we won’t be able to get the data out that
we need from that particular source when we decide that we have got a data
aggregator here to get it.

MS. MC CALL: Thank you. I have got some questions for you, David. I wanted
to thank you before I asked — for the remarks that you shared with us today
and the enthusiasm I think that is obvious in the comments that you shared.

The questions that I have — it is actually kind of two parts and the first
one is related to the enthusiasm that you see on the part of practices and
specifically small practices. Do you see in that enthusiasm an increasing
adoption, a desire to actually have measures or some sort of feedback on — I
don’t know if we want to call it quality or whatever, that somehow that that
will come as a part of EHRs and that somehow that they do want it?

DR. KIBBE: Well, I think that one of the things that is a bit of a
disconnect here and it comes up in Bob Miller’s article that was — Rob
Miller’s article that was published. It was a very good article. I think that
when a family physician group comes to me, to my center for help, they are very
enthusiastic and they are focused on quality, but they are not defining quality
as outputting measures from my system and getting it back.

They are defining quality in a more sort of global but practice centered
way. How can I and my practice and my colleagues function more efficiently? How
can our work flow be better?

They often get also confused with and comingled with how can my practice do
better financially because — those issues are tied up, but the thing that they
are not thinking about — I think this is the question you want — they are not
thinking about or a small section of them are, a small subset, how can I use
this system to export all of my hemoglobin A1Cs on all my patients to someplace
that will help me get the information.

MS. MC CALL: Right. Then the second part of the question because that
becomes important and I think it gets to maybe some things everybody has been
talking about, which is lenses that we view things through and what do people
see. Before I ask the second question, I want to introduce another metaphor,
which is that of a nervous system. And I think that then what you had talked
about in terms on the secondary uses of data and if you think of this kind of
synaptic response and then going off to a brain, but some things don’t go to a
brain. But some things don’t go to a brain. Some things just kind of loop right
back.

I put my hand on the stove. It is immediately going to come off. It didn’t
go up. I didn’t think about it. It just came off and it sounds like what the
immediate feedback that docs want, practices want, is not about going off to a
big brain and secondary uses of data and all of that, that what they want is
something more immediate. What I can’t tell is whether or not they actually
envision something more profound coming after some, you know, cognitive
chewing.

So, with that as a context, I guess I have a question now. You talk about
the continuity of care record and can you and then some other people talk about
the continuity of care record and how we think about that versus a use of EHR
and versus clinical applications and I think that the vocabulary we used, the
concepts we build are still very fuzzy. Can you help differentiate what you
think a good vocabulary should be? Is an EHR the same as a continuity of care?
Is it the same as a clinical lab or are there distinct concepts that are
important for us to tease out and make distinct as we move forward?

DR. KIBBE: Let me take a crack at that because I have to leave and you all
will have an opportunity because this is a very important issue. The semantics
here are really confused. When a physician calls me and says we want help with
an electronic health record, they are talking about a set of software
applications that includes most of the time billing, scheduling and what used
to be called the electronic medical record, clinical information. They are
looking for — and this is a big breakthrough in the last year or so — they
are looking for an integrated system of software in their practice that will do
a whole range of functionality.

Now, sometimes people use the term “electronic record” or
“electronic health record” to mean actually a file, think of a Word
document or a PDF document or a spreadsheet and that is an electronic health
record. What is confusing about that is that that could be something small and
highly structured and very specific, which the continuity of care record is,
right, or it could be all of the records that a patient has ever had, including
images and tons of documents and so forth.

The term “electronic health record” and now we have patient
health record are clearly undefined and we have no idea what we are talking
about most of the time. Let me finish by telling you what the continuity of
care record is and isn’t in that context so you will understand. The continuity
of care record was designed to do basically two things. I have an electronic
health record from Company A and I have an electronic health record from
Company B. This is the integrated software program. It could be Hospital A and
Hospital B, but let’s talk just about ambulatory care.

These are data islands. There is absolutely no way to get any information
from this system into this system because these are proprietary databases. You
can’t take a data set out of NextGen(?) and import into e-clinical works,
electronic health records. It doesn’t work. So, a group of physicians primarily
said, look, one of the first things we really have to have is a limited
operability that would allow a defined data set of health information to go
from this computer system to this computer system and be read and understood in
the same way that when you take a Word document and import it now into a Word
Perfect application, they can understand each other.

It ought to be clinically relevant. So, the CCR was designed to include
sections like patient demographics, problem lists, diagnosis. Any physician who
looks at a CCR immediately gets it because we work with this information all
the time, whether we are in an emergency room or a doctor’s office or whatever.

So, the CCR is a highly defined content standard that structures these data
in XML and now it allows this company to say, okay, we will just export that
data set to the XML. We only have to do that once because then we can export it
the same way every single time. This company says all I have to do is parse
that data from the XML into my database and anytime I am presented with this
file, I can read and interpret it. That is what the CCR is.

So, it is in some ways an electronic health record. It is i some ways a
personal health record, but it was designed primarily to get a data set from
Company A computer to Company B computer in doctor’s offices.

Does that help?

MS. MC CALL: It does. It helps a great deal. I guess when you had talked
about it before because I am not familiar with its technical specifications, I
heard something different. What I heard was the data cloud in the sky, that
somehow it was the longitudinal cradle to grave that had everything about me.

DR. KIBBE: It is more like a snapshot. However, it could be a very powerful
snapshot because if you have got this data set about yourself, if it includes
your immunizations and your medications and your problems, there is a lot of
information in there which could be utilized for quality measurement and if all
of these information systems can read and write to that, then it becomes very
efficient to use that particular data standard for that purpose. I think we
will see that kind of thing emerge.

MS. MC CALL: Okay. Thank you.

MR. HUNGATE: Michael, did you have a question for David also? He is
running, but he —

DR. FITZMAURICE: A couple of maybe more technical questions. One of them
has to do with the continuity of care records. I see it listed as a standard
E2369. Is it an American National Standard? It has been balloted and it is
finally approved as an American National Standard?

DR. KIBBE: It is a fully balloted standard under ASTM International. This
is the largest standard development organization in the United States and it is
fully accredited with ANSI.

DR. FITZMAURICE: So, it becomes a American National Standard when ASTM gets
done with it. Is ASTM done with it?

DR. KIBBE: Yes.

DR. FITZMAURICE: So, is it now an American National Standard, do you know?
I don’t know.

DR. KIBBE: I don’t know if it has gone to that, but it is fully balloted
within ASTM. It will be published by ASTM within the next few weeks.

DR. FITZMAURICE: Okay. Then that would make it an American National
Standard, I believe.

Next question, in one of your slides you say e-links has made progress in
promoting national and industry-wide laboratory results reporting between
clinical labs and practices with electronic health records. There is a coding
system that has been promoted for widespread use, LOINC, logic observations,
identifiers, names and codes is what LOINC stands for.

Do they use LOINC or do they have their own proprietary —

DR. KIBBE: E-Links uses LOINC and it also uses HL7 2.4. So, it is an
agreement around those two standards in the main.

DR. FITZMAURICE: So, this is an example of harmonization not of more
diversity.

DR. KIBBE: Oh, yes. This is very much using the existing standards. And
everything on that page I think with the exception of the CCR is about using
and harmonizing these.

MR. HUNGATE: I think we ought to take a quick break here for about 15
minutes. We have got a lot more discussion to do. I am hoping the rest of you
can stay for that. Is that okay?

Let’s be back, oh, a little bit after 10 after. Let’s shoot for that.

[Brief recess.]

MR. HUNGATE: We have got about 45 minutes here for discussion, continued
discussion. And I would like to try to separate it into the two kind of
discrete content frames of the broad, long term where are we going with this,
what are the barriers, what are the limitations, what is it we are trying to
get done, what are the possibilities. And the more immediate is the EHR as it
is currently conceived going to be adequate in its content to do the things we
want to do?

So, if we could maybe split the time 20/20 in that sense and first start
with the broad one. I want to kick that off with a question that I think ties
together all three of your presentations and see if you think I am on the right
track. It seems to me that the payers are trying to

— they have recognized the variation in cost between places and are trying
to find ways to justify making decisions based on the variations of cost that
are not anti-quality. That is what they are trying to do. It is the motivation.

It seems to me that some of that has shifted from an emphasis on managed
care in the classical way to the disease management tools that are appearing.

Maybe it is not completely that way but there is at least some of the
movement in that direction. My question kind of is directed at does the
emphasis on disease management offer potential to yield a common health
measurement system in a disease by disease way that would serve the broad
aggregation of measurement of public health and evaluation of the health effect
that David Lansky raised in his content. That is a broad question. I hope it is
clear.

DR. VILLAGRA: Let me say a couple of words about the concept of disease
management because I think there is a lingering misconception that this is a
disease by disease kind of retail proposition and although it started that way,
in fact, in fact, freestanding organizations that offer these services sort of
bore the names of the type of services they provided. Mayfield(?) was maternal
and child and core solutions was heart and that kind of thing.

When managed care decided to implement disease management programs for lots
of reasons and put these organizations or these services at risk for the
totality of the patient claim experience. In other words your point of entry
was diabetes, but once you are in it, you are you with all your problems,
health problems.

And you are accountable both on quality and financially and satisfaction
for the totality of that experience. These organizations all expanded their
competencies, horizontally to comprise many diseases clustering around these
type of patients simultaneously. What that produced was a development of
electronic health records that was able to house the information across
diseases. Word processes that accumulated information especially from claims by
that disseminated and moved information across specialties across specialties
by necessity and developed information systems that was able to manipulate all
this information with a big financial risk on their back and so some pressure
to perform or essentially be outcompeted by somebody else.

That integration, there was one more dimension of this integration, which I
just not having a name for it, I called it meta-guidelines in a paper I wrote a
couple of years ago, which is the interaction between clinical practice
guidelines when they coexist in the same patients. Some recommendations being
synergistic, some being antagonistic but on a real person, the ability for
these disease management programs to have the business support to do all that.

When you put all of these things together, I believe disease management as
a concept can hold many of the elements of Ed Wagner’s chronic care model. It
is already invested in technology, mass communication infrastructure,
aggregation of clinical content and it has developed a business model that so
far has proven viable.

I will stop there because I think that that is as far as I understand its
potential role. If managed care, let’s say, would retreat from decisions about
medical care at a very granular level, and — decisions back to the delivery
system, we would not have very good quality care and I think disease management
is a potential repository for an entity, maybe even a future institution that
could fulfill that function.

MR. HUNGATE: John and David?

DR. LUMPKIN: Well, I will jump into it. First, a couple of terms. When we
did the report in 2001 on the National Health Information Infrastructure, we
were very careful to stay away from the terms “health records,”
either personal or provider-based. As I struggle for terms, I am kind of like
resting on the term “personal health information system,”
“provider-based health information system, because not all electronic
health records are the same. The key issue is it is not just do you have a way
to record what is going on electronically, but can you provide the decisional
support that enables an individual to meet the challenge of Dan Mathis, which
is the kind of decision making, which exceeds the ability of human cognition.

Having said that, the promise of disease management has to be taken in
context with the transformations that are going in the health care system and
there are other trends that would tend to move away from disease management. Do
you need disease management if you have a really good information system that
provides decision of support so that every doc can manage diabetes in the way
that it ought to be managed.

On one sense you could say, no, you don’t. On the other sense, what we have
learned in a number of areas, and maternal and child health is perhaps the
best, is that if you provide services in a comprehensive way to patients or to
individuals, you have better outcomes, particularly because that means that
there is continuity of care and there isn’t always continuity of care, even if
you have this whole identified source of health care.

But the other disruptive factor is the trend toward the combination of
health savings accounts, which are tied in with high option plans, consumer
driven health care, increasing the activities by payers of care to shift costs
to the individual, as well as, you know, all these other trends, in which case
the information needs become a lot different because what you have with the
disease management systems is you are sort of fixing, you are cobbling together
the system, where fundamental changes is that you can’t really get quality if
people don’t know what quality is and they won’t demand it.

There is increasing evidence and I was just at a presentation yesterday at
the Clinical Scholars Meeting, where there are some surveys that are being done
that the awareness of the public of quality, that there are discrepancies in
levels of care that their variation of care is increasing and that if we can
have consumers and purchasers of care engaged in making decisions based upon
some understanding with transparency of quality and price, it is our belief at
the foundation that we can begin to do different things in the health care
system.

In fact, that is a major area that we are going to be doing some of our
grant making in the future and trying to do that in communities to drive that.
Within that context, I still believe that there will be an important role for
disease management, particularly with those who have chronic disease just
because of the fact that that kind of comprehensive care can be seen as an
adjunct to the care that is given in other venues.

DR. LANSKY: A couple other thoughts. I think this is — Victor described it
— we are talking about a way of virtual integration of the delivery of care
and coordination of care, as John just said. I think from an IT point of view
what is happening is one can imagine it happening at either of two levels but
not in the middle. The upper level, in effect, is the payer or disease
management entity as an aggregator of information across a number of sources.
As you heard Paul Shields, I think, testify to the NHII committee a few months
ago about the health plan, national health plan’s idea of especially
integrating all the digital data under plan auspices, but it would have the
same potential theory, principle, to provide the integration and apply division
support or intelligence for that database and do a lot of good things with it.

The other locus of integration is the patient themselves or the family and
the personal health record, personal health knowledge system, whatever we want
to call it is an alternative focus or locus for integrating that data. Within
the middle are all the individual care settings and data collection points and
they are each so fragmentary in their contact with the person that they are not
able to be the integrators. They are really suppliers of data to some other
function, whether it is at a higher order or a singular order of functionality.

But I think the challenge is — for me, one of the reasons we keep putting
emphasis on the patient as the aggregator is they are the only one who can
supply all the patient source of data about outcome symptoms and quality of
care experience, changing needs and so on. None of the individual professional
data sources can do that. I think there is a reason for work like you are doing
to continue to analyze how can we enable the person to be the virtual
integrator of the information flow around them and around their lives.

The last thing I want to say about disease management, in a sense to me it
is one instance, one of the more successful instances of system innovation and
redesign and it is not the last. What we want to do is allow there to be an
information environment and a quality measurement environment in which this
model and a thousand other models yet undefined will proliferate but also be
tested as to whether they actually make a difference in improving health.

MR. HUNGATE: Very good. Thank you.

Eduardo, you had a question next?

DR. ORTIZ: My question is directed basically at David, but, obviously,
anybody feel free to answer. Indulge me for a minute on my preamble so you
understand the context of my question.

A lot of the potential benefit of electronic health records is to improve
quality. As I was listening to David, it seemed to me that he had some concerns
about what we currently use to assess quality of care. So, you know, he has
talked about process measures. So, we obviously use process measures a lot. As
an example we will say, well, what percentage of patients in the practice who
have coronary artery disease are receiving a beta blocker or aspirin therapy or
statin? That is a performance measure to indicate quality.

We do a lot of that. It sounds like there are some concerns about that. We
also do intermediate outcome measures, which is a step a little further along
than process measures. So, for example, we might say, well, what percentage of
patients that have hypertension have their blood pressure controlled, less than
140 over 90, which we do know that we have good data to show that that is an
intermediate outcome measure, but we know that that is actually related and
linked to important patient-oriented health outcomes.

So, you know, that might be a reasonable measure to use but there is a lot
of intermediate measures that don’t have that association, that we don’t know
that they necessarily improve important patient oriented outcomes. So, a lot of
these measures now, it seems like — and that is what a lot of places are
using. That is what the VA uses and that is what Kaiser is using. That is what
the pay for performance thing — these are the types of measures we want to
use. I think we use a lot of these measures, you know, one, because they are
easy to collect and measure and analyze. So, that is why we do it because it is
there and available.

Some of them we do because there is some evidence for it, but not all of
them and probably not the majority of them. There is not a lot of good
evidence. So, it is obvious and I agree with you that these are probably
sub-optimal in terms of measuring overall quality of care. So, in terms of the
content of quality measures and substance, this is a really important issue
moving forward with electronic health records.

My question is, you know, what are your thoughts or recommendations as to
what we should be measuring and what is needed to move this forward besides
what we are currently doing. That is directed at David, but anybody else feel
free to chime in on that.

DR. LANSKY: I did say in my comments that I think it is very worthwhile for
a physician practice or an enterprise like the VA to measure the kinds of
things you just listed because certainly having done work in the outcomes field
the criticism correctly was that it wasn’t actionable for some who is operating
a specific program or shaping a practice design.

So, I think you should be measuring the things you are measuring. I
wouldn’t want to take us away from that. My comments today were more directed
at national strategy and what is the role of broad public policy as established
in a building like this in setting a both measurement and IT agenda. So, one of
the concerns I have from a sort of microscopic point of view is that the
consumer as they experience their experience their own health care is not
terribly sensitive to, for example, the hospital measures that are now part of
the CMS measurement set for pneumonia and cardiac and so on are not very
consumer relevant measures for someone who is suffering with heart disease or
some family member of someone who is suffering with heart disease. They don’t
talk about angina symptoms, shortness of breath, life experience, lost work,
productivity, lost quality of life with the family, things that are immediately
experienced by the person and are outcomes that that person would like to
improve and that they think they are making a financial investment in the
ability to improve those outcomes that they experience.

So, at a national strategy level I think it is unfortunate that we don’t
have a way to help people understand whether they are making to a provider or
that we are making financially on their behalf through public funded programs
are producing a benefit that they experience in their health.

For those intermediates, those primary intermediate outcomes that you
described are important, but as you say only to the extent they ultimately
contribute to improvements in health. Some of them are going to be sort of hard
endpoints like stroke reduction and some of them will be quality of life
improvements, like angina symptom reduction or improved mobility for someone
with orthopedic concerns. That is where I think some of the focus should be and
one of the reasons the measurement issues I have said we should give some
attention to the personal health record as a platform. If it is possible there
to assess cancer patient’s pain and angina patient’s pain or disruption, an
asthma patient’s ability to sleep through the night or attend school, those are
the kinds of endpoints that we are just completely neglecting.

One of my concerns about the EHR launch is that that platform makes
literally no accommodation for patient supplied endpoint or outcome.

DR. ORTIZ: Let me ask for some of these things then, David, is it your
opinion that we know enough to know what we should be measuring, for example,
someone like the cancer pain thing and the angina scores and we know what it
is, we are just not doing it or do we still need a lot of work even in
determining what we should be measuring to determine whether we are providing
good quality of care?

DR. LANSKY: I don’t think that — there is, obviously, much more we could
learn about how to do it well. I don’t think the state of measurement science
is any less in those outcome categories than it has been in the process
measures. About 10, 15 years ago, there was an acceleration of attention on the
process measures because the data systems were available through primarily
claims to permit us to do that. So, there may be relatively more progress in
the last ten years or so on that. But there is a great body of work. One of the
ironies is because of the clinical trials environment, we have had a very
rigorous set of patient outcome measures in the world of the FDA and clinical
trials for a long time, but they haven’t been brought over to the performance
assessment and the evaluative arena very much.

MS. MC CALL: Just a clarifying question on that. I am sorry. To understand
that if you think about the measures that we have, that can be derived from
claims and think of that as having end measures, that there is a lot more that
would be available that could be captured, assuming standards and harmonization
and all that if they won’t attempted to be derived from a claim but attempted
to be derived from systems if designed appropriately that there is a body of
knowledge that could be captured and codified that is much larger?

DR. LANSKY: One example I brought I mentioned earlier, I was on a panel, an
IOM panel that did this report on measuring quality of cancer care in Georgia
and I thought the process was very interesting for me and I thought the
measurement approach they came up with in this project was a very balanced one
in terms of the issues Eduardo is raising, where there are a number of process
measures that the people on the ground in cancer care felt were very important
indicators for themselves of quality of care delivery day by day and it was
also a set of patient centered measures and public health measures in effect
and the long term outcome measures that created a balanced view of cancer care.

So, I think to your question, Carol, I think we know enough, an example
like this particular project, to compile a set of rigorous, well-documented
measures that cover that whole suite.

DR. LUMPKIN: But I think that the key issue, what we don’t really know,
goes back to the story of the guy who is walking out one night and he sees this
man clearly intoxicated, who is looking for his keys. He proceeds to help him
for half an hour, look for his keys under this lamppost and it finally gets a
little bit frustrating. He said, you know, let’s reconstruct this. Now, where
is the last place you remember seeing your keys. He said, well, over there by
my car. Why are you looking here? Because I have a light here.

Much of what we have done in measurement has been driven by the data that
is available and there is a lot of science on, you know, how do you measure
outcomes. My memory is blocking because — but we had a lot of hearings on
that, of the committee, on measuring, you know, scales of function. The problem
is how do you get that data.

Part of the challenge I think is to sort of create the case for collecting
that data in a way that is meaningful. Again, at the meeting I was at just the
last two days, there was a set of 86 measures that were being vetted for
looking at surgical risks, reducing surgical risks for people over 65, who are
undergoing surgery.

One of those measures that the expert panel came up with was the position
of the — appropriately positioning the patient on the table by the
anesthesiologist. What is the value to the anesthesiologist to document that?
When it becomes a value for the anesthesiologist to document it, then the
measurement of that quality and that encounter becomes really — it doesn’t
cost anything to do. So, we have to think about the interplay between systems
development and systems analysis of what is going on and how to improve care
and getting the providers bought into it at the same time that we are doing
with measurement.

So, we have to be careful that our conceptual models of measurement enables
us to get to the granularity that ultimately we should be able to get with an
electronic health record and we think about it sort of as peeling the skin of
an onion.

DR. VILLAGRA: Just a quick comment on the granularity versus integrated
outcomes measurement. I am beginning to see a significant uptake of activity,
quality related activity, aimed at improving specific metrics to cash in on pay
for performance schemes, whenever the money is available. This is done in such
a focused way that I am observing that this may happen at the expense of other
important processes that make the care experience a good one from the patient
perspective and medically that good in general.

When you think about the contributions of measurements to be able to assess
quality with the level of granularity that enabled you to change systems and to
improve constantly, you can superimpose that on a patient centric view where
they do not — they are not thinking of particular measurements or particular
metrics of what just happened. I am related to somebody who had a fractured arm
and experienced infinite transactions in the health care system. The best
integrator is a highly complex cognitive process that takes place in the head
of the patient.

If we can devise a mechanism that creates a business case for that
impression to be captured and measured, the one I came up with is that I would
ask this person to assess the quality of care she received under the care of
this orthopedic surgeon and the team that took care of her three months later
and that that particular assessment would be an authorization for payment for,
let’s say 80 percent of the fee that the orthopedic surgeon charges and that
six months later, that particular patient has to — this person is integrating
in a lot more information that the particular metrics that we can devise,
objective, as well as subjective, and that that person could authorize payment
for not the remaining 20 percent, but they say 30 percent of the remaining
payment, based on satisfaction with care, incorporating technical outcomes and
objective outcomes and build a business case that truly empowers the data
collection system in a way that we are, I think, generally speaking very shy to
allow to happen because it would be in somebody else’s control.

MR. HUNGATE: Very good. Thank you.

We have two more questions on this and then we shift to the other folks.

DR. HOLMES: One of the purposes of these hearings is for the committee to
develop a kind of work plan for the next year or two years. One of the things
that we struggle with is trying — is going back and forth between being very
narrow in focus about, you know, what should the electronic medical record look
like or something versus being very general. I was interested in David’s
comments to the effect that if we just look at the electronic medical record,
that is perhaps too narrow a view, that we should look at digital networks of
information sharing.

Then on the other end, we shouldn’t just look at quality measurement, but
the outcomes of quality measurement, which is after all the purpose of the
whole endeavor. Given that perspective and given, you know, our attempts to lay
out, you know, what we might do over the next couple of years.

Would the three of you maybe comment on what you think would be most useful
for us to pursue in terms of supporting the advancement of quality and health
care?

MR. HUNGATE: Please proceed.

MS. MC CALL: Okay. Top three wishes.

DR. LUMPKIN: I will start off because it is a challenging question and one
which I much preferred when I was sitting over there.

I think that we have to be careful that we are not looking so far ahead to
where we want to go that we trip over the rock, that we don’t see in front of
us. To that extent, we need to do a combination of things. One is is that with
the small penetration that we have in electronic health records, expecting that
it is going to get larger over time is to look at those kinds of quality
applications that can be inserted into the health record. Let me give an
example of a standard that I think would be important to be developed now and
that is the common interface between a decisional support object and an
electronic health record so that the data can be fed into these objects, which
can be built by the specialty societies and other organizations to abstract
data in a common way.

So, rather than building one for each one of the vendors, building their
own decisional support stuff, there is a common way to feed that in to engines
that could be then built by specialty societies, by other organizations. That
would be one thing. Second is to continue to resist the paradigm of medical
records and think about what can be done when the data that you are trying to
churn is digitized. That is to go back to the work of the committee in 2001 and
think about these in dimensions rather than — in systems rather than
individual documents, that the goal of all of this is to push knowledge down to
the point of service. So, I think defining the terms is going to be very
important.

Then, third, is think about ways that the current system can be implemented
in ways that will enable a patient-centric concept of quality.

DR. LANSKY: I will throw a couple other ideas on the fire. I support John’s
comments, too. I think at this stage of development where we are all very
uncertain about what is going to happen, I would essentially work through
scenarios for the next couple of years and I would develop a set of
architectural assumptions or architectural alternatives, one of which is
essentially broad EHR adoption, another of which is more of the network digital
database model, where labs, pharmacy, images, encounters, claims are out there
and can be accessed.

So, lay out two or three technical architectural models. I would lay out a
set of assumptions about availability of data for public disclosure in which
essentially the issue of rights or intellectual property are in play because I
think that needs much careful analysis. The Katrina health work that we did was
instructive because we discovered that in the space of a week in a crisis that
everyone agreed upon was a humanitarian crisis, business issues and legal
issues and technical issues could all be relaxed and things could be done in a
week.

As soon as the crisis had passed, those walls came back up and we did not
in any way develop a durable solution to what should be. The solvable problem
is that in a week, virtually 70 percent of Americans could have their
medication list available online in a week from now, but the legal and business
issues are significant and they are meaningful. They are not trivial.

So, I think that analysis needs to be done. As we look at this digital
network, whether it is in EHRs or in PBMs, wherever it may be, what are the
rules or expectations about availability of that data for uses of the quality
assessment. When conversely is it — we have to operate on the premise that
only voluntary disclosure by individual data holders is the only way that data
would be made available. That is a very important issue.

A third thing I would do is what the AHIC is doing now, identify a set of
use cases, short term. I would say a three year time frame and basically
identify for the sake of discussion three use cases that you would like to have
answered and then use those to drive analysis. Essentially, if you could
analyze in the context of architecture and policy, if you could then drive
scenarios for three use cases, such as the one I proposed was what is the value
of the Medicare prescription drug benefit and to whom and to provide value and
to what degree and be able to analyze the quality if you will of that program.

I am sure you can think of a dozen other use cases. Pick two or three use
cases and then develop essentially what would the work plan look like to
implement both the IT infrastructure and the information requirements to
analyze that.

DR. VILLAGRA: A couple of thoughts. I would try at all costs to avoid the
potential error of allowing the electronic medical records and all the
technology surrounding the electronic records to get so far ahead of our
executive capabilities against the information and the knowledge that we
generate that we will create a tremendous amount of frustration much like what
we had — we did when we developed guidelines and they sat there and they sat
there and nobody did anything about it in spite of enormous knowledge that it
embodied.

So, that would be to understand what is the delivery infrastructure that is
capable of executing in parallel the acquisition of new data and new knowledge
related to implementation of a health record. That will be the first one.

The second would be an examination of who or what are the potential
aggregators of information. I would suggest that a platform that you can use to
examine that function of aggregator could be built on the function of care
coordination because care coordination has an information knowledge function,
but it also has an operational correlate.

I believe that a concept like disease management but not it as it is out
there today necessarily, could be a place to start and go from there. But I
suspect that the institution or the entity that will function both as
aggregator of knowledge, aggregator of information that would allow analysis of
population health and be able to intersect with a delivery system under the
umbrella of care coordination does not exist today. Simply, we don’t have it.
What are the requisites for this entity or institution?

The third one is just very general and take, perhaps, the Institute of
Medicine report and more clearly articulate what we want as a country in terms
of health care. This is a much longer term or position but remember a few years
back, Ron Widen(?) and Orenn Hatch put a bill in front of the Senate that was
completely ignored that essentially called for an examination, systematic
examination of what we want out of health care, given limited resources and
what are the tradeoffs that we are willing to accept and somehow create what I
call share values that are simple, easy to communicate and easy to understand
for everybody.

We know what it is that we want to measure at the end of the day.

DR. SCANLON: It actually didn’t get ignored. It is part of the NMA and the
work is underway right now.

MR. HUNGATE: Okay. Carol? And then we will segue over to the other — you
need to run, John?

MS. MC CALL: If you can listen while you are packing up.

Actually, I want to extend this theme. Okay? So, you have some wish lists
and I love the items that are on here. Okay? So, the question that I now have
are what do you believe are either the compelling events or the burning
platforms that can be used to kind of ignite some of these issues because not
all of these can necessarily be done or

— order matters, okay, as we try to grow toward the solution. So, think
about what those could be and I have two in mind that I want to ask
specifically about and get your opinion, but there may be others.

Those two, the first one are the chronic care improvement program pilots.
Again, another investment that the government is making and it is a smaller
investment than PDP, where if you make almost a trillion dollar investment, one
would hope to see a business plan for how we are going to see what is coming
out. But could that, in fact, be one of those? And I ask specifically around
that because we actually at Humana, we won one of those awards in the area
surrounding Tampa. As an intervention and as a model that is person centric, it
is wonderful. It is delightful. It takes into account the person and the
families and the caregivers and everything from just what is the experience of
your life and perhaps your death, as well as some of the process metrics and
some of the things that are more classically defined as measures.

So, they are both opportunities for research and which we will do, but are
they a fulcrum because the country will expand that. So, that is the first one.

The second is P for P. We have talked about this as a workgroup before,
kind of waxing and waning on whether or not that is, in fact, a compelling not
event but wall of activity or a burning platform and I keep thinking about
whether or not — you know, it is based on claims. What if it were based on
something that could come out of an EHR? We have talked as a group about
whether or not you could have a partial P for P, kind of a lower case if it is
based on claims and upper case if it is based on something that is based on
something that is based on output, exhaust, if you will, from an EHR or some
sort of clinical application. I don’t know if that is something that you see
could be used.

So, that and any other compelling events that you see out there.

DR. LANSKY: I think the British Excellence Model is the closest example of
using P for P in a way that provides additional rewards for an IT adoption
within the more outcomes oriented approach that they have. They do capture
data, which is beyond what is available from claims. So, I think that is a good
place to go.

I do think the two models you gave as examples are at opposite ends of the
spectrum, where the chronic care improvement projects, like disease management
and the other virtual integrations I talked about are methods of integrating
care. I think all three of us, at least this morning, have talked about the
challenge of integrating care across fragmented systems. So, by coordinating
payment or integrating payment or oversight through a central contractor, that
facilitates the ability to do outcomes oriented measurement and patient
centered measurement.

Conversely, most P for P is fairly fragmentary and it is paying individual
providers for their small episodic contact with a patient and they are not
really trying to — they are not capable of addressing the continuum.

MS. MC CALL: Yes, I did not mean to imply that those were things that would
get at or compel the same items on the wish list. They would touch on very
different attributes.

DR. LUMPKIN: I am just going to toss one thing out here. I think if you are
familiar with the concept of disruptive innovation, I think the disruptive
innovation, I think the disruptive innovation in health care is going to be
personal health records or actually personal health information systems.

Two million people currently have health savings accounts with high option
plans and they are in the position — and that number is growing — of having
to make health care decisions that heretofore have been put in other people’s
laps. Their desire to have the kind of information that they need in order to
make those decisions, I think, is going to be a big push and it is going to be
a push that is going to be felt in many of the places, which make policy
because when you can’t get the data and you won’t need to make the decisions,
you are going to get angry and where do you go but to your elected officials.

MR. HUNGATE: Interesting observation.

MS. MC CALL: Do you believe that the laws are currently — if you as a
consumer, as a person said, look, I want my data, do you think that the laws
are currently in place to enable you to get it electronically?

DR. LUMPKIN: Well, the point is — and that is the reason why I think it is
a disruptive innovation is is that if people want the data and more and more
people are asking for it, providers who are going to look at the bottom line
and saying unless I go electronically, I can’t meet this demand. So, it becomes
another factor that is going to be pushing towards adoption of — in addition
to the ones that David was mentioning.

MR. HUNGATE: Thank you, John.

DR. VILLAGRA: If I can just add one additional thought to your question
about compelling ignition points. The small office or the large physician
practice, adoption, quality improvement processes that are helped by electronic
health records and similar type of aids, I think, boosting the pay for
performance initiative is definitely worthwhile and it has already ignited the
response and the enthusiasm by physicians in practice, but the other area where
it has not been exploited sufficiently is the potential role of quality in
managing risk, meaning medical legal risk.

This is something physicians are extremely sensitive about. Any call to put
together a, let’s say, continuing medical education program or management
systems that lowers medical legal risk and essentially decreases the likelihood
of being sued, that is met with a tremendous response on the part of
physicians. I think if we can continue to explore some of these areas where I
call the utilities that are derived from values that we explore and flesh out,
we can get a lot more mileage out of the existing processes.

An example would be if a payer has information about all patients who are
50 years of age and who have no claims for, say, colonoscopies and that
information can be fed into a quality improvement loop, it also has important
correlation in risk management because the vast majority of legal action
against physicians, particularly primary care physicians is failure to diagnose
and colon cancer and breast cancer are at the top of the list. This is just a
minute example but I think a broader exploration of these potential utilities
that align data and quality with other benefits would be very helpful.

MR. HUNGATE: Very good. Thank you.

We have not gotten to the second part, the short term issues relating to
the adequacy of the EHR. The cultural issues, the other kind of barriers has
taken that time. Let’s see if there are some immediate questions that should be
addressed to that point now before we take another — at least spend 15 minutes
there and make sure that we have got any questions that are sitting right now
covered.

But I think we are going to come back to that more this afternoon when we
get to the developers. So, questions in that context?

You asked one earlier. Do you have any follow-up questions, Bill, about —

DR. SCANLON: It is more, I guess — you mentioned that there is enthusiasm
for pay for performance and I guess I am not sure — I would say there is avid
interest. I am not sure which direction it is ultimately going to go because I
think John’s presentation and yours both set up the fact that we are
potentially on the verge of a transformation of health system and the
marketplace and in that transformation there are going to be losers and — in
John’s presentation to the issue of — that if you look at it from the buyer’s
side, we are very concerned about costs and like to see something done about
that and actually think of information and the flows of information as a tool
to try and influence to try and influence the future path of costs.

I guess I am somewhat pessimistic about pay for performance and in the
introduction, I didn’t say I am from Washington and having been here in
Washington and watched the resistance to incredibly rational small changes and
the successful sort of blockage of small changes. I guess I worry about the
ability to have something that is going to require sustained major change. I
don’t know how — I mean, my cynical side says what we need to do is we need to
sneak up on everybody and have this transformation occur subtly over time and
suddenly everybody wakes up and says, wow, things are different.

But beyond that, I don’t know if you have any suggestions in terms of how
we influence this shift in a way that is going to be more palatable. Pay for
performance here, you know, we are talking about if you go look at the Medicare
Payment Advisory Commission’s recommendations, we are talking about budget
neutrality, take away sort of money from the bottom and give it to the top,
relatively modest rewards. If you look at the British model, where in the U.K.
for the primary care physician, they put a big chunk of additional money on the
table.

Now, they are starting off from such a different base, that was in some
respects a relatively easy thing to do. Our situation is so different that I
kind of have these worries that we are not going to be able to manage to keep
this moving forward. Once it starts to pinch, you know, at this point nobody’s
had any money taken away, at least from the public program.

DR. VILLAGRA: What I would ask is I understand the challenge both
operationally and politically of the need for budget neutrality — I would like
to know more about what is the potential for operating within even a budget
neutral environment that rechannels health care away from inefficient,
ineffective and excessive care in a way that will not impact quality and that
will allow for redistribution of income across the spectrum of that variation
that we know exists.

I understand very well the political barriers to implementing something
like this are enormous, but the only alternative in the near future is to
continue to pay for production and that is a dead end. I mean, I do not see
with the advent of new technologies that we all know are going to be not only
expensive but are going to be extraordinarily good. If we don’t tackle the pay
for performance and the methodology that allows us to shift from pay for
production to pay for outcomes in some measure, be that in a granular way or be
that in a more global patient centric way, I think we are just postponing
perhaps a political solution to all this that will just make it easier on all
of us.

DR. SCANLON: The one slide of John’s where he showed the relationship
between supply and the use of services, I mean, it almost comes down to if we
really start to recognize the quality of services and resultant effects on
health, that the solution, we are only going to do the redistribution is we are
going to have to redistribute the location of providers because as long as we
have that concentration , we are going to end up in this production model where
we reward production.

MR. HUNGATE: Okay. Are we through with the topic for this morning? It seems
to me that we are.

Thank you for excellent contribution at all levels. You are welcome to stay
for the afternoon and participate further if you have the time and interest.
But you don’t need to.

Let’s reconvene at 1 o’clock.

[Whereupon, at 12:05 p.m., the meeting was recessed, to reconvene at 1:03
p.m., the same afternoon, Friday, November 18, 2005.]

A F T E R N O O
N S E S S I O N [1:03
p.m.]

MR. HUNGATE: I think we had better begin to proceed, although we are
missing a few and go through the introductions again.

I am Bob Hungate, chair of the Quality Workgroup, member of the NCVHS,
which is positioned in this discussion as the adviser to HHS on health
information policy. The workgroup specifically working in the quality area. I
chair the workgroup. I will move to my left.

MS. MC CALL: I am Carol McCall. I am vice chair of the Quality Workgroup,
also a member of the full committee of NCVHS. I am vice president of the Center
for Health Metrics, with Humana, as well as on the board of directors of Green
Ribbon Health, which is one of the recent awardees of the Chronic Care
Improvement Pilot. This company has been started in Tampa.

MR. HUNGATE: Dr. Fletcher, it is to you now.

DR. FLETCHER: I am Dr. Fletcher and I am the VA representative. I happen to
be the chief of staff at the VA here in town and we have pretty much a complete
paperless and filmless hospital, which I will be talking about.

Thanks.

DR. HUFF: I am Stan Huff. I am with Intermountain Health Care and the
University of Utah in Salt Lake City. I am a member of the committee, of the
full NCVHS committee and a guest here with the Quality Committee and will be
speaking on behalf of IHC and our electronic health record today.

DR. RUCKER: Don Rucker. I am with Siemens Medical Solutions, USA and we are
a large vendor of health care IT and imaging. I am also on the clinical faculty
at the University of Pennsylvania.

DR. JANES: Gail Janes, staff to the committee, CDC.

DR. ORTIZ: Good afternoon. Eduardo Ortiz. I am staff to the Quality
Workgroup and I am also at the Washington, D.C. VA Medical Center where I am
the associate chief of staff for informatics and a staff physician on the
inpatient and outpatient medical services.

MS. KANAAN: Susan Kanaan. I write for the committee.

DR. HOLMES: Julia Holmes. I am a staff member to the committee and I work
at the National Center for Health Statistics.

DR. CARR: I am Justine Carr, member of the committee and member of the
Quality Workgroup. I am a physician at Beth Israel Deaconess Medical Center and
director of health care quality.

MS. JACKSON: Debbie Jackson, National Center for Health Statistics, CDC,
committee staff.

DR. SCANLON: Bill Scanlon from Health Policy R&D, member of the
workgroup and the committee.

MS. GOVAN-JENKINS: Wanda Govan-Jenkins, National Center for Health
Statistics, CDC, staff to Standards and Security Workgroup.

MS. ALTON: Migna Alton(?). I am program associate for the Quality of Health
Care Team at the Robert Wood Johnson Foundation.

DR. FRIEDMAN: I am Dan Friedman. I am with somewhere between small and
minuscule consulting company called Population and Public Health Information
Services.

MR. ROHDE: I am Dan Rohde. I am with the American Health Information
Management Association.

MR. HUNGATE: Okay. We are all set.

This morning we focused very much on expectations from the electronic
health record in terms of the users of information that might evolve from that.
It focused a lot on the barriers and complications that exist in making this a
reality in improving quality. The intent of this afternoon is to start from the
other side of it and work from the EHR and say how is the EHR positioned to
serve these various demands.

I should express that there is concern on the part of the workgroup about
whether we have adequately understood the needs of the quality agenda in the
rollout of EHRs as they occur. So, we are looking to understand better what we
need to worry about in terms of that meshing downstream.

Agenda Item: Developers/Suppliers of Electronic Health
Records — Panel 2

That said, I would like to turn to Stan Huff, who helped us very much to
understand the secondary uses of data, which has become a core focus of the
attention of the workgroup. That will follow by Peter Geerlofs, then Dr. Rucker
and Dr. Fletcher.

We try to hold comments to maybe 15 minutes to allow more time for
discussion back and forth, which is where we seem to make a lot of progress.

So, Stan, look forward to hearing.

DR. HUFF: Just to start off, I would just like to acknowledge that the
things I am going to present in fact are the work of a lot of people and I
would just like to acknowledge them as mentors that as well as co-creators of
the systems that we are going to talk about.

Just a brief introduction to Intermountain Health Care. We are
not-for-profit corporation with 22 hospitals; 1.4 million patients that we have
electronic medical records on, 24 clinics. We have around 450 employed
physicians and roughly another thousand or so physicians that are closely
aligned and use our inpatient facilities.

My presentation is coming from the perspective of involvement in electronic
health record systems that span the health system, which was developed by Homer
Warner and others starting in the 1970s, a system I worked on when I was
AT&T, Bell Laboratories in the eighties. Then electronic health record
system that IHC developed with 3M during the nineties and then a new system
that we are developing today. So, there is some perspective on different
systems, different environments that I am bringing to this discussion.

Just a quick summary of system design considerations, some obvious things.
Speed is very important. Response time that you have for your users is
incredibly important. Business events trump good system design. That might be
obvious, but in at least two circumstances they were very good systems and
because the systems weren’t selling as well as the producer had anticipated,
you know, those ventures were cancelled basically.

So, a lot of times good system design can be trumped, in fact, by the fact
that it is not succeeding, you know, for whatever reasons as a business. I want
to emphasize in this context, as well as later slides, that good people are the
thing that actually make changes happen in the system. So, that is true about
the system design. It is also true about actually getting quality outputs from
the system. I think we have been successful at IHC as much because people have
had longevity in their position as by the fact that we have made good systems
because the people are there to be able to make a promise to the clinicians
about capabilities and then they stay long enough to actually fulfill those
things and it often takes five to ten years to have any impact on the true
infrastructure of large organizations.

So, that is a consideration. Patient centered longitudinal records, data
sharing from a common repository and I could — I won’t go into the details of
all these things, but that basically reduces the cost of interfacing and makes
it possible to modularly change out a subsystem and make it possible to migrate
to newer applications within a given area without perturbing the whole system.

Common terminology services as a modular part of the architecture and that
is really important in terms of maintainability and using the system for
decision support. Formal information model for the data that you are storing
and, again that comes down to really being able to use the information that you
are capturing, have it consistent over the lifetime of the patient and being
able to share that outside your institution with public health and other
people.

Modular architecture, we, again, believe in trying to purchase the best
software for a given purpose and then integrate using standards and common
terminology. Again, build decision support in from the ground up. There are
important aspects of maintaining decision logic that you want to consider in
the upfront design of the system because decision logic is going to change
rapidly over time. You want to be able to able to develop it quickly and so you
want that to be a modular part of the system and to be a centralized repository
of rules and protocols rather than implementing them as part of the
applications themselves so that you can change the decision logic without
having to redeploy applications or redeploy software.

So, it is a matter of configuring terminology and writing new rules rather
than deploying new software when you want to change and do a new kind of report
or do a new kind of alert or do a new kind of protocol. Then standards are the
future in terms of interoperability. I won’t talk too much about that, but it
is very important to adhere to standards.

So, a driving assumption in the creation of the systems that we work with
at IHC has been that we want to provide vast, least expensive, highest quality
patient care that we can possibly provide and our belief is that we can only
meet that goal by using computers in appropriate ways in the system. So, that
relates to another principle that has come up at least in a peripheral of some
of the conversations. Some systems are designed with the assumption that what
they are trying to do is bring data to a physician or a nurse, who makes a
decision and goes forward. That is a very good thing.

That is certainly better than a written paper chart, but in fact, what we
are trying to do is design a system where the system is an active part of
taking care of the person so that we can real time do alert. We can have the
system an active part of implementing protocols and we find that there are some
things we can only do because the system is an active part. So, that leads to,
in fact, a somewhat more complex architecture than you would have if your goal
was just to bring data to clinicians.

So, the specific kinds of things that we are trying to support are real
time decision support. We are trying to do data sharing, which is not only data
sharing between different hospitals within our system, the data sharing outside
of our system with public health, with clinical trials, multi-centered clinical
trials, all that sort of thing.

We are also trying to share decision support and there is no market for
that right now because there is no common infrastructure based on which people
can share that decision logic, but we feel very sort of passionate about having
that ability because it takes so long to develop the computerized protocols
that one institution can’t bear the cost of doing all of the things that need
to be done. So, we are really committed to that, but we haven’t been able to
find a marketplace or a forum where that can happen yet because of the lack of
standards in this area.

Of course, we want to do bio-surveillance. We want to do data analysis. We
want to do clinical research and clinical trials and those kind of things. Just
so people know when we talk about, you know, real time patient specific
decision support, we are talking about alerting reminders, critiquing,
protocols, patient management, all these things where the computer is very
active in taking care of the patient.

This is just kind of an overblocked diagram of the way our system is set up
today. We have a number of ancillary systems that represent a lab system,
radiology system, pharmacy system, blood gases, x-ray pack systems, those kind
of things. We have inpatient and outpatient systems that are all contributing
to that clinical data repository down in the lower center of the system. All of
the things that are going through an interface engine and in the interface
engine are where things get converted from whatever the representation is in
these external modules, external systems, into a standard structured coded
representation against which we can do the decision logic and against which all
patient care and all patient data access happens. The standard structured
coding that is happening by reference to the health data dictionary that is
shown in pink there, which in that data dictionary, we have our own concepts
that we store in the database, but we have known correspondents, which is
mostly one to one to LOINC codes, SNOMED codes, in our case drug codes that are
coming from the first data bank, drug knowledge base.

So, kind of a big overview. Just a few statistics. Our health care data
dictionary has over 875,000 concepts, 4 1/2 million relationships, 5 million
different representations, different names for the same thing and that is
supported by ten people, who work again in the corporation to support mapping
of the concepts to the ancillary systems, as well as creation of new concepts
and new data structures as we need them to store data in the database. We have
a team of 26 people that are providing interfaces and we have 60 plus different
kinds of interfaces, both HL7 and X12 interfaces. It is roughly a 50/50 split
between clinical data interfaces and what I would call administrative
interfaces. The X12 benefits claims, all that part, versus XL7 for lab,
pharmacy, pathology, microbiology, all of those kind of things.

Because we have multiple hospitals and other things, that 60 different
kinds of interfaces, they get replicated because they are talking to multiple
institutions. So, we have over 700 actual interface instances and that results
in about 3 1/2 million transactions a day. All of those are not against our
clinical data repositories. You know, roughly, again, half of those are billing
sorts of transactions. So, to just talk about the quality issues, we then
instituted a lot of computerized protocols or simple alerts or other kinds of
quality measures.

One of the things that we have implemented is, in fact, care related to
diabetics. The things that we actually instituted were threefold. There is a
report that physicians can pull and what the report shows is for a given
physician, the hemoglobin A1C level for his patients, his or her patients,
versus the hemoglobin A1C level for all of the patients, all of the diabetic
patients in IHC. This spans both inpatient and outpatient environments.

The second thing that they can do or second part of that diabetic is the
creation by the system of a personalized diabetic report and so when a diabetic
is seen in an outpatient clinic, the report looks at the medications, looks at
the hemoglobin A1C. It understands how often certain kinds of tests, such as
hemoglobin A1C, ophthalmologic exams and other things are supposed to be done.
The computer makes recommendations about what should be done. So, that is easy
for the clinicians to follow.

Then the third thing that they can do is pull a report and it shows their
patients who are out of protocol, if you will, whose hemoglobin A1C is high or
who haven’t had a test that they should have had or haven’t had an
ophthalmologic exam and so it is easy for them to get a list, sort of a to-do
list of patients that they need to see or that they need to take action on.

A combination of those things basically you can see over time that the
percent of patients that are getting a hemoglobin A1C test has increased over
time. So, this is a process measure as were talking about before.
Correspondingly, if you look at the number of patients where either their
hemoglobin A1C was not measured or it was greater than 9 1/2, the percentage of
those patients have come down from 34 percent down to 19 percent.

So, you know, we have seen rather dramatic improvement because of the
computerized protocol in this area. This represents a plot of adverse drug
events and initially adverse drug events were reported in our institution
manually and there was a suspicion that there were tremendously more of those
than we were finding. So, we put in computer protocols that watch for — you
know, just watch for high levels, toxic levels of drugs from the laboratory
that looked for treatments from pharmacy to treat adverse drug events, that
sort of thing.

So, what you see, for instance, is that in the first measurement we have
was before we implemented the computerized protocol. So, you see this huge
jump. That represents not actually a change in clinical care, but the fact that
we were now detecting many, many more adverse drug events than we ever detected
before and then the subsequent decline in the number of adverse drug events
represents a real change because we implemented protocols, we were able to
analyze how these adverse drug events were happening and create systems and
changed to the way we provided care, that decreased that number of reactions.
So, the rates today, 2004 to 2005, it has remained pretty stable at about 270
per year and, you know, the difference between the previous rates and this rate
basically represents about a $1 million a year net cost reduction at LDS
hospital along within the institution.

Another thing that we have done is looked at elective inductions for
pregnancies less than — where induction was less than 39 weeks and, again, the
computer’s role in this one isn’t actually — the computer is not active in
implementing this protocol but the data from the computer allowed us to
understand what was happening so that we could institute change. So, it was
easy to find the data to show that, in fact, we were inducing labor in many
more cases than what would be warranted by the clinical condition. By tracking
that, you can see this dramatic reduction in the number of patients that
induced before 39 weeks. You can break that out and show — this is broken out
by a bishop’s score. The bishop’s score is a score that gives you an idea of
the probability that induction is going to be successful. You want to have a
bishop’s score of 9 or greater and if you have a bishop’s score that is lower
than that, then it is unlikely that — you just have a higher risk that
induction is not going to be successful.

So, again, you can see sort of for those people with a bishop’s score of 10
and a bishop’s score of less than 8 and then the overall decline in the number
of induced elective — induced births. This just represents basically the cost
savings that accrue from that.

I won’t go into a lot of the detail but especially if you can prevent —
so, one of the complications from improper induction is the fact that you then
end up with cesarean section because of the stress of the mother or the fetus
because of those early inductions. Of course, if it is the first birth of the
mother, then it is very likely that subsequent births are going to also be
cesarean sections so you have this — you know, if you don’t do it right the
first time, then you have this building of costs that you know are going to
happen in the future.

So, again, this just represents the fact that, you know, the cumulative
savings since 2001, since instituting this, or roughly $10 million in cost
savings to Intermountain Health Care by introducing this particular protocol.
Another interesting study and this one, again, is a hundred percent
computerized. This represents something as simple as bilirubin testing on
babies and, again, you can see, you know, basically a step function change in
behavior when we instituted the protocol and it basically just said we want to
do a hundred percent of testing of babies to make sure who has high bilirubins
and who doesn’t.

You can again — a combination of first measuring and understanding what is
happening and then instituting protocols to manage that show basically, you
know, a very important decrease in the number of babies that have bilirubin
above a certain level. One of the most interesting ones is these counts down
here on the bottom are the ones that you really care about because these are
babies, whose bilirubin was greater than 25 milligrams per deciliter and those
are the babies then that are potential for brain damage or hearing loss or
other serious kind of complications.

You will notice that we are actually down to zero here and at census time
basically, the last 18 months, we have had no — we have had zero babies with a
high level. So, also this chart is showing basically the rate of readmission of
babies with — and you can see that the readmission rate is dramatically
decreased. Now, one of the things that is interesting in terms of the Quality
Workgroup, this and another protocol, this quality improvement actually cost
Intermountain Health Care money because the cost of testing in sum doesn’t
compensate for this decreased rate of readmission. Now, IHC continues to do it
because, obviously, if we didn’t do it, you would have all of this, you would
have that continuing set of babies that have either brain damage or hearing
loss or other kinds of problems, but it points to, in fact, the need to align
in this whole scheme to align incentives with the other programs that are going
on.

This is a situation where, in fact, we lose money doing this but it
provides better care. There are a number of these others and I have probably
gone over my time here, but prophylactic use of antibiotics in surgery,
nosocomial infection monitoring, rule-based billing, reportable diseases,
clinical research are all other kinds of initiatives that are going on at IHC.

So, recommendations, this is really kind of a synthesis from things I have
been thinking about and things that I heard this morning, you know. Just in
time processing has some advantages here. You know, I think one of the
perspectives that has come to me is so if we had interoperability and
everything was perfect in terms of systems that could interoperate in
understanding standards and we could export and import data, it still wouldn’t
equate the data. There is still something else that has to happen for quality
and at Intermountain Health Care we have been successful because we have been
enabled by a good EHR, but in and of itself it wouldn’t have had a quality
impact. We have an impact because we have clinicians like Brent James and Dave
Burton and there are many others in IHC, who worry about the people process of
creating quality improvements. They are the ones who create reports and provide
feedback to the clinicians and that work with the clinicians to say now that we
have good data about what has happening, what change should we make in the
system in order to have an actual increase in the improvement and quality.

I mention again that there is a need to align incentives because the good
data that allows you to do these studies takes time for physician and nurses to
enter and to get good data and they are not often the — don’t benefit as
greatly from the data as some other people do, either the patient or other
administrators. So, we really want to try and figure out a way that people who
collect the data can get benefit from the data, as well as all of the other
people. I mentioned sort of the perverse incentive about newborn bilirubin. The
same sort of thing happens with community acquired pneumonia. I didn’t show the
statistics.

We implemented protocol also around community acquired pneumonia and,
again, we lose money on that protocol because what it means is that we send
people home who have sort of appropriate scores that will allow them to be
treated safely at home and we actually lose money because we send those people
home, rather than admitting them. We get more reimbursement — we would have
gotten more reimbursement had we admitted those patients. So, again, there is
this sort of perverse incentive in some cases to do the wrong thing because of
the way the reimbursement schemes are set up.

So, I think the sum of all of that says how do we initiate change in the
practice of medicine and the EHR enables that, that it comes down to people
processes. As Larry Weed(?) has argued and I have to agree with him, we can’t
make perfect physicians. Physicians don’t — can’t know and can’t remember
everything that they need to do and so the systems can compensate but it takes
an ever-increasingly smarter group of people to tell the computers what is good
and to be able to implement that in protocols that actually change. So, we need
research in order to understand what data to collect and what measures are good
measures of quality and how to implement those and we need a way of sharing the
computerized protocols across institutions when once they are developed and
once they have been tried and tested.

So, I will stop there. I apologize for taking more time that I should have.

MR. HUNGATE: Very good. Thank you. Make sure that we get a copy of that to
put into hard copy for everyone to have.

Let’s shift now. Peter, are you ready?

DR. GEERLOFS: I am.

MR. HUNGATE: Janine is just getting the computer up. Let me take a minute
for housekeeping detail while she gets that up.

Who has a train at what time? You have one at 2:30. At 3:00. And you have
one at 2:30? Just one. We will watch to make sure that we make that work.

If you have any introductory things to say before your slides are up,
Peter, go right ahead.

DR. GEERLOFS: Sure. First of all, I just wanted to say that Stan’s comments
really are a good segue into one of the things I want to stress in my few
minutes here. That is just the notion that an EHR is nothing but a tool, just
like a violin is an instrument and the tool is nothing without the processes,
the people and the thought that goes into how that tool is used.

So, this industry is such an interesting dance because, frankly, we are
sort of alternating between vendors who think they know how the tool could be
used, users who use it in ways that are unexpected, which teaches us and then
we iterate the tool to make it more and more capable as people kind of expand
in their transformed thinking, if you will. So, that is going to be one of the
things I wanted to talk about.

Just briefly, I am the chief medical officer at Allscripts and I will talk
about Allscripts just very, very briefly. I am a family physician by training,
did that for about 20 years and have also been in medical informatics since
about 1981.

Do we have the slides up yet?

MS. MC CALL: We do have paper copies in front of us, though. So, feel free
to actually speak to them.

DR. GEERLOFS: Sure. Why don’t I just start.

Slide No. 1 is just a little bit about who is Allscripts. I am putting it
up less from a sales perspective than from the notion that you may or may not
be aware that especially in the last year to 15 months, this whole world of
electronic health record and physician adoption of it has really kind of turned
on its head. There has been a major sea change, tremendous increased interest,
tremendous increase in effective utilization of these tools, which means that
there has been tremendous learning on the part of organizations, you know, such
as Intermountain, as well as the vendor community.

In our own experience, we have 20,000 plus physicians in most of the
country, utilizing our tools. Currently, our physicians are writing in excess
of a million prescriptions a month electronically, using our tools. I expect
this number is going to double quite easily over this next year. We are
primarily ambulatory focused and primarily large practice focused. So, our
experience to date has been in clinics, typically, the smallest clinic, 20 to
30 physicians, on up to a thousand plus physicians. So, our learning as a
particular bent to it because the larger clinics in general have been much
earlier to adopt these types of products and they have the wherewithal, if you
will, to put processes in place to really use them effectively.

The real challenge as I am sure you are well aware is in the smaller
physician market where those resources aren’t there. One of the things — we
have really been paying attention to this because it isn’t just about the tool.
It is how you institute best practices around abuse. We actually just recently
published a book. It is available on Amazon, called Electronic
Physician, which is a compilation of what we have learned in terms of
tricks of the trade around implementing electronic health records in the kind
of environment where we are. One other comment about our environment.

We don’t have the luxury for our customers to take years to really adapt to
these new tools because as a public company, you know, we are expected to be
successful and make a certain amount of money each quarter. That is good and it
is bad, but the good side is that it has really forced us to say, look, how do
we take a group of, say, a hundred physicians, who may not have had a lot of
say about the purchase of a system such as this. It may have been done for
them. Had a lot of say about the purchase of a system such as this. It may have
been done for them, although, you know, more and more certainly clinicians have
important input, but often the vast majority of clinicians, who are faced with
using a tool such as ours really haven’t had much say.

They may or may not be ready but there are various stages of readiness. How
do you, No. 1, build the tool? And No. 2, how do you build the processes and
the teaching of processes such that in eight months, nine months, no more than
a year, you can get that organization up and running. So, we really don’t have
those kind of luxury of time, which has been challenging but also it has been
good in terms of teaching us a lot. So, what I want to do in these few minutes
is I want to do two things. One is I want to share with you some of the
insights, just a few of the insights that we have learned and then secondly, I
want to get very much kind of down to where the rubber meets the road and I
want to share with you just one example of an approach that we are taking
towards helping our customers improve quality.

I am choosing this particular one because it is not a terribly technically
difficult approach. It is not even one that requires many standards or
intercommunication. All that is important and we are doing it, but it is so
important to recognize that there is a lot of low hanging fruit out there and
to the extent that incentives can be created to help physicians adopt these
tools, independent of all of the bigger kind of broader things that we want to
do nationwide. This is going to have tremendous impact if they are the right
tools and if they are implemented correctly.

So, slide 2 talks a little bit about our philosophy.

MR. HUNGATE: Your slides are up now, Peter.

DR. GEERLOFS: Okay. Great. The slide 2 says “Adweenum”(?) at the
top and Adweenum is an acronym and it has almost become politically incorrect.
Yet it is still the acronym that we sort of use within our company. That is, if
doctors don’t use it, nothing else matters. That could be substituted for if
clinicians don’t use it and, frankly, if patients don’t use it as we are
implementing our personal health record. But, you know, it all really boils
down to the relationship between clinicians and patients and in the ambulatory
— in the hospital information system world, you can put in a system and if the
docs don’t use it effectively, you haven’t really totally failed.

You have got a laboratory information system and a pharmacy system and a
radiology information system and typically those people use those systems quite
effectively. In the ambulatory world, it is all about the docs. If the doc is
not effectively EHR, then in effect that organization is not realizing any
return on investment, either from a quality perspective or a cost savings
perspective. So, this is very much kind of the center of our universe and it
has caused us to do a lot of thinking about why it is that docs don’t use these
systems because, you know, we have had the technology to implement EHRs
nationwide for probably 15 years. So, a lot of it is cultural. A lot of it is
will.

This whole notion of the phases of technology adoption has actually become
a very important sort of learning tool for us. I don’t know if you are familiar
with it. I will go through it just very quickly. The notion is that there
really are three phases whenever any individual human being is introduced to a
new technology. So the substitute of phases, basically I can only really
understand the new technology from the context of the old technology. So, the
classic example is when cars were first introduced what were they called? They
were called horseless carriages because people really couldn’t understand this
new thing, except in the context of the old thing. This is one of the reasons
why it has been so important for us to get rid of the term EMR, electronic
medical record, because that is a highly substituted term. It really is taking
a computer and taking the paper record and putting it in the computer. That is
really kind of what an EMR means.

Frankly, the paper record stinks and has major problems with health care
for a hundred years and we all know that automating a bad process typically
leads to a bad automated process. So, the big challenge, frankly, for vendors
and for physicians in general is to as quickly as possible move past the
substitutive phase into the next phase, innovation. Innovation is where you
kind of have learned to play the instrument a little bit and you start to say
to yourself, gee, you know, I bet you I could do something differently, more
effectively, more efficiently with this tool.

What we have discovered is that once you get a critical mass of clinicians
saying that, they are on their way because they are owning the tool. They are
starting to be creative with it and what we find is that inevitably an
organization that has a critical mass of clinicians who are innovative within a
year, you start to see true transformation happening. Transformation I like to
define is you wake up one morning and you realize that you are using this
technology in ways that you really could not have dreamed of using it before
you had the technology.

Now I say all this because I think it is terribly important. I mean, as
policy makers or advisers to policy makers, one always — I think you are
always tempted to kind of work from the top down. How do you create the
incentives, which I think is terribly important? How do you create the policy
that can drive us in the direction that you want? But I think it is also
important to recognize thinking from the bottom up, which is to the extent that
we are beginning to achieve critical mass of clinicians effectively using these
tools and some of them get to this transformative stage.

We are getting to a level of understanding about how these tools need to
work that we could not have imagined, frankly, a couple of years ago. So,
really the challenge is getting physicians who first start off past this
initial substitute of change. What we have discovered is that there are certain
drivers helping them do this. First of all, if you talk to an individual
physician and I talk to probably 15 to 30 physicians a week, unfortunately, if
you ask them what is most important to them in terms of adopting EHR, almost
all of them are going to say it is speed. I need something that is going to
speed me up. Very few of them will say I am doing this because I want to
improve my quality. That is just a fact of life.

However, if you talk to that same physician a year later and they have
figured out how to use this thing and are now being creative, either innovative
or even transformative, almost all of their questions are how can I do this in
a way that helps me with P for P or how can I do this in a way that helps me
track, you know, my hemoglobin A1Cs, et cetera. But the whole interest in that
clinician shifts overnight.

So, really my plea, I think, to this group is — it is like the old
Gertha(?) quote that if you really want to move something, you simply have to
begin it. In the beginning it is getting this in the hands of as many
clinicians as possible and I think you are going to see a lot of magic happen
and, of course, now this exact same argument, I think, works for getting it in
the hands of as many patients or consumers as possible. So, this whole PHR
concept, I think, is going to take off very much the same way that the EHR is
taking off.

I want to speak just very briefly to deterrents to adoption because I think
there are — well, I don’t know that I want to call them myths or sort of ideas
that are floated out there that really in the real world can be challenging and
that is that if you take someone sort of outside of the industry directly and
say what do you really want in electronic health record and often what they are
going to say is they want a highly prescriptive device that in effect leads the
clinicians through all the things they ought to do. So, you know, very much
prototype driven, i.e., do this step first and then the system is going to go
out and check what is going on and using rules and alerts, et cetera, and, you
know, I think we very well may get there and certainly there are organizations
that have successfully deployed systems that are highly rules based, highly
alert and interruptive oriented.

But they can be very, very challenging, especially in our environment where
we are really dealing with customers that need to get up and running very, very
quickly. So, our view is that the decision support model that we think works
the best — and we certainly use ruled engines and we use alerts where it is
absolutely necessary, things like drug allergies and that kind of stuff, but
what seems to work the best in our environment has been what we call a
referential decision support model. What this means is if you make it really
easy for the doc to do the right thing and somewhat harder to do the wrong
thing, most docs will very happily do the right thing because it both speeds
them up and they get to go home at night, realizing they are doing the right
thing.

So, I will give you some examples. That is really what I want to focus on,
kind of for the rest of the couple minutes here. So, just an example of this is
something that we are newly introducing called Guideline Templates. We used to
call them Care Plan Templates. I will try to give you an overview of this
quickly to give you kind of a sense of it.

Fundamentally, we have developed in house and have had reviewed across the
country and actually by AAFP about 1,200 templates and they are going to grow
to about 2,000 by the end of next year. What these are are sort of guideline
documents that help lead the clinician through a variety of clinical
situations. These are all inclusive. What I mean by that is so many of the sort
of guidelines and rules based approaches have just because of the volume have
been forced to limit themselves to kind of the big ticket items if you will.
Our approach is that we need to create a tool that operates — I don’t care
whether you are seeing a child with a cold, an adult with diabetes or, you
know, a well child exam or prenatal exam, it really needs to cover the entire
gamut of what clinicians do.

So, these templates really help maintenance, acute, chronic disease and
they are highly specific so that, you know, the difference between asthma,
moderately severe in adults versus asthma, mild in a child, same disease states
but obviously the guidelines are very, very different. Second, they are patient
centric. Fundamentally, what these are are a tool to enable the clinician to
very quickly decide on a care plan and then effectively communicate that care
plan with the patient, either in a written document that is a completely
customized patient education document, including precautions, call 911 if this
and home monitoring, et cetera, as well as a document that could be sent
directly through their personal health record, so they have sort of their
instructions, personal instructions from their physician on their personal
health record.

Then finally they are designed to provide decision support and they provide
decision support simply by the way they are organized. I will show you a
picture — I think, is it the next slide? Yes. If you look at the next slide,
there is a lot on here. This is slide 4. This is a screen shot and if you just
look at the center of the screen where it says “ianotropic(?) agents”
and attention to and instructions, diet, lifestyle modifications, basically
this clinician has brought up a template on congestive heart failure and when
he brings it up or she brings it up, what it does is it has a list of meds,
orders, patient instructions, patient precautions, follow-up, what we call
health management plan. In other words, what should I be doing on a periodic
basis for congestive heart failure? How often should I be getting a chest
x-ray? What disease management programs should the patient be in?

In effect, all of this is together in a single document that they can
scroll through. Once they do it once and have selected sort of the standard
things they want to do, the system remembers this as default or he can
specifically set it as default. So, the next time you see a patient, you have
sort of your standard template and all you have to do is really say how is this
patient different from your standard patients. In doing so, we have discovered
that our clinicians can often complete a template in less than a minute and I
will share with you in just a second really what that accomplishes.

But there are a variety of other things here that this picture doesn’t show
effectively. Fundamentally you can reorganize the template in any way. So, with
the medications you can have a group that says here are my first line choices.
Here are my second line choices of medication. All the clinician has to do is
put a check in front of the med. If he wants more information, he can double
click the med, basically bring up a monograph on that medication or he can do a
very quick search on the scholar. As well, the organization can send to that
specific medication item an organizational guideline, which could be just the
text, a paragraph or it could be a whole web page that could at the point of
care provide information about the right way or approach or protocol, what have
you, to order that particular item.

So, probably an awful lot for you to digest, but I wanted to give you a
little bit of a sense this is something that isn’t technologically difficult to
do, really speeds clinicians up and can really drive decisions. Just while we
are here, the little green happy faces are formularies. These are drugs on
formulary for this particular patient.

Obviously, it is possible to insert the guidelines and the sort of
component of this from various stakeholders, not just that enterprise. So, the
very last slide and then I will stop, so, as I have mentioned, this is sort of
a non-threatening approach that really has had the opportunity dramatically to
speed up what the clinician does. As a byproduct of spending that 30 to 40
seconds, the patient gets his problem list updated, his medication list
updated, allergies updated, orders and medication list updated.

The assessment plan is automatically dumped into the note and the patient
gets this completely customized patient education piece. It drives the health
management plan, which is a grid-like control that shows the clinician all of
the things that are scheduled for this patient and it automatically captures
the most important discrete data. This is an important one because one of the
great barriers, frankly, to the electronic health record is folks who say, hey,
you have got to use pick lists to document the note.

You have to choose from lists and do what we call a structured note. This
can be very, very time-consuming for folks and the truth is that most of the
data necessary for research and for quality really comes from the assessment
plan. What are the diagnoses and what was done for it? So, using care planning
in effect, all of that is captured automatically and the last thought that I
will leave you with, we are doing a lot with patient questionnaires where
patients do either web-based or kiosk-based questionnaires prior to coming into
the dock.

But we have set up the template so that automatically based on what I have
selected, the patient can get a questionnaire in a specified time interval that
is specific to what I have done. So, as a small example, a lot of patients who
were prescribed ace inhibitors get a cough and they stop the meds and you only
find that out the next time they come back in. The system can be set up so that
every time I write a prescription for an ace inhibitor, the patient
automatically transparent to me, the doc, gets a little questionnaire ten days
later asking about the cost and with the ability for that information to come
back and alert me.

So, I will stop here and hopefully in questions we can go further.

MR. HUNGATE: Very good. Thank you.

Okay. Dr. Rucker, are you ready to plug in there?

DR. RUCKER: My name is Don Rucker. I am with Siemens and maybe give a
little bit of this sort of another industry perspective on how do you get
statistics around quality, which I think is really the focus of the workgroup
and how might you go about that and how might you think about that and some of
the things that we have done and some of the tools that we think are
particularly — have some very high potential for really changing the dynamic
of this.

I think sort of first what is implicit in a lot of what we have already
heard is if you want quality, the best way to find it is not to look for it.
That is, you know, minimally counterintuitive, but, you know, the reality is if
you look at folks who have changed the world and improved the quality of, you
know, their product or service, they have done it in ways that are remarkably
different from sort of looking for quality per se.

Here are a couple of case studies of people who have fundamentally changed
the way we live in America and really improved the quality of their service,
but they have done it entirely through being very clever about process
automation. I think that is sort of the focal point of process automation and
how do we drive that in health care is the way to go. So, the four little case
studies, the first is a very young John D. Rockefeller and Standard Oil and we
sort of think Rockefeller as a robber baron, who somehow negotiated out lower
rates on, you know, shipping his oil by train, but his real business insight
was fundamentally having a uniform system of refineries and guaranteeing the
quality of every barrel of kerosene. Right? This was, you know, Titusville,
Drakes Oil Well and kerosene in the 1860s and 1870s was an ad mixture of dirt
and kerosene.

John D. Rockefeller made his living and his fortune by saying he was going
to provide 90 percent pure kerosene. So, I think those are the same numbers
that Stan was looking at for the hemoglobin A1Cs, as I believe — I think we
are sort of right there.

Thinking, of course, in the 1870s, that was so rare and so novel, having
standards, that he decided to call the company, the little company that he
started, Standard Oil. Right? You know, now standard means we didn’t get the
alloy wheels and the power windows. We are not wildly dissimilar. And, you
know, you could say, well, that was manufacturing but in a lot of ways it was
actually a service industry.

Henry Ford, I think we all know the standardization there, but it is worth
thinking about two more modern pioneers in service industry standardization,
which is after all what we are about in health care. This is Mr. Crock, who
founded McDonald’s as a large business or he bought it as a very, very small
business. He set about figuring out how to totally reengineer the making and
delivery of hamburgers.

Now, you say, well, what does that have to do with health care? Obviously,
present little in some ways, but that fundamental rethinking, that fundamental
breaking down, what are the steps? How can we rethink the hamburger? That is I
think what we need.

Another more recent pioneer in service industries, I just flew out of the
Memphis airport this morning. This is Fred Smith, the founder of FedEx. So, the
ability to have certainty, you know, this sort of gets to the IOM quality chasm
things, you know, the timeliness. We are willing to pay roughly 50 times as
much to get a piece of first class mail, absolutely, positively guaranteed. We
still do this. The U.S. Post Office is pretty good these days. You know, first
class mail actually — I mean, when I was a kid — I won’t say when that was,
but it was a long time ago — you know, that was a sort of random event. This
week or it might get their next week. Right now, there is no place for mail to
hide, with the volumes of mail. So, it actually gets there pretty quickly.

But for that extra degree of certainty, we are willing to pay a small
fortune. So, can we identify process automation in health care to drive this
underlying statistic because we know that manual quality and manual quality
data is just plain too expensive. Now, the problem with process reengineering
is, you know, the committee is called the last thing, you know, vital health
statistics. Maybe you should rethink the name and call it vital health
processes rather than statistics because if you ain’t good on statistics, you
are sort of a little bit looking in the wrong corner of the world.

I mean, how do we do processes and what do we identify there. I think our
target should not be statistics but what are the things we want to change and
then work backwards to the variables. In a conversation I had last night with
one of our customers down in central Mississippi, this fellow is a vascular
surgeon and he was complaining that Medicare essentially pays him on net much
less to put in a primary natafistula(?) than to throw some gortex(?) in.
Primary fistulas take longer to put in. You know, an AB Fistula for dialysis
access, what we are talking about, and gortex, but they almost never clot in
the lifetime of the patient, unlike gortex fistulas, which can clot. His
declotting business has gone down by 70 percent, you know, apropos that —
acquired pneumonia. The guy is losing two thirds of his business to do the
right thing. If we targeted not a statistic about this, that or the other, but
statistics, let’s say, on primary fistulas to reengineer that process.

We would get the variance reduction, the quality we want. It is very
interesting looking at all the things that Health and Human Services has done
and Secretary Leavitt and, you know, the regional health initiatives. What is
interesting to me is that that vocabulary and those issues are actually almost
identical to a whole community of issues in computer science called Enterprise
Software Architecture. If you pick up a J2EE, which is a sort of an enterprise
software design paradigm, the issues of networking, of semantic
interoperability, of security, of huge complicated processes that are not
definable up front to reengineer, doing this over multiple sites, over unknown
work flows are essentially the same. So, I think one of the things that the
committee may want to look at in further work is getting in some people who do
enterprise software. I know we have the regional health initiative grants out
there that are joined in an experiment on that, but there is a very similar
vocabulary and a very similar thought process and it may be a specific benefit
just to get somebody, one or two people who are speakers on that area in.

Let me get concrete with a couple specific tools that I think can generate
both interesting health care data and process reengineering. The previous
speaker talked about that. We still as an industry totally get confused on
structured versus free text data.

We impute the benefit of one to the cost of the other and the cost of one
to the benefit of the other. You know, as the previous speaker mentioned, you
know, the things a really important problem with — you know, plans are much
more important than signs and symptoms. So, I think there needs to be a
conscious statement by the committee if it hasn’t been and I think you may have
already done that on that, there are some clever tools now with XML and other
technologies that you can do here. I would disagree with the previous speaker
and I don’t think this is a complicated sociologic thing to get doctors to
change. I am not saying it is easy. It is not easy, but when you look at doctor
behavior, I have — I was one of the principals in building the first
Windows-based EMR starting on Windows 2.1 in 1988, not as long as the folks in
Intermountain Health Care, but, you know, I have been doing this for a long
time. I see very little physician behavior that can’t be explained by the
amount of time they need to read about — read the screen, navigate from screen
to screen and think about the work flows on that screen.

So, you know, every sort of microsecond of time on screens I think is
really what we have to focus on and when you do that doctors are very good at
picking up new technology and I think are very good micromanagers of their
time. So, I would just sort of shy away a little bit from the grand cultural
thing because I think if you make it easy enough people will come.

Other tools, natural language processing. This is a technology that is not
quite there yet because natural language processing means we understand what
the human brain does. That will be next year. You can today go in and do
automated processing of large bodies of narrative text. This is — some of our
researchers have done some work here. There are multiple projects by multiple
groups of researchers throughout the United States taking large bodies of
narrative data and trying to do some classification of that. And, again, to
give you some interesting quality data, for example, our researchers went and
for the implantable defibrillators at South Carolina Heart Center, which is a
monstrously large cardiology practice, they were looking for people who might
be eligible for this device and with a 94 percent accuracy, were able to look
at 61,000 patient charts and come up with 300 odd people who benefited from
this.

So, I think there are some interesting tools where you don’t actually need
total agreement on vocabulary and statistics in order to do it. For angina,
they were able to identify in an automated fashion who is on aspirin and beta
blockers and ace inhibitors, et cetera. As you look on the right here at
basically the same level of accuracy as nurse audits, again, very powerful
industrial quality metrics that don’t strictly require that.

Three more tools to think about. Vocabulary services. I think as a big fan
of SNOMED over the years, I think we have sort of done ourselves a little bit
of a disservice with those things in the sense that — and Dr. Huff mentioned
this or maybe implied this, maybe I am overinterpreting, but having a large
list of many words is really not wildly helpful. It seems wildly helpful, but
it is not as wildly helpful as you think because I may have 200,000 terms. I
cannot put a menu on a doctor’s EMR with 200,000 terms. I am going to get
carpal tunnel syndrome by the time I am 1 percent down that menu. So, as soon
as I have decided these are the 50 terms, I have semantically changed the
nature of the communication because now I am shooting at a pool of 1 of 50
versus 1 of 200,000.

There are some subtle things. So, I would say that what we ought to look at
is not just these raw vocabularies with a little bit of characterization of,
you know, it is fish, fowl, it is a disease. It is a med. It is a symptom, but
really look at richer vocabulary services. We do some stuff where we have very
rich mix of a term dictionary, an entire physician ordering knowledge
representation that is entirely integrated so you can put in all of these rich
behaviors. You can do synonym searches against any part of it and really
abstract that as a layer in toto and it can make a large difference in ease of
adoption because it allows sites to have a nice separable tool for representing
their site specific protocols and behaviors. You can obviously put in national
protocols.

It allows us in a very, very subtle way to get around the absolute bugaboo
of probabilities and rules and alerts — the absolute bugaboo of rules and
alerts, which is probablistic reasoning. I mean, that is why the AI community
in 1980 was not anywhere near successful as those of us who spent time in it
had hoped is because human reasoning is pattern recognition and probablistic
reasoning. So, when you are doing EMRs, you have to figure out how am I going
to accommodate that. That would be a whole talk and then some.

Another set of tools, work flow engines. Microsoft now, for example, in the
Visual Studio 2005 has embedded an entire suite of workflow application tools.
So, workflow engines you can think of as automated flow charts. Take a visual
flow chart and automate each of those steps and tools for that because you can
automate the entire process not just sort of the thinking or the alerting
around it have been very successful in a number of industrial applications. For
example, Intel has gotten rid of all the people in the bunny suits. They used
to have Intel inside and people in the silver lame bunny suits.

Now on the Penny and Poor assembly lines, their fab, they hook up 450
different machine tools in a single human hands free automation. That work flow
engine exchanges 170 million messages a day to get this and, believe me, they
have 27 separate decision support aps(?) to make sure that power point works
fine on our laptop by the time we get to it. So, there are some very rich
automation processes here and you can say, well, health care is more
complicated, but I am not sure that what we do in a hospital is intrinsically
more complicated than a $3 billion fab that has to get literally hundreds of
millions of items to within, you know, tiny fractions of a micron.

HL7, the 3-0 rim has done great work with process automation. It is maybe
too rich for a lot of tastes in terms of the details. It is something that I
think NCVHS may be able to lend a very powerful helping hand.

The last of the five tools I wanted to mention, just as sort of a thought
process in terms of automatic capture of data, generation of quality, is voice
over IP. Our telephone systems, if you go to any hospital or physician office
and just, you know, close your eyes for a second, open them up, you will see a
lot of people on telephones. You know, whom are they calling? What are the
calling for? I remember I was trying to get a hold of, you know, Dr. Carr and
folks and consultants and, you know, we mutually spent a lot of time on the
phone, you know. You know, paging each other and then we would be in a room and
they would be somewhere and we do a lot of that in health care.

That whole Lily Tomlin model, one ringy dingy, you know, point to point,
you know, the tin cans kind of — Alexander Graham Bell, that is actually
history now. There is something called voice over IP, rich protocols, which you
can decide, do I want two human beings synchronously talking to each other or
do I want an asynchronous conversation. There are all kinds of tools to build
stuff in. So, again, automation around telephony — Vocera(?), you are familiar
with a company that is out there in Silicon Valley, has done some interesting
things there.

So, all of these new technologies I think get us wholesale quality data,
takes a lot of analysis. Let me conclude with the simple moron version of
quality. This is sort of something I sort of thought about over the last couple
of years. I have been involved in redesigning our computerized physician order
entry and have been lucky enough to sort of install, you know, some of this
handiwork in about 20, 25 of our customers, enterprise customers. So, based on,
you know, roughly about a hundred thousand physician orders placed today. The
real issue on quality you can often net out, the cycle time.

You can say — and, you know, the core measures do this. I think you have
some mention of that in the committee document. If you want a single statistic
in complicated environments on what is working, cycle time is a wonderful
statistic. Here is some data published by Ohio State a couple of years ago.
Now, you could argue with what the baseline was, but they took their time —
first dose of medications from 5 1/2 hours pre-CPOE, post-CPOE of 1 1/2 hours.
Now, you might say that was not the most efficient pre. We have a life span, a
four hospital chain in Rhode Island. They took their medication time from when
the physician ordered it to when it was in a pixus(?) on the nursing unit from
90 minutes to 10.75 minutes. So, just under 11 minutes. Right?

If you are septic, you need an antibiotic, that is a 10 percent mortality
reduction right off — again, connectivity cycle time. The other thing, Bob and
I were talking about cycle time over lunch. The other beauty about cycle time
is physicians and nurses aren’t trained about process reengineering. You know,
some of us do it. We are obviously here because we have a taste for it. It you
just say clinicians, this takes two hours. Why does it take two hours? That
conversation empowers clinicians to reengineer their thing in a far easier way
than saying here is, you know, Gerand’s(?) book or here is Demming or here is,
you know, some big sort — Peter Drucker, you know. Here is some big
engineering thing.

What are the components that empowers discussion. So, I think NCVHS could
come up with a metric of cycle time. Last example, Cincinnati Children’s
measured by hour how many orders were placed pre and post-CPOE, you can’t
actually interpret all this data because it is too messy, but the first line,
the pre-CPOE was 11:00 a.m. for orders placed. Post-CPOE, so they have all
their residents and attendings rounding on wireless with CPOE on wireless
carts. So, they are placing orders as they round. Patients are getting x-rays
as they are walking down the hall, rather than going back to the nursing
station and, you know, finding the chart and writing an order and then someone
in the afternoon radiology comes.

They have taken — this was the first couple weeks. They are now 1 1/2
hours earlier on average for every single order placed in that 400 bed
institution. So, tremendous improvements on cycle time.

Let me conclude, the best quality data actually comes not specifically from
collecting quality data, but as a byproduct of process automation. I think we
owe it to ourselves to be very clever about vocabulary tools and services
rather than just saying go to the large national vocabularies. If you want one
stop shopping, you know, cycle time is wonderful and, you know, it is an
exciting time. HHS has some great initiatives coming up with, you know, all the
standardization, you know, the regional health initiatives, which are great,
you know, experiments in nature.

Plan B, if none of this works, just pay for it. Lots of performance. Don’t
pay for five core measures or ten. Those will be gamed. If you pay for hundreds
of core measures, people will have to buy IT.

Let me conclude — sometimes you just need a good picture.

Thank you very much.

MR. HUNGATE: Very good. Thank you.

Dr. Fletcher, another switch on the plug.

DR. FLETCHER: Earlier I mentioned I was chief of staff at the VA here in
town and it is kind of interesting to hear people’s history in IT. I have been
there since 1972. I think I have been in IT since about 1978 or 1979. So, we
have been at it for a long time and have enjoyed it. I think the fact that IT
has been available to us at that hospital is why a lot of us have refused to
leave and I think I am one of those.

The questions that were asked were how does health improvement with
widespread adoption — how does improvement occur with widespread adoption
interconnected with EMR? What I hoped to show is that we have a system that is
widespread. We have about six or seven million patients that are all connected,
all the hospitals, 180 hospitals and about 800 clinics are all connected to the
same system and when we pull up a patient, we fundamentally — and most of the
patients, we can see all the data in anyplace on any patient and that is soon
to be improved by the common health data repository, which I will be coming
into.

Then there are several other questions which I won’t go through in detail,
but I think you will see that we will be answering as I move along.

The organization of our adoption was from the top down the director and
staff became committed to it with the RM chief and then several of us
clinicians who had a lot of experience helping to develop this throughout the
system were on board, but most important to our committees and I think this is
true of most hospitals is the presence of clinicians with high use, but little
computer expertise at least initially. Some of those people have gained a lot
of expertise and are now innovators in and of themselves as we moved along.

We have used this combination of expert and non-expert advisers, created
local ownership whenever possible. I think a system that allows you to
customize templates, customize reminders and set overall rules within each
service even within a hospital makes the best ability to adopt it because the
doctors in those specific areas take ownership of the product. We often package
popular situations with unpopular, discharge summaries everybody loves, labs
and the x-ray images which we have on all our systems at every place in the
hospital. We say that if you don’t do order entry, you won’t get discharge
summaries. If you don’t write the notes, we will have to abandon the images.

In truth in our own system that was actually the fact. If we showed
ourselves very good at order entry, we often were the first persons in the VA
system to adopt images and we were the alpha site, for instance, for that. So,
we would actually link these together and gain some compliance. There is a
point when you don’t have to work anymore at having people adopt it and I think
everybody has been talking about that, that when about 60, 70 percent of use is
achieved, all the doctors start using it and as a matter of fact will not go
back, absolutely will not go back to a paper system because they see so many
advantages.

Sometimes it is not speed, although the speed is extremely important, as
was mentioned earlier. But they see a lot of other advantages in that they can
see the record every time they see the patient, where in the past it was like
50 percent of the time you would actually get the chart when you saw a patient
in our outpatient area. We never have that problem now.

Keeping that software intuitive and user friendly is extremely important
because although we took time for those of us who were on the ground floor to
allow adoption of this whole system, there are residents and interns that come
in and in one day, they have to be using the system. So, it must remain
intuitive and user friendly and I think all of us find that if it is providing
real improvement in patient care, we are for it and favor it fairly strongly.
The physicians are in back of it on those circumstances alone.

This is an example of the cover sheet, which I will not dally on any, but
it has all the problem lists, medications and a bunch of tabs at the bottom
that let you go through and order things, see the notes, see the discharge
summaries. This is a note screen and over on the left shows that if we click on
reminders, it shows the reminders that are important for this patient on this
particular visit. Those reminders will look something like this and our system
links the reminders with some action and we document in a plain text what we
have done — that text message that you see at the bottom of the screen
automatically goes in the note when we have hit the reminders. So, we can
actually solve the reminder problem very, very quickly with documentation.

The record frequently also order right out of the reminder and we can enter
data such as the patient’s most recent blood pressure right through the
reminder. Anything that is important for that we are able to put down. As a
matter of fact, the message at the bottom is often patient education, which
actually the patient can see if they belong my Healthy Vet Program, which is a
personalized health record, see exactly what we intend to have them do.

This is the kind of data that can be rolled back to the group and as you
can see, it is a rank order, which I find extremely valuable and useful. The
names are at the bottom and you can see immediately who is not doing well over
on the right by virtue of the fact that they are over 40 percent of their
patients have a hemoglobin A1C greater than 9 or not done. That particular
person you will notice on the next slide is over on the left. He is now at 3
percent and that is a three month period.

I happen to have, as Dr. Ortiz will know, personally embarrassed that
person by announcing what his numbers were and he claims he did nothing
different from one to the other, but this is now 77 patients at a 3 percent
less than 9 percent. So, I think seeing the data in rank order with all the
other doctors makes the doctor move towards the better, even if it doesn’t get
him pay for performance.

Pay for performance is even better and you can kind of see that where it is
green and blue, they are meeting or exceeding and if you see the previous
slide, you can actually see the blue and green have markedly changed in only a
three month period. So, we are getting better and better very fast on this
particular measure. We need to because it was not good for us in our hospital.

This is a performance measure on the diabetic foot exam and you can see
very quickly that the green and blue, while they change in relationship to each
other, they are a little green and blue, they really didn’t change much on this
one. So, we are not making an inroad on that, although we are doing pretty well
in general.

We can report that back by month and you can see the Dr. DD — in this
instance we have coded the doctors’ names, but you can see that doctor has
markedly improved month by month, but was very, very low to begin with, to see
that — for this doctor to see himself low in relationship to his colleagues
helped produce that change I am sure.

Additionally, there is a second physician showing a marked change, actually
even in the colorectal cancer screen. Colorectal cancer screen, this is
patients who have returned the values and have three values registered, not
just those that have been — had the order given or been given the cards, but
those that have actually returned it and he is obviously talking his patients
into doing it more and more over that period of time.

We are able to pull the data. If we know the database, we can create
automatic reports. We can improve our computer entry that way, but most
importantly, we can improve patient care as you will see.

Here is the hypertensives in our hospital. Hypertension is defined by the
database. Those patients who have had three values, three different days apart,
above 140 over 90, are patients who are hypertensive. Those patients who have
returned to below that number are listed in green. So that in 1998, we had 33
percent return and over time, gradually improving each and every year we are
actually in 2005 up into the 70 percent bracket. We are obviously creating more
and more patients, who are in the normal tensive zone, who were previously
hypertensive and those that were 160 over 100, you can see on the red bar have
gotten markedly improved as time as gone on and we are actually looking at
every single patient in our hospital. This is 13,000 patients. We are not just
taking a review, an EPRP review. As a matter of fact, we look at these numbers
before the EPRP walks through our hospital and say oh, oh, we have got to pick
this one up because we are not doing so well. We can anticipate what their
review will be. As a matter of fact as time goes on and the electronic record
gets adopted nationwide, I think you will be looking at the actual blood
pressure values, not some secondary review of the chart because most of the
pressures will be in the automatic record.

We can compare Baltimore, Martinsburg and Washington with our system and
you can see that in each of the hospitals, the green got better and the red got
less on one year to the next and now I am talking about 31,000 patients. All
these vital signs are now rolled into the health data repository, which we are
now looking at in the VA. That is one of the first things that got put in it
and we are looking at a very interesting phenomena, which I will demonstrate in
just a second. It looks like in September to January all of us did badly for
quality.

You can see the green in Baltimore going to less green in January and you
can see the red going to more red. What did we do? What are we doing wrong?
Well, one of the questions you have got to answer is what did we do last year
from September to January and the nice neat thing about having an electronic
health record is you can examine the data over time and in large numbers of
patients and you can see in this instance that in March of 1999 we were not so
good and we are much better in September. Going from the left hand corner to
the right hand corner, overall this curve is improving but every September we
are better and every winter we are worse, every summer we are better, every
winter we are worse, every summer we are better as we go through the whole
chart. That is typically not just with this six month review, but if we take
all of the blood pressures done in July and done in January, you can see we
have a similar sinusoidal curve. So, we have actually developed the idea that
there is a seasonal change in blood pressures which is reflective of these
thousands and thousands of patients. These are now about 10,000 patients that
go into these numbers.

If we have a different cut point at 160 over a hundred, we have the same
affair, that it is different. Dr. Perlin(?), who is our chief of the PHA in the
VA, asked a very interesting question as he say this data just a few weeks ago,
what happens at 120? I imagine it goes over and above that number as well at
that place as well.

Now, for hypertension we can feed back the data to the doctors on what
percentage of their patients are severe, moderate or normal and the percentage
of drugs they are on. We can do that by patient and you can see that in the
diuretic column in the middle, there are many blanks, are encouraging the
doctors use more and more diuretics. We can actually see the results of that
encouragement.

I notice from August to February we actually got a big jump in diuretic use
in the green zone and we actually are using more central acting — more ace
inhibitors, but that fell off and we have to now reenergize our
antihypertensive program. Same kind of data can be brought up with LDLs. They
can be markedly changed. This is a very short period of time, about seven or
eight months. The LDLs below 120 went from 68 to 83. Our new measure is now
below a hundred and that number we can very majorly address.

We actually take all the patients who are in orange and in red and bring
them back to a special clinic and we very abruptly changed this number. It
isn’t a large number of patients, who are post-MI in our hospital, but we were
able to handle that very fast and change the number for the better.

Some of that is done by, again, another report that goes out to the doctor
and you can see at the bottom of the page, that the lowest result in 1995 is
encouraging the physician to give a call very quickly and get the patient back
on the medications because he is already 187 and 156. He may just stop this
drugs to get up to that other higher number.

This is the result. Across the VA, we are benchmarking these performance
measures for tobacco, beta blocker, breast cancer. You can see all the way
down. We look at Medicare’s numbers and we look at the best possible number
elsewhere and the VA is on all 18 measures better than any others. It is partly
this reminder system inside the electronic health record that allows us to do
this.

The interoperability and connectability is very good. We have remote views
for our data. This is the web that we use to get out data anywhere the patient
has been seen in the VA. ECGs, we can see anywhere that they have been taken.
We just map the news, which is a private system but we can map each of the
muses to our hospital and immediately see in order all of the
electrocardiograms and compare them. A remote image view just started in our
hospital. I think we might have alpha tested it once again, but now it is going
through the rest of the system where if the patient has an x-ray anywhere else
in the system, it will appear in our record and we will see it in order.

We will move in January, I believe, to the health data repository, which
contains all the notes from all of the A visits, which we can see now, but it
is not as it will be when it will actually be part of that patient’s chart as
we pull it up.

We saw 560 patients from Gulfport Armed Forces Retirement Home. They were
evacuated with the Katrina hurricane up to Washington. We put 16 laptops and
three buildings over there, got on line through VPN access and immediately
registered the patients and could see the drugs they had been getting either
from the site that they had come from because we could still see into the
Biloxi VA and the New Orleans VA or into a web site from their pharmacy. So, we
could actually look at the pharmacy that dispensed it, see what medications
there were, get them on their drugs immediately that evening and very, very
quickly.

The patients who had been treated in the VA in New Orleans did not lose
their records, none of them, and we could see them immediately while they were
even in the process of being evacuated, very, very strong. This is a picture of
the electronic health record that the patient sees. He actually sees all of his
progress notes on all the discharge summaries and he can thus, if he walks into
any other doctor’s area and they have the ability to get on the web, he can
actually give them access to this information and they can see it.

In addition, he can see his own reminder system so now it is not just the
doctor that sees reminders, but the patients that seems them as well. And he
can enter in blood pressures, blood sugars, cholesterols, heart rates, weights
and you can see on this particular patient that the patient, once he started
entering his weight, he gradually brought it down from a very high point.

Also, this same patient was hypertensive and came down to a much more
normal level. This patient was perturbating with bursts of hypertension and he
would tell me, he would see that the pressure was up and think what was wrong.
Did I take too much salt in the last day and often that was the case? Sometimes
it was simply he went off his medication. But recording it himself and watching
it, he could get into a much more sustained period where the blood pressures
were in reasonable areas.

This is the way blood pressures need and must be monitored. You can’t just
monitor them every three months or every six months, like doctors do. You have
to be on a day by day basis to get any effect. This is one of the other ways we
have been monitoring weights and blood pressures. In this instance, this
patient had an effusion on the left chest. We took it off. It came right back
up and then it went back more slowly and all of these weights come right into
our own personalized health record but it is because the man steps on a scale
in his home. It goes to a server in the — at that time in VISN 1, now it is in
Austin and then into our health record data so that we can follow them along.

We are able to take data that is in the health record and change the way we
do care. These are pacemaker patients. We have actually been able to follow
when the pacemaker fails and we have changed the calling system to the cut
point. We changed it from calling every three months to every one month, once
we see the data go down. So, you can take the data out of your database and
actually change the care for patients.

You can also in the database analyze things like mortality and see that
dual chamber pacemakers do better than single chamber pacemakers. As a matter
of fact, we can break it down into the type of device and can see it. So, we
will be using data in very unusual ways that we haven’t even thought of when we
are talking about a piece of paper once we know it is all in one system.

So, we can see that the electronic record can improve the health in many
ways. It is obviously doing it we think in our system. The reminders are a
major way we are doing that. There is major value in addition to being able to
see the data from a remote site if the patient moves or as they often do in our
system, move from north to south in the winter, for example. If they carry with
them their own personalized health record, that is a window to what we are
doing in the VA for anybody else to see. We would hope in the near future
everyone else’s data will be equally available on such a system. The ability to
have the electronic medical record show the physician where he stands in his
performance is very easy. I fully adopt the idea that they should be rewarded
for good performance.

In the VA, we have got a performance component to our salary coming up in
January and we are sort of saying if you have very good performance, we will
give you even more money. We are not saying we are going to take anything away,
although it looks that way to the doctor. We are changing medical knowledge. As
we look at the medical knowledge, we are able to pull off these systems over
time. We are obviously, able to get in decision support in a much better way
once the electronic record is fully implanted.

Thank you very much.

MR. HUNGATE: Thank you. We need a copy of those slides, too. I hope that we
have made provision for that.

DR. FLETCHER: They are here.

MR. HUNGATE: Have you got that already, Janine?

Okay. Good. She says she has a copy of it. So, I think we are all set.

You have got a train to catch. How quickly do you have to leave? Like now
or have you got two minutes? Well, let’s make sure any questions get addressed
in your direction first.

Agenda Item: Panel and Workgroup
Discussion

Questions?

DR. RUCKER: Obviously, your docs are very sensitive to sort of the breadth
and scope of this data. Is there — and how do you decide what things to focus
on because I can imagine that you have so much data and so many opportunities
to focus and you haven’t increased the length of the office visit, I am
guessing as part of this. How do you decide what to focus on and do you find
that if you are not focusing on something, other things fall off? Or is there
something that just isn’t done because now they are so metric oriented that
they are working on these 18 metrics and the rest of it just sort of goes a
little bit by the wayside?

DR. FLETCHER: It is a very interesting question and one of the things we
tried to make sure happens is that the performance measure is a logical
improvement in health. When it isn’t, people like Dr. Ortiz and myself holler
even at Central Office and say what are you doing with this one. It doesn’t
make any sense and they not infrequently modify what — their measure, not
infrequently.

MS. MC CALL: Can you describe a little bit more of the structure of the day
as well as you go through? Is this something that is done by individuals? Is it
done by —

DR. FLETCHER: Well, it is done by — I am not talking about two individuals
who reflect what the physicians are saying back to the central organization,
but the performance measures themselves are set centrally but by a committee of
physicians. It is not just performance, quality improvement people, although
Barbara Fleming is very good at this. John Perlin, who is now our leader, was
the chairman of quality improvement in our hospitals. That is why we are, I am
sure, so good at it. But very, very early on, John, when he first came into the
quality improvement group saw the way the electronic health record was going to
take us way up beyond where we had been before and has made that happen.

So, the measure gets set and the VISN directors and the directors are
responsible and that responsibility is very specific such that if we are doing
very poorly in comparison — now, this is an interesting point because I think
this is the key. If VISN 5 — there are 22 in the system — is not near as good
as all the other VISNs. We get concerned and we get worried.

Now, VISN 5 may well be better at hemoglobin A1C than any other private
organization around. I mean, our numbers, we are trying to get below 15 percent
and the mean is about 10 percent and that is very good. The control of blood
pressure may be better, but in comparison with the other hospitals, we are not
good and we get called on it. As a matter of fact, the measures keep changing
in their targets. This year the target will be met when it is 80 percent of the
hospitals. So, it continually rises. Every now and then the hospitals don’t do
well as a group and it levels off. Most frequently, it is just continually,
gradually going up. I think that is a large part of why we are doing so well.
We are comparing each other with each other. It is important for the VISN
director to be as good as the next VISN.

It is important for the director in our hospital to be better than
Baltimore and I always look at Baltimore to make sure that I am not going to be
hollered at that day. We actually then move it right on down to the practicing
physician, but it has to make sense that controlling hypertension is good for
the patient, controlling LDL and acute myocardial infarction, less than a
hundred reduces acute infarctions.

MR. HUNGATE: This sounds to me like an excellent model of clinician control
of the performance measures that self-assessment is enabled against.

DR. FLETCHER: I think the other point that you just made is that the record
itself was largely pushed by physicians. In other words, there were physician
user groups that define what the record ought to be. We had as our major goal
improvement of care of patients and that — and taking care of the patients
rather than where some of them have all the financial incentives of the private
sector, did not have that causing problems. Although I think the record speaks
best even for those. We do an encounter at the end of our visits, which we then
can send right out to the billing process and it helps that as well. So, if you
have the records solid and good, all of those other things will follow.

MR. HUNGATE: Very good.

Carol. I am sure Eduardo can take over the question and answering
questions.

DR. FLETCHER: That is okay.

MS. MC CALL: To continue on in the decision where to focus, once you have
made those decisions about how many different measures are you actually — is
in that set that you are focusing on and actively trying to manage and to
understand and to study?

DR. FLETCHER: That is a good question. It is a lot.

MS. MC CALL: Is it ten? Is it a hundred or a thousand?

DR. FLETCHER: I would say overall it may be more like 50, like it is breast
cancer, it is cervical cancer, it is colorectal cancer in the cancer area. Ace
inhibitors, when the — less than 40 to be on board, when the patient comes in
for congestive heart failure, it is discharged, instructions and so forth. It
is hypertension, 140 over 90 and 160 over a hundred. It is in diabetes foot
care, an eye exam, hemoglobin A1C and the blood pressures. So, it is — if you
add them all up, it is quite a few, but they fit the patient. In other words if
the — and they only come up if the patient needs it. In other words, if the
patient is not a diabetic, you don’t see them. That is the beauty of the
reminder system is that you walk into a patient’s chart, you may have to look
at all the things he has and all the problem lists and then try to say, well, I
should have gotten hemoglobin A1C because I do it every year.

No, no. All you have to do is hit the reminder and it will tell you if the
patient is diabetic and it will tell you whether one has been done in the last
year. If it doesn’t come up at all, one has been done and it is less than 9.
Now, if it is greater than 9, it will come up for you to repeat it every three
months because we want it down as quickly as possible. But in actual fact, it
comes up in relationship to the patient’s basic disease. You will not see
hypertensive reminder if there is no hypertension.

You will not see the heart failure reminders if there is no heart failure
and so forth and so on. So, it may actually be as the patient walks in the
door, your numbers, like 10, for that individual patient as you see than — and
it will be influence of vaccine and things like that. So, when I say 50 or 60,
it is not that much of a — it is not as big a burden as it seems.

DR. CARR: In charting, in the physician charting, how many fields are
modular and how many are narrative? In other words, we were hearing about the
word search, if you have a narrative, but I mean, your blood pressures
obviously, go into a field. I am just trying to get a sense of what the
encounter is like in terms of is it physician typing or filling in or how does
this go?

DR. FLETCHER: The note that we bring up is, again, a customized template.
Some physicians want a blank sheet of paper and other physicians want all the
medications the patients are on, the problem list, recent lab values,

x-ray results. In my instance as a cardiologist, I want the stress test and
the echo.

Now, I can select them and right click, cut them out of the note. I don’t
have to keep them in my note, but they are there in the note when I start and
then I begin the narrative, which is the patient’s current complaints, which I
then type in and then what the patient does. If I am using the reminder for
some of these things, if I have used that ahead of the note, they go in the
note automatically as text, dependent on the box I click. So that things like
blood pressure and lab and pharmacy are specific, concrete areas. Things like
dysmion(?) exertion and so forth are not — signs and symptoms are not at the
moment. They are in the text.

MR. HUNGATE: Further questions here?

Eduardo, go ahead.

DR. ORTIZ: An important thing, too, though, is so it brings in structured
stuff, like problem lists, medications, lab reports, vital signs, the
subjective, you know, like the history and physical part, the physical exam,
the assessment plan are pretext narrative. They are not structured templates,
but you can build your own individual templates. So, for example, if I want to,
and I have done this, I have built my own like comprehensive initial H&P
template, where I have actually put all that stuff in there. I have got one for
low back pain that I have built for myself. You can share it with other people
so people can choose to have a structured templated note or not. I think most
of the — I think it is a mix. Some clinicians have built their own templates
for their notes because they see certain types of patients regularly. Others
just type it in on their own. But it does bring in, as Dr. Fletcher was saying,
typical things like problemless medications, labs, et cetera.

DR. RUCKER: But is it correct to interpret that within the note there,
other than automatically brought in, you are not filling out structured
database fields that you can do, for example, a relational database query on?

DR. ORTIZ: Right. You are not. Exactly. When I see a patient, I am just
typing in basically free text. Exactly.

DR. CARR: Just to reflect a little bit, so if we think about the various
sort of modules, I mean, one part is the fields that get filled in. A second
part is the — well, the patient putting in it. Then third is the decision
support and then fourth, I am wondering about what are the venues where the
physicians come together to look at these data and respond to them. You
generate those reports and then do they just go out electronically or are there
discussions or is there M&Ms or —

DR. FLETCHER: Primary care has a meeting that they give these reports out.
We give the reports out to the doctors, but they have a meeting where they go
over it and they discuss it with each other. It is quite frequent that someone
who is doing poorly just picks up a clue on how to do it better and they
immediately jump the next time around. So, they do help each other.

In those meetings, we emphasize who is doing well and point those people
out and then have those not doing so well go see them and see if they can’t
make a better run at it. We present them almost every week, but we have a
medical executive conference, which I run. I am chief of staff and this data is
given out at that time and that is exactly what we are doing as a hospital.

But as you can see, we can drill down and see what we are doing as
individual clinics, as well as physicians.

DR. CARR: Phenomenal.

DR. FLETCHER: Thank you.

MR. HUNGATE: Thank you. Have a good train ride.

DR. CARR: I would just like to emphasize again that it is not — you know,
we have heard a lot today about it is not just one thing and it is not just one
moment in time. It is serial data. But here I think we are seeing that it is
not just the field, it is not just the data. It is really the aggregating
component, the decision support or the decision — maybe an analytic and then
the venue with the physicians.

MR. HUNGATE: Carol.

MS. MC CALL: I have a question and actually this one is directed to Peter.
Are you still there?

DR. RUCKER: I am.

MS. MC CALL: Wonderful.

We have heard about a little bit of context for this question, Peter. We
have heard a lot about two systems now, both Intermountain, as well as the VA,
both of which are a different model. They are a different organizational design
and so what I would like to hear about is what you encounter — obviously, your
relationship and your experience is very different because you are a provider
of these solutions to physicians that are not part of your company. So, I would
like to hear you talk about what you see out there with respect to the
processes that they have, whether it is some sort of kind of top down approach
for how do we decide where to focus, how do we actually give feedback.

Then related to that, I do have a question about what your system is
actually able to tell them. Both of these systems have a built in process and
does yours have a process for actually bringing back metrics and reporting or
is that something that they do on their own?

DR. RUCKER: So, we are in, I don’t know, 160 some odd large organizations
now and trying to think about generalizing their internal process for deciding
sort of how to use the tool, if I understand your question correctly, sort of
how do you use the tools to obtain certain objectives. So, for example — and
one thing that I have seen happen is the tool sort of enables you to
instantiate at the point of care the behaviors that you would like to see
occur.

So, what it makes possible is, for example, if you have got a monthly
meeting, where you get clinicians together and say, okay, what would we like to
focus on from the clinical quality perspective over this next month. Let’s say
they decide that it is diabetes, Type 2 diabetes. What they can do is they can
think through what it is that they want to accomplish and large portions of
that can be instantiated in the tool so that as they are writing notes or as
they bring a patient up and see what we call the health management plan, which
is somewhat of a different paradigm for showing the clinician the context of
the patient. This is, in effect, a grid that is problem oriented. So, for the
problem that the patient currently has in their problem list, this grid shows
in effect, everything that has been done around that problem of a discrete
nature. So, the bed, what was the last decision around a med, any labs that had
been ordered ad hoc, any orders that are scheduled orders, you know, the
hemoglobin A1C every three months, for example.

What was the last value of that? One click and they get a graph of all the
previous values. When is it overdue. If it is overdue, there is an alert and
the ability to order it right and cut it in that spot. So, the point is that
what we are trying to do is create a tool where as clinicians become more and
more creative around what they want to do with focused disease states as an
example, how do they improve their efficiency and quality around a particular
disease state.

What we want to do is create a tool that enables them to put I guess one
would call it sort of rules, but also the referential information, which is the
approach that we prefer, it guides the clinician at the point of care. So, that
is the — I am not sure if that answers your first question, Carol.

MS. MC CALL: Not quite. Let me try it again because what I heard you say is
that this is a very kind of point of care decision support driven thing where I
can make sure that I am focusing on the right things.

DR. GEERLOFS: As well as, obviously, any electronic health record
accumulates information and can report on a population basis. But a lot of our
focus is — the bottom line is garbage is, garbage out. Unless you are
collecting the right data, then the reports that essentially any good EHR can
create are worthless. So, our focus is on how do you get compliance from the
clinicians and how do you collect — how do you get collect — how do you get
data that is useful without slowing down the clinician?

MS. MC CALL: Understood. So, let’s assume for a moment that all of that is
delightfully so and happening. How does the practice as a practice decide its
focus, No. 1, is that a data driven process? Are you seeing that emerge or as
they have been with it over time. Then the second part is how do they manage
and see whether or not they are making the changes.

So, it is more a meta analysis. So, how do they go about managing the
improvement, the process of improving, which is, you know, what we heard talked
about?

DR. GEERLOFS: Sure. Okay. As a commercial system, the system comes with
certain standard reports that are kind of pre-canned, that enable you to look
at various aspects of patterns of care and as well, it comes with something we
call query panel, which is the ability for non-informaticists, if you will, to
create pretty sophisticated reports that pull out patterns. So, for example, if
the decision is let’s take a look at a particular disease state, such as
diabetes and then looks at, you know, by physician, what are the hemoglobin
A1Cs, what have they been.

So, all of those reports are possible and because we are providing in a way
a totally potential tool, each of our customers chooses to approach how to use
that tool somewhat differently.

MS. MC CALL: Yes, are you seeing them use that?

DR. GEERLOFS: They often start with the canned reports, which can give them
trends around individual clinical performance, clinician performance, as well
as trends around specified D(?) states or they can create their own. So, it is
a difficult question to answer in a way. Our job is to imagine with our
customers all of the possible ways in which they want to envision patterns of
care, population care and be sure that the system is structured so the critical
data elements can be captured and that, obviously, the reporting can pull it
out.

So, we have a little bit less direct influence and even sometimes
understanding of how some of our customers are using it. They often surprise us
and they go beyond what we had even envisioned. That is how we can do our next
level of product.

MS. MC CALL: Because you have a different role, a very different role than
what we have heard about from some other speakers today, I was just wondering
what you saw out there. You know, how well are they doing?

DR. GEERLOFS: It largely depends frankly upon the culture and
sophistication of the organization. They have got a lot of academic medical
centers that are very sophisticated and IDNs that are very sophisticated and we
have a number of smaller practices, you know, in the 30 to 40 range that are
much more focused on collections than on collections than on quality so far,
although they are all starting to pay attention, obviously, to the whole pay
for performance issue and they are starting to ask the right questions. So,
fundamentally we are — just like I said, substitutive, innovative and
transformative around EHR technology. What we are seeing is that we have a wide
range of customers who are at different phases, frankly, of understanding how
to do this.

As a vendor, one of the things we are trying to do is collect experiences
that have worked from among our best clients and share those and kind of create
this best practices situation. I am not sure if this is where you are going
with this, Carol, but I think that one of the great benefits, frankly, on a
national level would be to sort of increase the discussion of what are the —
how to put it — what are the best practices ways of using EHRs, whose ever EHR
to get data out in ways that help practices improve in quality. I think that is
an important national discussion to have.

DR. RUCKER: Don Rucker. Peter, I am guessing that the folks who are using
your templates, the 2000 templates you outlined, in essence, you know, their
use of those sort of guides what happens. I know on the inpatient side, the
thing sort of analogous to your templates that we had to do were really work
with our customers on what type of order sets they want. Now, we provide a
started order set family that, you know, makes it easier for them to edit, but
it really is in the large sites it is the governance around the base component,
which in an outpatient EMR might or an EMR might be more in the templates on
order entry is more on the order sets.

That gets sort of tricky because you have to do a couple things like you
have to get buy-in from everybody in the departments. So, you usually use the
same administrative hierarchy you are using for other things. You have to
monitor that that is kept up. You know, some of our customers are fairly
clever. They just put a finite life on every order set and the people have to
renew it. So, you know, two years out, the order set just is taken out of the
system and then they know that, you know, if people complain, it has been used
and if people don’t complain, it hasn’t been used.

So, I think a lot of — you know, in these high end systems, a lot of it is
just, you know, the substrate that people are working with. If you are just
working with sort of a fairly raw H&P template, you are not going to have
the behavioral collection and if —

DR. GEERLOFS: I think that is exactly right. People can’t expect of the
typical customers that they had time to think all of this up from scratch. So,
we have a little mantra within the company saying the content is key

— is king, actually, is what we say. So, by delivering templates and we
also do note templates in a variety of other contents — what this does is it
gives people that starter set that you were talking about.

It is amazing how when they see something they can very quickly understand
how to make modifications that would make sense to them. But it is a lot
tougher for them to start from scratch.

DR. RUCKER: I would think that content delivery is really, really a key
part to the appropriate utilization of the tool.

MR. HUNGATE: I wonder if I could stimulate a little conversation between
the three of you around the direction of what — I come from an experiential
background at Hewlett Packard, where I learned that we had to do a product
three times before we finally got it right. I am very worried about getting the
implementation in all of these offices done before we have got it right.

So, the question really is what do we have to worry about in what is called
an EHR right now that we will be very happy to be worried about later but very
sad if we didn’t? Can you give us any — the three of you give us some help in
that content? What are the pitfalls that we ought to be sensitive to when we
care about quality improvement being a major piece of what happens from these
systems?

DR. RUCKER: Well, that is a hard question. You know, I mean, you can look
at it a couple of ways. You can certainly look at it from just what is the
quality data we want to measure. You know, it is the hemoglobin A1C. It is the
blood pressure. That somehow you can — that, you can fix after the fact, I
think, in probably multiple vendor systems and multiple implementations.

You can fix sort of the data fields you capture. I think that sort of the
bigger national question, for example, around office vista is, you know, how
much do office practices have to invest in these things and do we want to sort
of — if we push too hard, it is sort of, you know, from the Washington
perspective, you are going to force people to buy a lot of stuff that
fundamentally they are not very happy with and have a backlash.

My sense is that is sort of part of HHS’s worry about Office Vista. You
know, I would be curious of Dr. Ortiz’s impression on that. I mean, the VA
environment is different than an office environment in some, you know, very
fundamental senses. So, I think that is the biggest risk because, you know,
these are expensive systems for, you know, undercapitalized physicians.

MR. HUNGATE: Yes, they are.

DR. GEERLOFS: I was just going to comment that, you know, one of the
promising approaches is the EHR certification approach, which I am sure you are
all aware of. Although the first level of certification is going to be fairly
elementary, certainly the goal is to ratchet it up. I think that we are going
to see certainly — I mean, I have been doing this for too many years really,
but certainly in the last five years, I have really seen a growing sort of
coalescence of functionality. Now, how people actually do it, there is still a
lot of creativity around that, but in terms of what is expected to be there in
terms of functionality, especially the ambulatory EHR that I am so familiar
with, has really been coalescing and, frankly, internally within our company,
from a strategic planning perspective we are assuming that two or three years
from now, that — maybe five years — that the fundamental basic EHR is going
to be a commodity, that it is going to be standardized and that the real
competitive areas are going to be around innovative ways of using content.

There will always be sort of cutting edge, sort of new things that you can
do with this, but the basic bread and butter product, we really believe is
going to move very rapidly towards commodity. Again, my main message today, if
you hear nothing else, is that we really are seeing — we believe we are
approaching a tipping point around this. You have all heard that, but
fundamentally what that means is that a very, very large number of clinicians
in this nation are going to get to a new level of understanding about what this
is all about.

I happen to be an optimist. I really believe that when they get to that new
level of understanding through use of these tools, that in and of itself is
going to have a huge transformative impact on health care and that is going to
be along with all of the other things, you know, that we are doing on a
national level.

But I guess I don’t worry as much maybe about imperfect systems because I
think there are market forces but I think the systems are getting better and
better. The ones that are good enough for physician adoption, I have great
trust that they are all going to be good enough to accomplish what you want to
accomplish.

MR. HUNGATE: Eduardo, do you want to pick up in this conversation with
observations as well, then Stan?

DR. ORTIZ: A couple of things. First, if you have questions directed to the
VA that you would have asked Dr. Fletcher, I will try and answer them if I can.
Second of all, a clarification just because I heard there was some confusion.
Dr. Fletcher uses a lot of acronyms because he has been in the government for a
long time. They are a second nature to him. So, because he kept throwing around
the term “VISN,” people may not know what that means. That stands for
Veterans Integrated Service Networks. What it is is the VA is divided into
regions. So, you have got approximately — I am not sure what our final count
is because it changes depending on different issues. But we have got about 160
to 170 actual hospitals in the country. There are about 850 outpatient clinics
that are freestanding outpatient clinics.

Then we have nursing home services, home health care, et cetera. But then
we have got 22 VISNs and each VISN is a region. So, our VISN here is VISN 5,
which is Washington, D.C., Baltimore, Martinsburg, West Virginia. So, when he
refers to a VISN, it is a regional network and they each have a medical
director and a VISN director and they kind of work together.

So, in case you wanted to know that. He also said EPRP. EPRP is basically a
system that the VA uses for a monthly chart review where people come in and do
hand chart reviews. He was kind of comparing the data that we can get from our
EHR to people coming in and doing chart reviews on a random number of charts.

So, that being said, the EHR — I don’t know if that is what you wanted me
to talk about — all I can tell you about that — so, first of all, I know some
about that, but I am not an expert in Vista Office EHR, but a couple of
observations. One as you pointed out, the Vista system has worked really,
really well for the VA, but we are unique. You know, we are not a typical small
practice with three or four physicians. So, one of the areas that Vista has not
been that strong in is things like practice management. So, that has been one
of the issues in terms of when you roll this out in public domain and give it
to physicians, is this something that is going to work? We don’t know.

It might work in some situations. It may not work because it doesn’t meet
their needs. I think this is something in evolution right now. I mean, part of
the process from what I was at HHS and I am at the VA is that let’s — you
know, we know that Vista works well. It is a tried and true system and let’s
put it out there as something that will help at least alleviate the initial
upfront cost of purchasing a system. It is a public domain system. We can put
it out for free. That doesn’t mean it doesn’t cost anything because you still
have to maintain it and update it and do other things and there are companies
out there that are positioning themselves to be able to do that.

We have got a few pilot projects out there right now where they are putting
it into place. They have put it in some Washington, D.C. public health clinics.
They are putting it in some places in Louisiana. I am not sure what happened
with the hurricane, whether that derailed that temporarily. A couple of places
up in — I think near Stanford, a couple of places. So, there are some pilot
projects to figure out how is this going to work, what are the barriers, what
works, what doesn’t work. So, I think it is something that we are not sure. We
just have to wait and see.

But I think it is a nice thing to throw it out there as part of the
competition out there for giving away a nice proven system. So, that is kind of
what I know, but I am not an expert in that field and there are other people in
the VA that know more about that than I do.

MR. HUNGATE: Let me try another cut at another piece of the same question
that I just tried to ask. You in your comments, Stan, talked about being able
to transfer packages of protocols, decision support, process management tools
and make them available in more than institution.

Now, for instance, could a tool developed at Intermountain Health Care get
moved to the VA and incorporated in its system. The answer is no. Now, it seems
to me that that is a productivity limiter on the system then, that we are not
going to be able to afford to develop any decision support tools if we can’t do
that.

DR. HUFF: Yes. Several comments that I have been piling up here with your
questions, just to — one is I think in this conversation, we need to be
careful to talk about the inpatient environment versus the outpatient
environment because decision support in those two environments are very
different things. In the one case you are doing fairly simple things typically
that, you know, in the outpatient environment you are worried about alerts and
some diabetic reports and other things that are fairly simple. In the inpatient
environment, you are worried about much more complicated things, like weaning
protocols from ventilators and in our case extracorporeal oxygenation protocols
and cancer protocols that span large periods of time, take a lot longer to
develop.

I mean it is fairly simple to do lab alerts or to do drug-drug
interactions. That is well-known. It is a simple look up in a list. These other
things have time oriented aspects and, in fact, there are lots of art in it
rather than science and you have to sort of turn it into science as you develop
the protocol because people, you know — anyway. So, there are enough
differences that I think you ought to be careful about to sort of separate the
inpatient from the outpatient circumstances as we do this discussion.

So, to come back, one of the things that happens today is that even though
you are recording coding data elements, there are sort of two patterns of
things going on. A lot of vendors, when they install a system basically have a
starter set of stuff and then people go ahead and create their terminology and
their order sets and their entirely local terminologies. So, even within the
same vendor, they don’t have the ability to transfer knowledge because the
terminology and the data, they — you know, and that is a barrier to being able
to make fast improvements. It means that even though I develop good order sets,
I can’t give my order sets to somebody else and have them be executable.

It is not that you don’t get some value from it because I can look at what
you did and say do I want to do the same thing and then I can reimplement and
it saves me time in the design, but I really am doing the reimplementation in
the sense that I have to map that to my own terminology, my own software to do
it. So, it is one of those things that it comes way late in the game, that you
see the pain of not standardizing from the start because it is easier to
install it, to just let people make whatever they want. But then when you get
to the stage where you want to share, then you pay a huge penalty to try and
understand and retrofit the data and make it consistent across all of the
sites.

So, that is one of the things that I think, you know, you were asking
specifically what would you do? If you could, you would like people to install
and actually sort of be consistent from the start and overall it would be a
lower cost when you got to the endpoint where you are sharing decision logic
then if you just let everybody do everything and then try and ask after the
question how to do it.

MR. HUNGATE: So, limiting to the inpatient circumstance. Let’s pursue that
a little bit. What does it take to — is it a standards issue in order to
define that kind of a content well enough to make it happen? What is at issue
here and what has to be described, I guess, is what I am trying to — because
it does sound to me like this is a place where there is a great potential
productivity in quality improvement if the development costs can be shared.

DR. RUCKER: I think the heart of it is also that when you do the inpatient
order entry, one of the problems is that the target order bowls all have
different names. Skip the physician name, but, you know, the thing that you
might call the servicemaster or, you know, your sort of charge catalog, I mean,
those are not exactly the same thing, but, you know, every hospital probably
going back to the 1960s, when they did their first billing system has — you
know, some hospital groups — and I don’t know if Intermountain Health Care has
unified their servicemasters. Some have but the actual target orderable is
highly unique for better or worse. Maybe that is an NCVHS type of project to
say we are going to have a uniform servicemaster, as well as some of these
other standards, but I think it is just worth remembering that that is a very
tricky issue that I think is lost on most clinicians, who are really thinking
of the more clinical display vocabularies or vocabularies based on etiology.

MR. HUNGATE: Okay.

Eduardo.

DR. ORTIZ: This is coming from a committee member, not from my VA hat. I
was just going to add to yours is — and I don’t know, since you are the chair,
maybe this isn’t the right thing, but posing to the panel members to say, you
know, not only what does it take, but in a way what are your recommendations to
us as a committee that we should do. You know, what should we be doing, like
maybe what recommendations should we be making to the full committee or to the
Secretary in order to move this forward because this is obviously a very big
challenge.

I know that the VA and Partners Health Care and other groups have been
talking about this because of the fact that this is such a daunting challenge
that it takes so much work and effort to develop these decision support tools,
especially in inpatient settings and to make them where you could basically
just share them with each other.

We have just gotten in some early exploratory talks. I am not sure how we
are going to do this because we think it is a good thing to do. So, anything
that you guys, Stan or any of the panel members have in terms of recommending
ways that we can move forward on this would be appreciated.

MR. HUNGATE: Thank you for the question.

DR. GEERLOFS: This whole issue of — I mentioned earlier the notion of the
EHR certification group and this is something I know that they are struggling
with, this whole issue of to what extent does a, quote, standard EHR have at
its core a standard vocabulary because where it all starts are, you know,
obviously, the vocabularies that are used internally and then EHR has need of a
number of different vocabularies. You know, you have to have the medication
list, if you will. You have to have the vocabulary that you are using for a
problem list, which it can’t necessarily be ICD-9s because, well, I am not sure
how — I need to go into this, but, for example, if you are going to do
structured charting, if you are going to create notes in such a way that
concepts of that note can be captured, you need a fundamental underlying
dictionary.

Large numbers of vendors do this using completely either proprietary or
force their customers to sort of make up these lists themselves and there are a
smaller number of vendors, ourselves included, who are using standardized
vocabularies. We have to use MediComp’s MedCin(?), which is the same vocabulary
that DOD is currently using.

The challenge comes when — and there are a number of these out there. So,
there is SNOMED. You know, there is probably three or four tools that could
possibly be used. One of the great concerns, frankly, is when one of them is
legislated over another. Of course, a lot of what is happening going on right
now is all of the vendors of vocabularies, certainly MediComp, is busily
mapping all of their concepts to SNOMED and, you know, to basically to LOINC
and to basically all of the other standards out there.

We happen to think that MedCin is the — well, let me just say from a
vendor’s perspective, we have got to serve two masters. One master is going to
be this ever-increasing need to be able to both import and export data in ways
that other systems and payers can understand. But the other master is the
clinician using the system and it turns out that a lot of these vocabularies,
SNOMED being a great example, were written for a purpose other than real time
use by a clinician at the point of care, which has created a tremendous burden
on vendors trying to figure out ways of making it user friendly.

Some people are doing it or getting there. They are chipping away at it,
but it is not easy. We happen to have chosen MedCin because it came at this
whole thing from the perspective of the clinician, making it easy for the
clinician and then from there being able to either map out to other
vocabularies or at least it is standardized.

So, this is a really big, complex issue but I do believe that as we move
towards a commoditized EHR, if you will, that standard vocabularies within the
EHRs and not really supporting EHRs, whose direction it is to force customers
to build their own vocabularies, is the right direction.

DR. RUCKER: I think it is also worth pointing out that the vocabularies,
they tend not to have a lot of operational terms in them. Right? I think there
was the comment made about EMR is a poorer choice of words because it is sort
of paving the cow path. But, you know, in an automated world, you know, the
terms are not just, you know, diagnoses and symptoms and things. They are
really — you know, there are transaction terms like “deliver this,”
“evaluate that,” “move this,” you know, “cut
here” type of things. I don’t know. I mean, maybe I am missing one, but I
don’t think there is a lot out there in vocabulary on operational parts of
health care. So then you are left with, you know, almost missing the meat on
these things that you have to sort of then put around the system with some
other type of semantics and you see the struggle on things like the guideline,
you know, the guideline interchange format, the GLIF format, take Arden(?) and
the rules sort of beyond the curly bracket problem.

I mean this is a heavily researched area, this sort of guideline sharing. I
don’t think we have a vocabulary of terms the way, let’s say, a work flow
engine might architect things. There is, you know, B-PEL(?), the business
processing engineering language. We probably need some things like that around
health care.

I would just point out that that is different than most of the things
people talk about when they talk about medical term dictionaries.

DR. GEERLOFS: Although, and, again, I am not trying to put a pitch in for
MediComp, but the reason we chose to go with them is they actually do have a
whole semantic sort of rules engine around it. They understand meaning and
interrelationships, which can create — basically supports the ability, for
example, to do something called intelligent prompting, where you can do
differential diagnoses based on the symptoms, the physicals that you put in.
So, some are getting closer than others, but I think that what is really
important is to not just settle on one, which had a really deep understanding
of all the implications.

MS. MC CALL: This is Carol. I want to ask a question but before I do that I
want to set a reasonable amount of context here. As I do that, just keep in
mind the question, which will be the following. Do you think any of this is
possible? Okay? And maybe state it a little bit more. Is this anything that you
hear being discussed? So, keep that in mind.

Here are some concepts that I want to bring in. It has to do with something
Stan said, creating — he used the term “market.” Can we, in fact,
have a market for certain types of discovery, certain things need to move from
art to science and it is almost as though you need to create a market if you
want to actually transfer from one organization to another, if you want to have
some sort of shared learning that is going on.

So, think of that as a market. When you think about that, there is an
entire movement of open source. So, when you take the concept of open source,
not necessarily the hard technology of that, but the concept of it is that this
is — it is a public good and so those can be done in either completely open or
quasi open environments. Take also that idea of what is happening in the gaming
industry and these massively multi-player games and there is a concept that is,
I guess, sometimes captured with the phrase “harnessing the hive.”
And harnessing the hive is a way for people, not just the programmers but there
is an entire gradient or distribution of sophistication.

Some of the people that play the game are able to customize it, not unlike
what we have been talking about here, but other people that play the game at
the other end, the more sophisticated end actually can come in and do some real
almost programming. Hang on one second, Michael.

Then another concept to bring in has to do with things you may have heard
about with foksonomies(?), tags. I can tag something, things that are happening
in a flicker and those types of things. So, as we wrestle with vocabularies,
MedCin, SNOMED, what is the right thing to call a thing, the idea is that their
could be a standard piece and it is, you know, a handful of vocabularies, but
there is also another piece that is user driven. It is harnessed by the hive.
It is created by the hive. It has come from an open source type of mentality.
So, all of that is context.

Now the question then is is anybody talking about this? The technology
exists.

DR. FITZMAURICE: I just wanted to have a clarifying — by harnessing the
hive, do you mean harnessing the beehive?

MS. MC CALL: It is the — harnessing the hive is just kind of code speak
for — h-i-v-e.

DR. HUFF: The thing that is going on and I think this speaks to some of the
question is beyond making messaging standards, there is a set of people and the
VA has been at the head of this, Ken Rubin and others that are working with the
VA have been at the head of saying let’s standardize services and what that
means is that I could build an application. So, in this example there could be
an Intermountain Health Care order entry and if I adhere to the interface and
pay attention to the shape of the interface there, I could talk to any body’s
back end and the VA could have a back end that does all of the order processing
and that sort of stuff.

Then what that allows basically is that then like the Department of Defense
can adhere to that same interface. They can have an entirely different
application and because it adheres to that service interface, it can again, you
know, do VA orders and then because, you know, the Cerner(?) back end, for
instance, maybe adheres to the back end service interface, then the Department
of Defense can talk to a Cerner back end. So, you get into this situation where
you can have all kinds of different applications that are adhering to that same
service interface and you have got applications that are adhering to a certain
interface on the front end and you have got providers of service interfaces on
the back end that adhere to that same interface.

You know, these slides are actually part of my slide set but I was already
over time. So, I quit talking. But the idea — and this is a revolution — this
is what has the potential to truly commoditize and revolutionize the way that
we build these software modules because what it means on the application side
is it means that I can have a one person or a five person company that can
build an exquisitely smart, good thing to do who knows what, you know, TPN, you
know, to concoct TPN solutions or to schedule my patients or something and I
can do that because I don’t have to worry about the back end. I have a set of
services that say that once I have got the data, I know how to persist the data
and so I can create these pluggable modules and I have created a marketplace
because people are adhering to these interfaces and I can plug and play with
anybody’s application.

On the back end, you know, it is probably — again, on the back end it is
probably going to be a select set of people who basically win that back on the
back end because it is going to be purely performance, cost performance, you
know, adherence to the interface and become more and more a structured set of
functionality as defined by the functional specifications that people — but it
truly then has in this, none of these interfaces work if the terminology and
things aren’t standardized, but to do this, you have got to do more than that.
You have to standardize these API to services and make these services available
but now it is an entirely different thing because I mean there are so many
situations now where you go through installing a system and because the
applications are so tied to the back end, you can never change, except in lock
step with what one vendor is going. So, your ability to share or the ability to
have innovation in a small area is really tied strongly to that sort of — of
that architecture.

This, whether it works or not, I don’t know, but I really think it will and
I think if we get to that — No. 1, if we get to the standards and No. 2, we
get an understanding in the marketplace of the value and that these things
really get implemented, I think it will dramatically change the price, the cost
of these kind of systems and make it so much more possible to share good
innovation in small areas, much more — much easier than it is today.

DR. GEERLOFS: I really want to reinforce this message. One of my favorite
books in the last couple of years is The Innovator’s Dilemma, you know,
by Clayton Christianson, who started the notion of disruptive technology, but
what he talks about is the normal life cycle of a product. I keep mentioning
the term “commodity.” In the ambulatory world, not in the hospital
world, but I think in the ambulatory world, as I have mentioned, I think we are
moving toward the commoditization. The nature of commoditization is that
companies initially in order to innovate, innovate through functionality. You
know, they have got great products, but as they commoditize, the functionality
isn’t the innovation. The innovation now is efficiency of updating the product,
maintaining the product and so there is a very natural tendency towards
compartmentalizing or making products more object oriented, if you will, such
that third parties can — in effect, innovative small companies can help
innovate the functionality of the product.

So, what we are seeing in our own company is that the very next version of
Touch Work, Version 11, coming out next year, has moved to an object oriented
paradigm and our initial motivation to do it is not what I have just said. Our
initial motivation is how can we — the pace of innovation is happening so
rapidly, how can we keep up and we can’t keep up with the monolithic products.
I mean, it will cost us a couple million dollars to test our products every
time we do a forward aggression test, when we bring out a new version.

So, by compartmentalizing the product into objects if you will or plug-ins,
we can now build better plug-ins and give them to our customers off cycle. The
testing is much less, et cetera. But what we are starting to talk about is
exactly the same notion, which is, hey, let’s just publish the API and create a
market out there for certain of the types of plug-ins so that third party
companies can build them and, boom, that does create a whole new market. So, I
think you have heard from two — I think it is fascinating actually that, you
know, two of us are thinking very much along the same lines and I think this is
something that is a —

MR. HUNGATE: That is encouraging that two of you are thinking —

MS. GREENBERG: Can you tell what those initials are?

MR. HUNGATE: What do the initials API stand for?

PARTICIPANT: Application Programming Interface.

DR. GEERLOFS: Think of it as the sort of the back end of the product is
where you store all the data and the front end of the product may be where you
have the user interface and some of the roles around how that works and an API
— so that the front end could treat the back end as a black box. All it knows
is a very sort of narrow set of commands that allow us to talk to what, in
effect, is a very complex back end, but it completely simplifies the view of it
to that front end.

DR. HUFF: You know, a good analogy that Clem has often used is, you know,
just plugs between stereo equipment and instruments. It defines how you can
connect, you know, any instrument to any amplifier and it just — you know, it
is a software configuration rather than a hardware configuration, but it says
how I can talk to another piece of software in a consistent, well understood
way. That is all an API is.

MR. HUNGATE: In the context of our discussion on quality and the decision
to buy and EHR, do you have to know what this interface is going to be before
you decide what an EHR is for you?

DR. HUFF: Well, these things don’t exist yet. Excuse me. They do exist.
They are different for every — if you are doing actually the vendor’s
applications now, these are entirely different shapes from every vendor and for
every application. So, there is nothing that plugs and plays with anything
else.

MS. MC CALL: So, the breakthrough here is to say, you know, a lot of this
coming together is handled through the interface layer, the API, and that that
should be standardized. I want to make sure that I understand it because I
think it is an important concept. Now, as I get standardized, is that also
where we were talking about vocabularies and I was trying to get a sense of how
structured the world needed to be, but also how nimble it could be.

So, are a lot of those translations happening in the interface in your
slide?

DR. HUFF: You could do the terminology translations in the middle piece. I
mean, one of the reasons that open source software hasn’t taken off in medicine
is because of the terminology in the data modeling.

MS. MC CALL: That is right.

DR. HUFF: Because, you know, they have all these great widgets where open
source as far as the software would work just fine, but if the drug names
aren’t actually the same or if there isn’t some common understanding or common
mapping, you know, if the guy up here on the top is talking French and the back
end is talking — in spite of the fact that they can hear each other across the
line, you know, they are not going to be able to perform the service you are
asking for.

MS. MC CALL: And I have heard — this is critical and the reason it is is
that we heard from Peter earlier that adoption is key, that there is a lot of
low hanging fruit, if you can just get adoption up. We also heard that one of
the things to watch out for if we are looking for quality — we heard yesterday
about numerator, denominator, data quality, integrity, those types of issues.
So, if we get a tower of babel going, then we pay a heavy price down the road.
So, it begs the issue of if you need perfect data and perfect data is a barrier
to adoption, then how do we thread that. So, it sounds like that this type of
thing, this type of API that does a lot of that translation is a key component.
Is that a fair assumption?

DR. GEERLOFS: I think it certainly could be and remember also that all data
is not created equal. I mean, this whole discussion of data and standards is
obviously a huge discussion, but I think it often gets oversimplified in this
notion that sort of all data is equal. The truth is that probably about 20
percent or maybe 10 percent of the data generated within practices is the stuff
that really needs to be shared. So, that is one issue.

Also, I think that we are probably in many cases not going to end up with
any one standard for any type of data. My guess is there will for some time be
more than one standard. So, this translation engine — in other words having a
public domain just as an idea, engine to translate among the most common sort
of general vocabularies around problems, you know, whether it is SNOMED or
MedCin or ICD-9 or what have you. That is the kind of thing that could begin to
matter.

But I really believe that this whole push towards standardization of the
API is going to be market driven. I think about the data backs and all of these
issues. Of all the experiences in the past, I really think what is going to
happen is kind of what has happened, for example, with Photo Shop. You know,
Photo Shop, in effect, published its API and a lot of its business because of
the open API are third party companies that create plug-ins, specific plug-ins.
So, I think that a very important discussion is going to be the balance between
the market forces that can really drive us towards this and the gentle
influence, you know, that can come from government, as opposed to the other
approach, which is, you know, attempts to just sort of mandate it independent
of market.

I think the reason it has taken so long is partly because that has been the
approach. The market is starting to heat up now. So, I think you are going to
see more and more opportunity for companies to be out there in leadership and
start publishing some standards and some are going to take off and some aren’t
and before long, you know, who knows, we may be in a much better place.

MR. HUNGATE: All right. I want to give Dr. Rucker one minute here and I
think we are done as a panel. Stan has got to go catch a plane.

MS. GREENBERG: I have a question for Stan, if I could.

MR. HUNGATE: Marjorie has a question for Stan.

MS. GREENBERG: To show my complete stupidity or at least elucidate
something for me and that yesterday when we were in a different meeting — we
have been meeting continuously for about four days here — I asked you, Stan,
about the vocabulary that you used in the Intermountain system and the
relationship with SNOMED, et cetera, and you said that you had sort of a local
vocabulary, I guess, that you had built, but that it all mapped to SNOMED.
Something like that, right?

DR. HUFF: I said 80 to 90 percent because I am in a hundred percent
agreement with — there is no terminology for orders or for orderable items or
for order sets and there are all of these things that you need to make a
working system that don’t exist in LOINC or SNOMED or anything, that are just
silly things like order statuses and process steps and —

MS. GREENBERG: Go to X12. They probably have all those.

DR. HUFF: They are in a different universe.

MS. GREENBERG: That is in a different world, yes.

But my question to you was is the terminology base or vocabulary base that
you use, that you have developed at Intermountain, is it kind of an equivalent
of something like MedCin?

DR. HUFF: Yes, in some ways, but — well, MedCin is — some of the
terminologies we use in the health system are really almost identical to MedCin
kind of terminology because what it is is a — MedCin, you know, is truly
organized for ease of use by clinicians and for using what they enter as — to
inference and be able to get quickly to an order set or, you know, to what you
are doing. We have terminologies like that and that is, again, one of the —
some of the things that are in our terminology that are not in SNOMED or not in
LOINC or other standard terminologies..

MS. GREENBERG: Because of the challenges — and we have heard this and we
are hearing it across the pond, et cetera, of just putting SNOMED as sort of
the entry tool — I am not even sure that it is intended to be that, but there
are maybe a few — everyone doesn’t have to — obviously, you started this a
long time ago and I would think you would need to add terms locally, et cetera,
but everyone doesn’t have to start from scratch. I mean, there are some kind of
interface or some entry level types of terminologies out there that could give
people a head start. They wouldn’t have to try building it from scratch.

DR. HUFF: And market forces are doing that, again, already, much more so in
the outpatient environment than the inpatient environment. The outpatient
environment I think, you know, the combination of people who are using MedCin
within products, for instance, you know, with Logishin(?), Logishin has a
consistent terminology across all of its implementations as well.

I don’t know if anybody has sat down and tried to match up Logishin’s
terminology to MedCin terminology. There are only so many terminologists in the
world. So, actually people are usually pretty familiar with what is going on in
the other — but that is happening much more quickly in the outpatient
environment and consolidation of products in terminology than it is happening
in the inpatient environment.

You just don’t see commonality yet in the inpatient environment between
these orderable items and things like that. People aren’t sharing at that level
yet in the inpatient environment.

DR. GEERLOFS: Just to comment, in the ambulatory environment — I have not
studied the inpatient, but in the ambulatory, we just hired a third party, a
company called Apilon(?) to do a review for us because we wanted to create what
we call an order concept dictionary. So, we would with all of our templates and
order sets, et cetera, it would be based on a standard dictionary and we are
looking for who out there could possibly do it.

Interestingly, we ended up — they ended up coming back and saying that
MedCin is the one out there and they actually do — we have now done the
analysis — they do about 98 percent of everything we need around order terms.
So, it kind of surprised us because we haven’t been using that aspect of it.
So, DOD must know something, I guess.

MR. HUNGATE: Don, any final comments?

DR. RUCKER: I would just throw out when you do these inpatient order
systems it gets very complicated very quickly on the interfaces because you
have to do all the things like security and log on. You have to have modules
for drug checking, you know, drug dose checking, drug allergy checking, drug
duplicate checking, extraordinarily tricky. You know, is that next sliding
scale dose of insulin a duplicate? You know, what part of the opiate regime of,
you know, the patient controlled analgesia and the long acting and the short
acting opiates, are they are duplicate? You know, what is the dose checking?

I think that is why these things in the real world get real complicated and
if anybody sort of wants a metric of complexity, I would throw out sort of two
sort of touch points. One from a very simple point of view is to look at what
Jenks(?) and Walters Clewers(?) are trying to do with just simple evidence
based medicine and putting simple sort of evidence-based medicine guidelines in
and talk with those folks about, you know, what they are trying to do with
standardized vocabulary.

The other thing on the complicated side is, you know, they talk about
thought experiments, you know, the Duncan(?) experiment, pick up any, you know,
ACOG, ECOG, I don’t know all the oncology group acronyms, pick up any
hemo-therapy protocol, you know, a hundred plus pages, sit there and try to
just stub it out in English or, you know, in visual bases, just take a random
page and try to represent that protocol, just pick a random page, you know, as
a random number generator and you have the cycles and, well, you know, the cell
count was down, but now it is up and their body weight was down and their total
body weight was up.

You know, the parameters passed on an API, who incorporate all those
variables would be, you know, like a thousand — you know, a thousand items.
So, you have to — you know, everybody has their own tricks on how to simplify
the world, but I would just caution the committee that that is a little bit of
a very complicated road that seems simpler on the front end than when you are
deep in the middle of it.

MR. HUNGATE: Okay. Very good.

I think we need to take a ten minute break and thank the panel and we will
come back and do a little workgroup discussion and then we will finish for the
day.

DR. GEERLOFS: Thank you all. It was a pleasure.

MS. MC CALL: Thank you, Peter, so much.

[Brief recess.]

Agenda Item: Workgroup Discussion/Strategic Planning
— Next Steps

MR. HUNGATE: We have about 35 minutes to use as productively as we can. The
first thing we need to do is agree that it is not going to take me 15 minutes
to do any closing remarks. So, we will use the rest of the time for talking
about what are our next steps.

I think that you have some other thoughts here, Carol?

MS. MC CALL: Before we get to next steps, I think it might be helpful if we
just go around quickly and just each person, just a couple of observations and
then kind of go into next steps. There is going to be a lot to digest, but just
a couple of what were the key things that struck people out of what we have
heard today.

MR. HUNGATE: Fine. We will start at the left and go around.

Michael.

DR. FITZMAURICE: One of the things I learned –and I apologize for being
gone for a period in the middle of the day. I had to go to another conference
and then back again — is that templates can be useful in producing quality
measures, maybe HEATIS(?) measures, other measures, ahead of the need to report
them, rather than the expense of going back to chart review. But a lot of
things are fraught with terminology and vocabulary and from the last set of
speakers, I learned that decision support isn’t as easy as it is when you are
just talking from a slide.

I remember maybe six to eight years ago, Jim Simeno(?) and Stan Huff saying
that they tried to exchange some Arden(?) syntax decision support modules
between their two respective hospitals and they ran into trouble with the
vocabulary, that they spent more time than anything making sure that the terms
were the same and that their physicians agreed with what those rules were,
based upon the terms that they had substituted.

It just was not easy to move from one system to another and a good part of
that was the vocabulary.

MR. HUNGATE: Bill.

DR. SCANLON: Well, first, I think I felt more optimistic about the time
horizons for us for moving forward today and I guess I am hoping that we didn’t
get with all due respect to the two panels, we didn’t get the wrong impression
from them because they could be sort of — this is their world. They are under
the lamppost and they are seeing sort of all this enthusiasm, but I am hoping
it is true. I think some of the statistics that were cited suggest that it is.
I mean, I think that is a very positive thing.

This afternoon left me a little more concerned because I think of us as
external users or demanders. I mean, we are going to be saying to the people
that have these systems give us this, give us that and then tomorrow we are
going to change our mind and say give us something new. This goes back to what
Justine has raised in the past, which is this issue of flexibility or being
dynamic. I am not sure about how flexible and dynamic it is. That is kind of
the reengineering, the rejiggering of your system when somebody comes up with a
new thing that they want, how straightforward that is going to be.

Weight, blood pressure, hemoglobin A1C, these things are all going to pop
out with no problem, but when we get down to some other lab values or something
or maybe lab values is not a good case, but something else that comes out of a
physical that is maybe sort of more difficult. That lessened my enthusiasm in
this afternoon.

In that regard, I guess, there is a question of what can be done in terms
of trying to encourage some level of flexibility being built into the systems.
How do you define a level of flexibility? That is a more challenging task than
defining a specific function, saying be able to do X. Instead what we are
saying is be able to do the gamut and we can’t tell you what the gamut is
today.

MR. HUNGATE: Carol.

MS. MC CALL: I guess an echo on the optimism and I guess I am going to take
what you said, Michael, about terminology and decision support both being hard.
I think there is a third area. There are three main areas that I see that
involve massive translation exercises. One is on vocabulary and learning either
how to translate very quickly from one language to another or having to have
everybody speak English, which is kind of what we are struggling with.

Decision support is also a translation where getting it back is a process
that is hard and how do you actually share. Then there is a third area that I
don’t see anybody talking about and I think it is related to this broad domain
of quality, which the context is the interface that Stan talks about is around
the raw data and the indicators and, yet, to go from an indicator to a measure
is also hard. You know, how often do I want to see a thing in a certain period
of time and all of that and that is research before it is decision support.

So, the diagram show everything going into this warehouse. So, that is the
end game and yet there is a whole bunch of processes around that in science and
art. It is first art and then it is science and I think that there is a need
for an API at that point. And it could be maybe an open environment of
methodology and science and analytics, but — and I think one of the speakers
today and I think it was David Lansky said, you know, we really need to look at
kind of an analytic level as well. I think that there are some contributions
that we can make, but there is an API there about how to transfer discovery and
knowledge and metrics and findings that is a technical issue and it is also a
process issue. I don’t see anybody really talking about that yet.

MR. HUNGATE: My morning take away was that the changes of cultures and the
resistance to the changes are more serious issues than the specific content of
the EHR, which I think is important and very relevant to our content. From the
afternoon, I had an interesting short dialogue with Don Rucker just before he
left and he said I am not sure all the emphasis on this vocabulary is
appropriate and he expressed that as saying that it is hard to use those
vocabularies, that they don’t necessarily fit with the clinical work flow. So,
it is not the clinicians that are looking for these vocabularies. It is people
from someplace else. That is an important observation about what we have, I
think, universally kind of accepted as a critical variable. But it is not
variable, it is not critical from the clinician viewpoint. That is an important
limit in what we are dealing with.

So, those are two things that I have picked up that are important, I think,
to our agenda.

Deb.

MS. JACKSON: A sense of time, warp speed, how much things have changed in
the last three to five years, I heard someone say. Well, that means the next
two to three years will make such pivotal difference. Hearing things about the
tipping point with — the analogy I am thinking more about is this window, that
we just seem to be so close to, you know, making a difference now when so much
is in the design stage.

The participants, the speakers all sounded enthusiastic and ready to jump
into it. At the same time, I am concerned about falling over the rocks as we
are looking at the vision ahead. What I learned that I wasn’t really familiar
with was the difference in the ambulatory and the inpatient care. I am very
taken by this one slide by Kibbe showing all this volume on the ambulatory and
the outpatient where the money is at the other end. I would like to make sure
that we are this concerned about developing the architecture that will help
develop this horseless carriage in the EHR instead of something that is
transformational and in really designing a structure that will make the kind of
differences in the dynamics within the health care we would like to see.

DR. CARR: I think what struck me the most today was the complete package
that delivers quality and it begins with — I am turning into Bob, Bob is
turning into me, very scary, but it does begin with some sense and roadmap of
what the clinicians believe to be quality. This is what we want. The next thing
is the electronic data capture and I think the part that I understood better
than I have before is the integration of the patient medical record and another
feature, of course, is the kind of reminders and the decision support.

So, by having the patient medical record so integrated into the flow of
things, clearly rounded out a fragmented picture and having the targeted
reminders ensured that what could be made better in the episode of care would
happen.

The third element is data manipulation and aggregation, trend evaluation,
data display and drill down. I think that without that, we have what we kind of
have today is just millions of data elements floating around and a scramble to
send them where they need to go when someone asks for them. But the context of
really improving care was so palpable with the VA system.

Then finally the — well, two more things. One is the utilization that you
trend it, but then you give it to someone who is accountable and there are
consequences. There are expectations going back to the vision. Their vision
isn’t to be at the average of CMS range. Their vision is to be better than the
rest of the country. There are consequences and it sounds like they will have
their own internal pay for performance.

Then finally, you know, the interoperability across the entire VA system
was very compelling when you think about what it meant with Katrina. So, you
know, I am kind of stymied with how we get there, but I can see where there is.

DR. HOLMES: I thought that the two panels for me illustrated the
distinction between where this group goes in terms of taking on tasks, the
morning session being very kind of general and policy oriented, as opposed to
the afternoon group being very detailed.

Another distinction is that perhaps the morning group being more focused on
population or the promise of population health; whereas the afternoon group
being more focused on individual health outcomes. I continue to be very
puzzled, i.e., confused about whether there is a connection between the two or
how one would attempt to traverse the areas.

MS. GREENBERG: Thanks for giving us this opportunity. I always find it very
interesting. Sometimes I wonder if I was at the same hearing or meeting, but I
actually don’t today. I agree with everything that everybody has said. I mean,
they are all things that I was thinking. The first thing I had written down
here was optimism. So, before anyone said anything.

Certainly, I just think in a year, maybe it is the people we are hearing
from, but I don’t think it is just that. I think there is momentum and I think
that one — you know, it is always risky to make a cause and effect statement,
but the fact that the Department and the Federal Government has really kind of
started to organize itself around this and try to push it even though they
haven’t, you know, put a lot of money into it, but I think, you know, may have
— at least it doesn’t seem to have pushed people in the opposite direction.
You know, I don’t know how much that impact has been, but it is interesting to
speculate on because we won’t know.

People have been calling for leadership by the Department in this area for
a number of years, going back to I remember when Secretary Sullivan was here.
So, you know, it is time.

I like, I think, Bill and others I think mentioned it, too, felt less
optimistic about not just flexibility but interoperability. Still, I find it
kind of scary that we may not in the VA system but in our overall health care
system or non-system, and I think that is what Don Detmer made a point about
that we don’t actually have a health care system in the U.S., that we could
have a lot of, you know, really good, hopefully much better care going on in
individual silos, but that these things won’t necessarily talk to each other.
They will at least within — in those silos. I mean, we have had the system
where the lab system didn’t talk to the radiology system in the same hospital.
So, that is at least I think that is really being addressed, but whether these
will really be interoperable, even to address the issues of patient care, let
alone, of course, to serve the needs of broader community care and population
health.

So, I didn’t hear a lot that encouraged me about that, but it just might
have been that they didn’t really focus on that. To me, the case for electronic
health records in the — for all theses things that like the IOM has pointed
out is so — you know, I think it was made more clearly during this week, maybe
because Stan spoke twice or whatever, than I have ever heard it made because it
wasn’t just hypothesizing or assumptions. I mean, there was a lot of evidence,
I felt, of just — I don’t know why the patients are putting up with all — you
know, if people really knew how many things you could improve, I don’t know why
they would put up with the current system because, you know, the elimination —
well, not the elimination but the reduction of errors of timing, of, you know,
just everything, it just seemed to be very clearly, you know, displayed.

I really hope that this is getting into the literature, not just into the
scientific literature, but into the consumer literature, et cetera. I still
don’t think, you know, you see much of it at all. You hear a lot about the
hospital where they threw the electronic system out because it was driving them
crazy. But I mean these are really successes every minute of the day that are
making our care safer and people, hopefully, being healthier, reducing errors,
you know, getting medications to people quicker, you know, all of this stuff
and I don’t think that is really well documented.

The fact that it should do that is getting out there, but the actual
examples — and I think if we can think of any way to try to encourage that,
getting that more into the literature, more into the consumer literature, more
into the — you know, other literature, not just to influence physicians, but
really to influence consumers.

I mean, if consumers know that one car would cut down their mortality rate
in half or something, I mean, wouldn’t they be buying that car? Probably.

But anyway having said all that because it makes the case so clearly, I
come to the conclusion that — with David Lansky, that the real role, I think,
of the National Committee is to be doing what Dr. Brayler(?) asked the
committee to do and that was to address the capacity of NHIN and EHRs in the
measurement of population health and its role in improving population health. I
am reading from Justine’s document.

To me, it is — of course, that is where I come from. I realize that, a
population-based agency and function and discipline and everything else, but I
really — I am not sure that we can make as big a contribution in this sort of,
you know, one person at a time health care environment because it seems to me
that it is happening and, again, that is where to the need to really get this
out there and document it. I think there are things we can do, but I think we
have got to keep — nobody else is looking at the population issues really. I
don’t think anyone else is. So, that is where I came out.

Oh, and as for vocabulary and terminology, what it has to be is sort of
invisible to the clinicians but it is all about vocabulary and terminology
because that is the only thing that will make things interoperable.

MR. HUNGATE: I don’t disagree but it is not perceived as a benefit at the
level where adoption is critical.

Go ahead, Susan. You get an option, too.

MS. KANAAN: Well, I would say two things. I always like the big picture
talks. So, I was very interested in the contextual remarks that people made in
that first panel, the basic system issues and thinking about our document, I
think that we need to begin there, even if we end up saying we are not going to
address those things. I think that we have to understand that those are the
givens.

The other thing that I found very interesting and that for me is one of
those kind of thought questions, like one of the speakers mentioned, is how can
this value and principal of patient centricity really be implemented on a
practical level. It seems like a very, very interesting challenge.

MR. HUNGATE: Eduardo.

DR. ORTIZ: I just jotted down a couple of things. The first thing that I
got out of this was that it is really, really important if we are going to move
forward with the quality agenda is that we have to be able to share data with
each other. We don’t do a good job of that and we have to find a way to do
that.

The second thing was that we need to do a better job with determining what
constitutes good quality beyond the traditional measures that we are using. So
not that they weren’t good measures, as David was saying, that those are
important measures, but if you look at almost everybody, they are all doing the
exact same thing. Beta blockers after MI, hemoglobin A1C and it is like we are
getting in this thing where everybody is doing the exact same 10 or 15 or 20 or
30 measures, which are important, but we have to get beyond that. I think it is
really important.

So, we need to figure out what really constitutes good quality. We need to
figure out how do we collect it, how do we do it using these electronic tools
so that we can be as efficient as possible.

The third thing was that we need to make sure that incentives are aligned
to improve quality of care because that is a theme that keeps coming up over
and over and as we saw when Stan was talking about his things, that a lot of
times doing the right thing will actually hurt your bottom line because
readmitting those patients actually generates a lot more revenue to the
hospital than not readmitting them. Keeping them in the hospital longer because
you are not managing them optimally for community acquired pneumonia actually
generates more revenue.

Until incentives are aligned, it is going to be very difficult to get
people to do the right thing.

The fourth thing that I got was that we really need to be able to share
medical knowledge and decision support tools. That is such an important thing.
You know, with the electronic health records you have got the benefit of having
this data available 24 hours a day, seven days a week, anytime, anywhere, but
you really get a lot of benefit from it when you can start building in these
decision support tools that help you make better decisions, help you manage
patients better and it is so complicated, it takes so much work. We have to
learn to share it, but it is such a daunting challenge. It is not going to be
easy, but we have to figure out a way to do that.

MR. HUNGATE: Gail.

DR. JANES: I would like to cherry pick from what everybody else has already
said. Just a few things and they really do reiterate some of the things that
have already been said and both of them relate back to standards, maybe because
we have all worked so long and so hard around issues of standard vocabularies
and standard terminologies, whether we think about HIPAA or some of the things
going on within the CHI initiative. It goes on and on.

I tend to think positive. You know, well, we have made a lot of progress.
We have worked hard on this, but when I hear talks like the ones that we heard
today — and admittedly I only heard the afternoon — it kind of brings me up
short. Two things struck me and both of them relate back to a more sobering
view of standards and perhaps not so much belittling at any level how much we
have gained from the work, but realizing as you sort of turn and you face
forward and you realize how much work we still have to go to.

As I said, two issues. One was I found the discussion at the end very
interesting, some of the discussion that was going back between David and Stan
when we were talking about API and this issue of the back end and the front end
and the fact that even though we have these standard terminologies that, in
fact, these systems cannot talk to one another. That sort of brings us to some
of the things Marjorie was talking about, you know, the scenario that I think a
lot of people have cautioned us about and that is that despite all the movement
around EHRs, that we are still at risk of building a series of silos, which are
not interoperable, which cannot talk to each other, despite all the progress
that we have made.

So, I thought the discussion about API and like a couple of people, I kind
of struggled to get a sense of exactly what that was, but it was clear to me
that this was a good thing. I thought that was very interesting and I also
thought it was interesting that it got raised eyebrows from all of our
speakers, but I definitely got the impression that this was something that was
still being — that was still very much sort of on the cuff, on the edge,
something that people were talking about that hadn’t been sort of probed that
much.

So, that certainly raises questions about whether this is something we
might want to think more about. So, the only other thing that occurred to me in
listening to the discussions again relates back to standards and to some of the
things that Eduardo was saying was I was very interested in sort of again as a
contrast to the data that we saw, which I think we have all seen before about
how much has been accomplished around the improvement of care, using quality
measures and relying heavily on some of the modes of standardization that have
been pursued.

Also, the discussion — and I can’t remember who made the comment about the
limitations in some of the vocabularies and the terminologies in the fact that
at this point they don’t really allow us to describe transactions more complex
— to describe some of the more complex activities of medical care particularly
well.

Again, as Eduardo was saying, I mean, at some point if you think about the
quality measures that we have now, HEATIS measures and the like, a lot of them
are switches. They are dichotomous measures. You know, was something — you
describe something in a standardized way and you ask was it done or was it not,
yes, no. At some point we are going to want to move beyond that. I was thinking
about what David was saying about actually being able to sort of delve into the
area of complex protocols and begin to sort of track that.

The message that at least I thought I was hearing was was that the
terminologies and the vocabularies that we have now are not well suited to, in
fact, move us perhaps into that next realm of quality assessment. Again, I
thought that was very interesting and perhaps a bit sobering.

MR. HUNGATE: Okay. We don’t have much time. I think that we are not going
to get very far in a discussion of next steps here in seven minutes. So, I
think we need general agreement to do two things. First is individual work, to
go back and think about what would I like to know next in the context of this
arena that we are talking about because I think that is the first place to
start in terms of each of our heads understanding of what we have heard so far
and what we feel like we need to know next.

Then we need to put two or three down in a list and then let’s arrange a
way to exchange that, which is probably through e-mail, and then use that base
of information for a conference call, not trying to do any judgment at that
level, but just gathering ideas. Does that make sense? Is that an agreeable
approach?

MS. MC CALL: Yes. I would like to add one thing to — some homework. One
thing I have found very valuable is to get not only transcripts and I would
also like to get a complete packet of all the materials electronically, which
would be very helpful. It allows me to reconstruct and also Susan —

MR. HUNGATE: Transcripts are very valuable.

MS. MC CALL: Susan has also done an excellent job in the past of
synthesizing and trying to sum up, losing some of the transcript grain, but
still trying to keep the common ideas. I have found that really valuable.

So, if those could be materials that could come into kind of the homework,
I would find that — both of those really good. Then I would like for us to put
down what we think would be, you know, maybe more refined thoughts but also
what we think possible next actions could be and then come back together in a
group and literally plan what we want to do next, share it and then see how we
want to proceed.

MR. HUNGATE: Marjorie.

MS. GREENBERG: Well, you know, we have our new policy that we only do
minutes or summaries of the meeting when the committee wants it. I assume that
you do want that and, of course, Susan often does our minutes for us anyway.

MR. HUNGATE: We depend heavily on Susan.

MS. GREENBERG: So, we will have that. We will do that.

The other thing is I get back to I think it was Bill, who said yesterday
that maybe we know more than — we have got more information than we thought we
did. I just think everyone should really — and maybe this is what you were
saying, too — but should really think about are there really other people we
need to hear from? Are there, you know, site visits we need to make? Are there
things we need to read? Or is the next step maybe pulling this altogether not
with a bow, but in a way that we can then really take out to people in some
form and possibly, you know, the regional hearing approach or — you know, I am
saying this knowing what my budget is, but, nonetheless, but, you know, I —
but if there are holes in the information, then I think we need to identify
those sooner rather later, schedule a hearing, but just think about that. I
mean, I would appreciate even from our planning point if we could really be
thinking about —

DR. CARR: Well, I would like to hear from Michael, from AHRQ, because I
know at the meeting two weeks ago, I know Carolyn is speaking before the AHIC
group and I think there is — you know, what we are touching on sort of is an
interface between AHRQ and Standards and Security. It is sort of an area that
touches both of them. I would want to have an understanding of what each is
doing and, you know, is there truly a space that isn’t being addressed or if
there is, is there something that we could partner with AHRQ or whatever.

DR. FITZMAURICE: I would like to offer maybe five thoughts because you
heard my thoughts first about listening to the testimony, but listening to you,
I got better thoughts than I had before. So, I am kind of echoing back your
thoughts.

The first thing if the Secretary were to come in and say, all right, what
did you learn from today? What do you have to tell me? I would say, well,
first, that there needs to be some focused research on what are some good
quality measures, how do we know that they are good? Is it a consensus? Do we
have studies that consumers want these measures?

The second thought is how well do these measures that we consider good
scale up to population health measures? The third thought, what is it that the
consumers want and do higher quality measures give it to them? You know, if I
were to go into the hospital to see a doctor, what I want to do is get up on my
feet faster. I want to get back to work sooner. I want to climb the stairs
better.

Do these quality measures, getting a foot exam if you are diabetic, do they
help me do that? I think that it probably does. But does it give the consumer
what the consumer wants out of health care? That ignores the prevention. I
don’t want to be sick in the first place, but we are talking about quality
health care being delivered to sick people.

Fourth, I guess the one recommendation I would give back to the Secretary
is that the National Health Information Networks and the standard harmonization
contracts and the CCHIP contracts should emphasize terminologies and
vocabularies for interoperability solutions. The question I would say should
there be a lot of mapping between all the terminologies that are out there or
should there be some focus on single choices for vocabularies for specific
functions?

I don’t know the answer to that, but you can spend an awful lot of time
pursuing both ends and what works in a pilot. So, let’s get some pilots to test
these thoughts and get some recommendations back from these contracts.

The final thought is what incentives could be developed and put into place
that would improve systems that produce better quality of care measures and
better patient outcomes. It is the patient outcomes that we want. We think the
quality of care measures are the way to get there. The greater percentage of
people who get quality of care, the better we think patient outcomes are.

There are studies that show for a lot of the quality measures that is true.
Let’s focus on them. Let’s find out what it is we know and what it is we don’t
know. So, it is research. It is giving direction to the existing contracts for
interoperable solutions and it is finding ways to make it happen through
incentives.

MR. HUNGATE: Okay. Thank you.

I have got a plane that is pushing me a little bit at this point. I think
we need a conference call the second week in December. I don’t think we want to
do the polling here. We want Cynthia to do that through the Internet of the
week, the 5th through the 9th of December.

This is a two hour conference call, I would guess. I would like to fuel
that with the three wishes, which will involve maybe next steps, but it will
also just involve content that you feel needs to be pursued as the starting
point for that.

Anything that you can add to that, fine and getting the information out
from this meeting to everyone with a brief summary to the extent that you can
get it done in two weeks. Not a chance?

MS. KANAAN: I am afraid that won’t happen. It will be a month. We won’t
even have the transcript in two weeks and I have another —

MR. HUNGATE: Let’s get the slides out and that will be the content, I
think, for that meeting. Now, I think as we individually think about that,
there will also be suggestions that occur to you for how we ought to spend the
time in that two hours. Feel free to share them in the context of the e-mail
communication.

I think that —

MS. MC CALL: Actually I would strongly encourage sharing them in advance so
that what we have is an opportunity to digest what other people have thought
prior to coming on to a call so that we can talk as opposed to —

MR. HUNGATE: Let’s talk the question of mechanics. I am under the belief
that Cynthia Sidney maintains the best mailing list, most reliable mailing list
of the content of our group. So, I would suggest that we work through her in
the communication with each other. We could each have our own mailing list and
broadcast to everyone, but I don’t think we should do that. I think we should
put our information to Cynthia and have her send it out to the group.

MS. MC CALL: There is a practical reality that once she sets the pace, all
you have to do is reply to all.

MR. HUNGATE: So, maybe what we want you to do is send an invitation to all
of us to send this information out and then we have got the list and we will
always reply to all with our list of three and whatever else we want to
communicate. Is that okay? Everybody okay with that?

MS. JACKS0N: So that this doesn’t come through kind of piecemeal, are we
looking at trying to get the responses in within a week or so, all to Cynthia,
and then she will do a composite and then send what —

MR. HUNGATE: No.

MS. MC CALL: There are three things that we need to do. One is we need to
poll for a date. And that is going to be done by Cynthia. Cynthia is also going
to send out electronic material from this meeting. That is No. 2. No. 3, as we
each individually are done with whatever it is that we would like to share,
things around — and I love what you did, Michael, in terms of if I had to make
a set of recommendations today, what would they be. That is one way to look at
it.

Another is to say what would we say our findings to date were. That is
another way. There may be other ways. Share what you have through the entire
group when you have it because that actually is a greater service to folks. It
gives them more time to digest it and we will have a better quality discussion.

MR. HUNGATE: Make sense to everyone?

MS. KANAAN: Would you all like me to send you Michael’s five —

DR. FITZMAURICE: I will send it.

MS. KANAAN: You will do it. That is even better.

MR. HUNGATE: All right. We are done.

[Whereupon, at 4:35 p.m., the meeting was concluded.]