[This Transcript is Unedited]

DEPARTMENT OF HEALTH AND HUMAN SERVICES

NATIONAL COMMITTEE ON VITAL AND HEALTH STATISTICS

SUBCOMMITTEE ON PRIVACY, CONFIDENTIALITY, AND SECURITY

THE COMMUNITY AS A LEARNING SYSTEM FOR HEALTH:

USING LOCAL DATA TO IMPROVE COMMUNITY HEALTH

PART II

May 12, 2011

National Center for Health Statistics
3311 Toledo Road
Hyattsville, Maryland

Proceedings by:
CASET Associates, Ltd.
Fairfax, Virginia 22030

Table of Contents

P R O C E E D I N G S (9:00 a.m.)

Agenda Item: Introductions and Opening Remarks

DR. FRANCIS: I’m going to get us started, so if people can take their seats
and be comfortable, and get happily on the line. The first thing that we need
to do is to say that this is a workshop sponsored by the National Committee on
Vital and Health Statistics. This part of the workshop is lead-sponsored by the
Subcommittee on Privacy, Confidentiality and Security of NCVHS. There was a
prior workshop in February where the Population Subcommittee of NCVHS took the
lead in organizing.

The goal of these two workshops, and potentially even more, is to think
through the questions of how to appropriately protect community trust, in light
of the extraordinarily wonderful new ways that various forms of health data are
being used, and not only health data, but also community data, everything from
the weather to the grocery store. So what we did in February was hear from a
number of groups about fantastic ways in which data are being used to empower
communities.

And what we are planning to do today is to begin to brainstorm about best
practices for making sure that people trust the ways in which data are being
used, and do so legitimately, so that there aren’t backlashes basically.

So with that quick introduction, the way we’re going to start this out is
we’re going to go around and ask everybody who’s here to identify themselves,
and say if you’re a member of the committee, and we’ll take it from there.

I will start. I’m Leslie Francis. I Co-Chair the Privacy, Confidentiality
and Security Subcommittee of NCVHS and I don’t have any conflicts.

MS. MILAM: Sallie Milam with the West Virginia Healthcare Authority,
Co-Chair of The Population Health Committee. And I, along with Dr. Larry Green,
are really pleased that Populations could co-sponsor this workshop today, and
felt like we learned a lot from everyone in February, and are very excited to
hear the privacy end of the issue today.

MS. HORLICK: Good morning. I’m Gail Horlick. I’m from CDC in Atlanta and I
am Staff to the Subcommittee on Privacy, Confidentiality and Security.

MS. GONZALEZ: Hello. I’m Natalie Gonzalez and I’m from CDC in Atlanta, but
I’m not on the Subcommittee, but I’m glad to be here. Thanks.

DR. BOTKIN: I’m Jeff Botkin. I’m a guest today. I’m from the University of
Utah and I’m a pediatrician. I do Bioethics and I’m the Associate VP for
Research at the University.

MS. KAHN: I’m Hetty Kahn. I’m with CDC’s National Center for Health
Statistics. I’m Staff to the Subcommittee in Privacy, Confidentiality and
Security.

MS. CHAPPER: I’m Amy Chapper. I’m from the Centers for Medicare and
Medicaid Services, and I’m Staff to the Subcommittee.

MS. GREENBERG: Good morning and welcome to NCHS. I’m Marjorie Greenberg
from NCHS CDC and Executive Secretary for the Committee.

MS. KANAAN: Susan Kanaan, Writer for the Committee.

MR. SUAREZ: Good morning, everyone. I’m Walter Suarez with Kaiser
Permanente. I’m a member of the National Committee. I Co-Chair the Standard
Subcommittee and I’m a member of both the Population Health, and the Privacy
and Security Subcommittees. And no conflicts, thank you.

MS. BERNSTEIN: I’m Maya Bernstein. I’m the Privacy Advocate of the
Department. I sit in the Office of the Assistant Secretary for Planning and
Evaluation. I’m Lead Staff to the Subcommittee on Privacy, Confidentiality and
Security.

DR. FRANCIS: I think we should go next to the phone, and then we’ll go
around the room. So Larry?

DR. GREEN: Dr. Larry Green, University of Colorado. Front Range passes are
closed this morning because of a winter snow storm. Member of the Full
Committee and no conflicts, just wishing the passes would open up.

DR. FRANCIS: And I think we also have Michelle Justus on the phone?

MS. JUSTUS: Yes. I’m Michelle Justus and I’m going to be presenting this
morning. And I am the Director of the Arkansas Obesity Initiative at the
Arkansas Center for Health Improvement.

DR. FRANCIS: Thank you.

MS. MAIN: Good morning. I’m Debbie Main. I’m from the University of
Colorado. Larry, I made it out here because I didn’t have to go through the
passes. And I will be presenting this afternoon.

MS. JONES: Katherine Jones, NCHS and Staff to the Committee.

MS. JACKSON: Debbie Jackson, NCHS CDC Committee Staff.

MS. RHODES: Rosamond Rhodes, I’m a philosopher, bioethisist at Mt. Sinai
School of Medicine, and at the Community Graduate School and at the Union Mt.
Sinai Bioethics program.

Agenda Item – Panel I Engaging
Communities

DR. FRANCIS: Okay, we’re set to go. So the first panel is entitled
“Engaging Communities.” And we have Michelle Justus, who’s here as
the Director of the Arkansas Obesity Initiatives, and then we’re going to hear
from Jeff Botkin. So why don’t we start with Michelle? We’ve structured this to
make sure that we have plenty of time for discussion because our goals here are
really to learn. So Michelle?

MS. BERNSTEIN: And also, I want to let you know, Michelle, someone is here
to turn your slides for you in the room, so if you could let her know when
you’d like to proceed, that’d be great.

MS. JUSTICE: Okay, great, thank you. First, let me apologize that I was not
able to be there. I’m actually about eight months pregnant and not able to
travel at this time. But again, I appreciate you guys having me.

MS. BERNSTEIN: We’re very glad to have you any way we can have you.

MS. JUSTICE: Thank you. But I’d like to present today to you all about the
Arkansas Body Mass Index Initiative that’s been going on here in Arkansas since
2003. So if you can go to the slide that says BMI assessment, and that’s for
the first year, and then to the next slide that shows the timeline of events.

So in April of 2003, the Arkansas General Assembly passed what we call here
Act 1220 and it’s a multi-component act. But I guess the component that a lot
of people have heard about and got a lot of media attention was the actual body
mass index assessments in our schools. So this was actually an assesment that
was state-mandated. It was an unfunded mandate, so there was not funding that
was given to the schools to actually do these assessments.

So in June of 2003, the Arkansas Department of Education and Arkansas
Department of Health, who in the actual Act were required to do this in our
state, turned to our center, The Arkansas Center for Health Improvement, and
asked us to help them and develop a standardized protocol for doing these
assessments across our state, and help with the implementation of this
initiative.

And so, we did not have a timeframe of, “Okay, well, let’s take a year
or two to take figure out how to do this, and then start implementing.” We
had to figure out how to actually do this, and then implement it all within one
year, so it was a pretty chaotic and crazy first year. So we had to determine
how to assess height and weight, and calculate body mass index on 450,000
students across our state in the public schools.

So in September of 2003, we worked with the University of Arkansas for
Medical Sciences and Arkansas Children’s Hospital to develop a standardized
measurement protocol, so all of the schools across the state were using the
same measurement protocol, so we developed that protocol. In October of 2003,
we actually tested all different types of equipment, scales and stadiometers
that measures height, to make sure. Actually, the main reason we wanted to test
it was to see what type of equipment that we could get away with using.

So our schools, since it was an unfunded mandate, we didn’t have enough
funding to go out and buy research grade equipment. So we wanted to see if
using a bathroom scale was sufficient or at what level did we need to use the
equipment. So what we found was that we used somewhat of a size scale that
wasn’t necessarily the bathroom grade.

DR. FRANCIS: Sorry, we’re having a little phone trouble.

MS. JUSTICE: Okay, that’s fine. And so, then we actually built our own
stadiumometer to measure height. So we wanted a stadiumometer that was
portable, that schools could combine all of their equipment within a district,
and have multiple stations if that’s what they wanted to do.

So then in November of 2003, we actually, here in Arkansas, through our
health department, have what we call “community health nurses,” and
they work directly in the educational cooperatives across our state. So they
actually trained all of the school personnel on the standardized measurement
protocol. So for the most part, school nurses or the school personnel that do
the assessments, there are others in some cases that do it, but whoever does
the assessment has to be trained in the standardized protocol.

Then in January of 2004, the actual assessments began statewide, so we
piloted it in the fall, and began doing it statewide in January of 2004 and
collecting the data. And then, in June of 2004, the individualized Child Health
Reports were mailed to parents or guardians.

Next slide, please. And so, really quickly, the process of year one, we
received a data file from the Department of Education, Arkansas Department of
Education, with all of the demographic information. So we didn’t have to have
schools provide all the names and information that we needed to calculate body
mass index. And so, once we received that data, in the first year, we had not
had time to develop an electronic entry system, so we had to do the entire
project paper-based, which if you can picture 450,000 sheets of paper, it’s
quite a lot, more than we ever imagined.

And so, what we did was we generated individualized bar coded forms, and we
mailed these directly to the school for the data collection. So the demographic
information was populated at the top of the form, and the schools completed the
height and weight assessments, and then got those back to us. And how that
worked, for confidentiality reasons was that, at the time, it just so happened
that Kinko’s and FedEx merged together to become one. And so, we actually had
them make all of the photocopies for us, and ship them directly to the school
through FedEx, so we had a mechanism to track the information and know where it
was at all times. We also provided the schools with a FedEx return label
prepaid, so they could FedEx it back to our center.

So the data was collected, using paper forms from the school, and returned
to our center. And then, we actually had around the clock data entry personnel
to enter the information and do validity checks on the data entry. And then,
our center generated a Child Health Report for all of the approximately 422,000
students, and mailed those to the parents by the postal system. And then, the
schools were actually given password-protected files so they could keep that
for their records.

Next slide, please. So this is just an example of what the Child Health
Report looks like. It still looks basically the same today. And the table that
you can see or the little graphic that you can see actually is a visual for
parents so they can see where their child actually falls and which
classification category their child falls.

Next slide, please. So in the first year, we did have five types, and we
still continue to have five types of Child Health Reports. We have one for
children that are overweight, one for at risk for overweight, healthy weight,
and actually these categories, as you know, have changed. This was in the first
year. Now, we’ve changed them and updated them to use the current CDC
classification category. And then, we had one for underweight, and then one if
the child was not able to be assessed. We had a generic report that went home
to the parent, just explaining what body mass index is and some healthy tips
that they can use in their family.

And again, the first years of reports were mailed directly to the parents,
using the address that was provided by the Department of Education, so we were
ensured that we were receiving the correct parent or guardian’s information,
because we were somewhat concerned or we were concerned that, when you get into
guardianship, and especially in divorcee cases, then who has the right to have
it. So we got all that information from the Department of Education in
Arkansas.

Next slide, so that was the first year. The second year, we realized very
quickly when we started receiving all of these 450,000 sheets of paper in our
office and we had to store them in a confidential manner, that this was not
something that we could continue to do through every year. We had stacks and
boxes of paper everywhere, under lock and key at all times, and it was a whole
lot to manage.

Next slide, so the year two process, we decided that we really needed an
electronic entry system that was web-based for the schools to enter this
information into. So the majority of the students’ information continued to be
the same process that we had in year one, but we did have two different school
districts participate in a web-based pilot system. One of the school districts
actually recorded information on paper, and then entered it into the system at
a later date. And then another district in our state had pocket PCs and this
was before iPhones and all that type of thing. But they had pocket PCs that
they could enter the information into and then upload it to their computer.

And so, then once they uploaded it, the data was stored in our secure
web-based system. The Child Health Reports were generated by our center, and
all of the schools had access to their Child Health Reports from the secured
web-based system. All of the schools, each nurse, was given, or school
personnel, was given a user name and password to pull the information from our
website.

And the second year, the other thing that happened was that we actually
outsourced the data entry to the University of Arkansas in Fayetteville,
Arkansas, Survey Research Center who is a center that’s used to dealing with
this type of data. And they actually entered all of that into our system for
us.

Next slide, in the second year, we also added a Spanish Child Health
Report. So one of the pieces of information that we get from the Arkansas
Department of Education is primary language spoken by the parent. And so, for
those that their primary language is Spanish, we do provide them with a Spanish
Child Health Report.

Next slide, so in year two, again, we had five types of individual Child
Health Reports, and they were generated both in English and Spanish. Those that
were generated in Spanish, we also had an English version for the schools to
have for their file.

And then, in the second year, we did not receive funding. In the first
year, our center received funding to mail the Child Health Reports to the
parents. In the second year, we did not receive funding, so that became a
responsibility of the schools. We highly encouraged them to get these reports
to the parents in a confidential way, such as mailing. Some of them hand them
out at parent-teacher conferences and different things like that. Since the
schools have local control, we do not have a way to control how they send those
to the parents, but we do provide examples and reasons why they should not hand
them directly to the children.

And then, the College of Public Health at the University of Arkansas for
Medical Sciences also does our evaluation of the entire Act 1220. And the way
you can see when they ask the schools how they’re actually getting the reports
to the parents, those are the different types of ways that they are actually
giving them to the parent. So the majority of them still continue to mail them.
Some of them have sent them home and others gave them out at parent-teacher
conference, and some of them let them pick them up at the school.

Next slide, so year three, get to the next slide, the year three process
was still again, we had approximately 300,000 students continue with the
paper-based process. And we included another option for those pilot schools
that we had. We increased the pilots to 16 districts in the state, and we also
had another option which was direct web access. So if they had laptops in their
school and they could get on, or a computer where they could still do the
assessments in a confidential way, they had access to the web system and they
could directly enter the information at that time. And the schools did have
access to the Child Health Reports by the website.

Next slide, so now to years four through seven, and we are currently in
data collection of year eight, so year eight is the same as years four through
seven. Next slide, and so now, beginning in year four, we went completely to
the web-based system, and schools basically have two options of how they can
enter this information. They can do direct web-based entry into the system, if
they have access to a computer nearby where they’re doing the assessment. Or
they can actually write the information down and enter the information at a
later date.

Next slide, so I don’t want to spend a whole lot of time on the results
because the information is on our website, but this is the most recent data
that we’ve released. Next slide, and in the 2009-2010 school year, you can see
here that this is the percent of students that their information was
calculated, so 83 percent of the data that we received was valid for BMI, so we
have BMIs on 83 percent of the information. Seventeen percent of the data was
children that were not assessed for various reasons. They might have been
absent. There is an option for parents or children to refuse, and there’s a
various list of reasons why they may not have been assessed.

And then, there was a very small percentage of data that a component of the
data needed to calculate the BMI was not available, so it was not valid for
calculation. Next slide, this is the results for the past few years. You can
see that it’s very consistent across the years. There’s approximately 38
percent of our students in public schools here in Arkansas are either
overweight or obese. Next slide, this is just a breakdown by classification and
gender, and pretty equally distributed, females 38 percent, males 39 percent,
either overweight or obese.

Next slide, this is broken down by ethnic group, and you can see that in
our state, Hispanics have about 40 percent of Hispanic children that were
assessed are either overweight or obese. Forty-two percent African-Americans,
and then 39 percent Native-American, 36 white and 31 percent Asian. Next slide,
the BMI classification by grade, you can see that pretty much in the middle
school grades, there’s a spike in BMIs and then it starts to head down again.

Next slide, this is BMI classification by gender and ethnic group. Again,
the Hispanic males, 50 percent are overweight or obese. And then, the next
highest group was female African-Americans, 45 percent, and the lowest was
white females at 34 percent. Next slide, BMI classification by gender and
grade. Again, you see the spike in the middle school years, and then it starts
to trend down again.

Next slide, this slide is somewhat complicated if you look at it at first
glance. It’s classification by gender, ethnic group and grade, and it’s
consistent with the other results. And then next slide, this is a map of our
state and the white lines are the county lines, the black lines are the school
district lines, and it is pretty busy. But the point of this map is that,
first, let me point out that there are a few white spots on the map and those
white spots are the schools that did not actually participate. So where there’s
blue on the map, are all of the schools in the state that did participate. So
you can see that we have a pretty high participation rate in our state, as
should be expected since it is state law.

And then, the other really important thing about this map is that all of
our schools in the state, no matter where they’re located and what their
population might look like, they all have an obesity problem. So even the
lowest rates are 20 to 30 percent. So the lightest blue are 20 to 30 percent
overweight or obese, so there’s a problem in our entire state.

Next slide, and then this is just my contact information, if you all have
questions after today, I’d be more than happy to answer them. I may not have
addressed all of the questions. You may have questions and I’m more than happy
to answer any of those questions. I did not get a lot into the confidentiality
and security, but I’m more than happy to answer those questions, if I know the
answer. If not, I can definitely find them out for you.

DR. FRANICS: Thank you very much. I think we will, in the discussion, I
know we’ve got a considerable amount of time for discussion, so I suspect
people will want to follow up on some of those questions, too. That was
fantastically interesting, thank you. I want to take one second to let a new
committee member who’s come, introduce himself. Paul?

MR. TANG: Yes, hi, Paul Tang, Palo Alto Medical Foundation, Member of this
Subcommittee and Committee, no conflict.

DR. FRANCIS: Yes, okay, thanks, Paul. And now, we’ve got Jeff Botkin, who’s
going to talk about public engagement in biobank research. Jeff’s getting miked
up. Can the people on the phone hear Jeff?

DR. BOTKIN: Testing, testing, can you hear me on the phone?

MS. JUSTUS: Yes.

DR. BOTKIN: Well, thanks, Leslie for the invitation to be here. And I’m
going to talk a little bit about a couple of issues that I’ve become familiar
with in recent years. I’m part of a group at the University of Utah that is
engaged in developing biobank in a federated data set resource for the purposes
of biomedical research. I’ve also been conducting in recent years a NIH-funded
study looking at blood spot retention by state public health programs, and
public attitudes related to that. And I’ve also been involved with, at the
federal level, the Secretary’s Advisory Committee for Human Research Protection
that has also been focusing on some biobank-related activities.

Now, I’m going to be talking, for the most part, using terminology about
biobanks. But I don’t think, from my perspective, at least, there’s often a
significant distinction between biobanks and data repositories. And it may well
be that distinction becomes increasingly blurred over time, as for example, we
can efficiently sequence DNA for example. It may well be that, for certain
types of research, you simply store the sequence rather than the sample itself.

So I’ve got a fair number of slides here and I’m going to keep an eye on
Leslie, when she gives me the high sign to wrap it up. So this is just a
reminder of what I think is evident to everybody, that there’s an enormous
amount of research that’s developing, a lot of capabilities for combining
sophisticated tissue analysis, linked with extensive health records. Folks are
very excited about this form of research and digital technologies, making this
increasingly possible.

Here’s the key ethical issue, though, as far as I’m concerned. It’s that
the biobanks and data repositories permit the analysis of tissues and datas at
times and places remote from the source. So traditionally, we’re used to
research context in which there’s a fairly close relationship between the
investigator and the research participant. Increasingly, though, with these
sorts of analyses can be conducted remotely. So the key question then becomes,
“How much control should sources have over research conducted with their
samples or data?”

When is notification or consent required? What should be the scope and
nature of informed consent for this type of work? And how should biobanks or
data banks be governed in order to secure public trust. The question here is,
can we move away from a traditional informed consent model, to allow this sort
of research to go forward.

So part of the issue here is that there’s no public knowledge or very
little public knowledge of many sorts of biobanking and secondary use of
biospecimens. Folks who are having their clinical specimens stored and used for
research purposes simply aren’t aware that this is a mode of research that’s
being conducted, and that’s particularly true in this particular domain that
I’ll talk with newborn blood spots.

When informed, the data pretty clearly shows that there are significant
public concerns about privacy for secondary uses of specimens. And again, I
mean here specimens, as well as data. Risk to individuals, however, as far as
I’m concerned, are really quite low, but risk to population groups exist, but
this particular type of risk is poorly addressed, if at all by the current
regulations.

So individual harms and wrongs, I think we’re used to thinking about in
this context. What are the risks of biobank and data depositories, breaches of
confidentiality, leading potentially to stigma and discrimination, breaches of
privacy that may cause potentially tangible harms or dignitary harms. And the
psychological impact, usually from predictive information in these sorts of
context. When you have an analysis of tissue sample for predictive, say
genetic, information, then returning that information to the source could
conceivably lead to psycho-social or psychological impacts.

But I would claim that such breaches are rare. The literature pretty
clearly shows that, at least for individuals who participate in predictive, say
genetic, research, the psychological impacts of that information are proving to
be quite low. You see a spike in anxiety within the first weeks or months after
disclosure of at-risk information, that then declines to below baseline by a
year or so, and this is pretty consistent across a variety of research that’s
been conducted over the last 20 years in this domain. And of course, there are
some predictive measures that are out there to begin to deal with things like
genetic discrimination, genetic information on discrimination act that, as
everybody here, I’m sure, knows that is in place, but is yet to be adequately
tested.

This notion of group harms is important, but again not adequately covered
by the regulations. This simply refers to a study that folks probably familiar
with here, Arizona State University, where they have the Havasupai Indians, in
which they were recruited for diabetes-related research, blood samples taken.
Those samples were subsequently distributed to other institutions and research
was conducted that was beyond the original consent agreement between the
participants and the investigators. The tribe learned of this research and
became appropriately upset and brought suit about that issue. Again, the
allegation here wasn’t so much that there were individuals who were harmed
through the use of this information, but yet the group experienced harm or
potential harm by the distribution of samples beyond what had been anticipated
by many of the participants.

So what do we know about public attitudes about this issue in general?
Institute of Medicine Report, 2009, this was on HIPAA privacy and so they had
done a nice job, I think, of reviewing the literature. They talk here about a
Harris poll, 63 percent of Americans would give general consent for use of
medical records and research with privacy protections. So a majority certainly,
but a substantial minority would not give such permission.

The majority of respondents in several studies expressed a desire to be
consulted before information is used in research, including when data is
de-identified. And I would just emphasize that this is such a consistent theme
in the literature in this particular domain, and I’ll show you some of our data
about newborn blood spots. But the consistent theme is people want a choice.
And if you ask them, they’ll say “yes” for the most part, but they
want to be asked. And again, what I’m presenting to you is what I see as a
contemporary challenge in that domain, because it’s increasingly hard to simply
ask people their permission.

A little more information about general attitudes that Kathy Hudson
published in 2009. A large US survey of over 4600 participants about biobank
research. Forty-eight percent supported blanket consent for future research,
meaning they would be willing to say, “Go ahead and do what is appropriate
for pursuit of science in the future.” However, 42 percent wanted consent
for each project using their sample. Almost half then, 42 percent, wanted
individual project-specific control over the use of their sample, and ten
wanted categorical consent where they could say, “Okay to use it for
cancer research, but not for other particular domains.”

Another study, this was a focus group participants’ opinions about
providing study-specific consent. So participants were asked if they agreed or
disagreed with these statements about how they would feel if they had to give
permission for researchers to use their samples and information before each new
research project. So here’s the top category, I don’t have a pointer here.
“I would feel it was a waste of time and money.” How many agreed with
that? Twenty seven percent. Seventy three percent disagreed that they thought
it would be a waste of time or money to contact them about each project.

“I would feel bothered.” Well, 26 percent agreed with that, a
large majority disagreed with that, that folks would not feel bothered or a
waste of time to contact them. Conversely, “I would feel I have
control,” 75 percent agreed with that. “I would have more trust in
the study,” 75 percent agreed with that. “I would feel respected and
involved,” 81 percent agreed with that. So you can see the strength of
public opinion, with this sample, at least, about how much people want to have
that individual level of control over samples and biobank-related research.

So here’s our project, and I’m going to give you just a little bit of
information about the study we’ve been doing for the last three years. This
gives you a graph of how state health programs are retaining residual newborn
screening samples. Now, quick reminder, these are screening tests that are done
under state mandate, in all states in the United States and around the world
for most developed countries. Blood spots obtained within a day or two of
birth, battery of 30 plus different conditions are assessed through that
bloodspot, usually to state lab. And then, those results are promptly returned
to clinicians when necessary to address the needs of the child.

So, typically rare conditions, but in almost all circumstances, there’s
residual blood left over on those filter papers. So what do you do with those?
A lot of states will discard them, only retaining them for a month or two or
three months, in order to make sure the tests are adequately completed.
Sometimes retesting of the samples is necessary, so they’ll keep them for a
couple of months. Once you kept them for a year or longer, it’s pretty clear
you’re keeping them for reasons other than the conduct of the screening tests
themselves. Now, these are conducted under state mandate, parents are not asked
their permission, although most states have an opt-out mechanism for
philosophical or religious reasons.

However, the vast majority of parents aren’t effectively informed that they
have that option. It’s in the brochure that’s in the bottom of the bag that’s
given to folks when they have a new baby, so virtually nobody opts out.

So you can see the number of states store the specimens indefinitely, or
for many years. California and New York, for example, are two states that store
them indefinitely. So it’s about half the babies in the United States, because
a couple of the large states retain them indefinitely, have these specimens
retained for decades.

It’s not been without controversy. The article in Discover magazine now, a
couple of years ago, newborn blood storage lost or fears of DNA warehouse.
Help, the government has my DNA. That lady on the right doesn’t seem to be
concerned enough about that situation. And there have been at least two states
that have now been sued for this practice. Minnesota, the suit was based on a
claim that retention of the samples without consent was inconsistent with the
state genetic privacy laws. The parents who brought that suit lost that case.
The decision was made that newborn screening was not covered by the Genetic
Privacy Act.

In Texas, a constitutional suit was brought, the claim being that this was
unlawful search and seizure. Well, the state didn’t want that suit to go
forward. I think with some concern, perhaps, that if they were to lose that
suit, there would be quite a bit of activity that was conducted in the
biomedical arena that might fall under that general category of unlawful search
and seizures, since we know data and specimens obtained clinically are used for
research purposes, often without the explicit consent of the people involved.

So Texas came to an agreement with the parents, destroyed five million
samples that had been retained for a number of years. It looked like it was
going to be resolved, and then it became public knowledge that the state had
shared about 800 samples with the Department of Defense that was interested in
using these specimens to further refine their personal identification system
that they had for remains. The allegation was that this information was being
withheld or hidden. The state denies that, but at any rate, a new suit has been
brought that is currently working its way through the courts.

A new suit has been brought in British Columbia, in Canada, so even
Canadians are concerned about this kind of process. New Zealand is now
experiencing significant controversy, so this is sort of a global phenomenon
that has been occurring because this practice has been ongoing for a number of
years, without adequate public engagement, in my opinion.

So we have a project that’s a three-year project, “Methods for
Promoting Public Dialogue on the Use of the Residual Newborn Screening Samples
for Research.” We have three specific games. This first one is to do a
comprehensive assessment of health department policies and procedures. And we
have a publication out just this last month to document results of that survey.

A key part for today’s discussion is our outreach to the community, to
ascertain public attitudes about this particular issue. We had three different
methods; we surveyed the public, surveys, focus groups and then Knowledge
Networks. Knowledge Networks is a company that has a pre-established panel of
individuals, representative of the U.S. population across the U.S., who have
technological support, computers basically, and they do electronic surveys for
a variety of different purposes. So the question for us was whether Knowledge
Networks was a less expensive and more efficient way to access public opinion,
other than focus groups or traditional surveys. Third specific game was to
conduct a working group to try to craft recommendations on policy in this
domain.

So here’s our assumptions, we’ve got the general public is not aware of
this issue, and increasingly aware, given the lawsuits, but for the most part,
the public doesn’t know this is going on. And therefore, basic education on the
issues was necessary to obtain informed opinions. We didn’t think we could
simply go out and ask people what they thought of this practice, without giving
them some education about what the practice was.

So we prepared a 22-minute video that covered newborn screening, retention
of samples, pros and cons, interviewed experts across the country, public
health individuals, ethicists, attorneys and others, about this practice. And
to some of our sample, gave them this educational intervention as a way of
providing them with sufficient background to provide a more informed opinion
than they would otherwise have. The survey instrument itself also had a little
bit of information about this practice, typical for a lot of surveys that would
give you a modest amount of information about the issues you’re being asked to
address.

So here’s our groups. We had three percent in traditional focus groups, all
of whom saw the movie. Surveys conducted by a company, Dan Jones, paper,
telephone, about 37 percent, and then Knowledge Network’s approach was 60
percent of our folks. About half saw the video, about half did not. Here’s our
responders, a pretty good diversity across our racial and ethnic groups,
mothers of young children included. About 40 percent was outside the mountain
states region, because we weren’t certain whether mountain states might have
some particular philosophical mince in this particular domain. A majority were
women.

So a little bit of the results here. “Did you know that these tests
were done?” These are the newborn screening tests themselves, and you can
see that a little over half were aware that newborn screening was done. Pretty
clear through the focus groups that folks didn’t have much knowledge beyond
that. You know, they might think this is the PKU test, for example, when in
fact, it’s a test for 30 or more different conditions, so a lot of folks were
aware that babies did get tested.

So here’s specifically about this retention issue. “How supportive are
you of health departments doing these blood tests on all new babies?” I’m
sorry, this is the newborn screening part itself, not the retention. “How
supportive are you of newborn screening?” You can see between very
supportive and somewhat supportive, we have pretty much everybody. People think
newborn screening’s a good idea. This isn’t a hard sell. They like the general
concept of newborn screening.

But do you think it’s all right that these tests are done without the
permission of parents? Now, here you see almost an exact 50-50 split, with the
largest single category being definitely not okay to do newborn screening
without the permission of parents. So the traditional approach that’s been used
in this domain of mandatory screening is okay by half, but not okay by another
half.

DR. TANG: I’m just clarifying that these are the ones that are listed that
they’re going to do immediately, versus the ones that are done when they’re
retained.

DR. BOTKIN: That’s correct. Yeah, these are for the clinical specimens
themselves. And this has been a big deal within the field for a while, where
the public health departments have consistently pushed back against a consent
model because of the complexity and difficulties of obtaining that. Now,
actually, Maryland is a state that, for many years, had an opt-in model where
parents had to sign a form in order to have these tests done. But at least,
anecdotally and by experience, it was never anything more detailed than
“sign here, your baby is going to get a blood test.” It really wasn’t
an informed piece to the informed consent, and within the last year, Maryland
has abandoned that approach and now has an opt-out approach, as many other
states do. So Maryland was sort of the one example out there for many years
that was a little different.

How concerned would you be if health departments save the leftover blood
samples from babies after the tests are done? And again, here you see again
almost an exact, well, this isn’t a 50-50. What you see is not at all
concerned, 25 percent, only a little concerned, 20 percent, somewhat concerned,
24 percent, and then very concerned, about 28 percent. So again, while there’s
a full spectrum here, the single largest category is very concerned at about 28
percent or so.

So here’s a quick vignette we gave them. Imagine that a health department
has been saving leftover samples for the past ten years, without the permission
from parents. Now, imagine that researchers want to use the samples for
important health research. It may be difficult and costly to find many parents
after several years. If parents cannot be contacted, what would be the best
thing to do with their babies’ leftover samples? “Allow use” was
clearly the predominant choice here. So when push came to shove, can’t contact
parents, should we use them or not use them, majority saying allow use.

Another vignette, some health departments keep samples only if parents
agree to this by signing a form. In other states, all samples are kept, unless
the parents contact the health department and say they want their child’s
sample destroyed. What do you think is the best thing to do? Keep samples only
if parents sign a form or keep samples unless parents contact the heath
department to have them destroyed? So, an opt-in model versus the opt-out
model. Clear predominance of parents want to have the option to sign it in.
Okay, and they don’t like the opt-out as much, even though probably 38 percent
or so thought that the opt-out was okay.

So final question, we had a whole series of other questions that I don’t
have data for you today about. But final question here, after thinking about
these questions for the last few minutes, we want your final opinion. Do you
think it’s all right to use these leftover blood samples for doing important
research? Definitely all right, probably all right, clearly the predominant
choice is here, probably not, definitely not all right, small minorities. And
here, the idea was that we wanted to return to the basic question because we
thought answering the survey itself would be educational for folks because it
would give them an opportunity to think about some of the complexities and the
different aspects of the issues.

So the public really is clearly quite supportive of the ability to do
research in this particular area, but again, no question that they want an
active role, or the majority do want an active role in having something to say
about that. So we looked to various associations for what led different people
to be more or less supportive, support for retention and use generally
associate with the video viewing. This was the most consistent fact. People who
had the educational video were more supportive.

Now, at the beginning, we weren’t certain whether folks who knew more about
this would be more supportive, or more upset or outraged about it, and it’s
clear that education about this leads folks to be more supportive. Female
gender and more liberal political ideology were also more supportive. Support
generally not associated with our mountain states region for race or ethnicity
or for religion.

So conclusions from our particular study, strong support for newborn
screening clinical services, general support for sample retention and research
use, but a desire for choice over retention. More information is associated
with greater support, so we think providing the public with greater education
about this will benefit programs, rather than what’s been the tradition for
many years, which is programs trying to fly below the radar. They’ve been
thinking, I think, that just not talking about it was the best way to go, and I
think they’re getting burned in Texas and Minnesota and elsewhere for a lack of
transparency about this process.

And here’s our research team. It’s been a terrific group. My general
conclusions about this whole area then. Biobank and data dependent research is
going to continue to expand. This is really a very important and powerful mode.
But appropriate authorization of the sample and data use is at least a key
ethical issue here. I think the risks associated with this type of research are
very low. I really think the loss of laptop phenomenon is probably one of the
most common methods by which data are inappropriately lost. But I’m not aware
of a track record of specific harms to individuals that have been documented
through this type of research.

Public has substantial concerns about privacy and control, nonetheless, so
I see a discrepancy here, again, from my perspective, between what the real
risks are and what the public thinks the risks are. And so, in the absence of a
consistent ability to engage people at the individual level about the variety
of choices that might be available for this, potentially a governing structure
should be fostered for these entities that will help promote public trust.

Having said that, we asked our participants in our study about, “Would
you feel comfortable if there were a public representative of you to help make
these sorts of decisions, rather than you personally?” And they frankly
gave us blank stares, it was like, “What are you talking about? What do
you mean a public group? What does that mean?” So they didn’t really get
the notion that there could be representatives who might try to protect their
personal interests, they want to be asked. And I don’t think we adequately
reflected to these individuals the complexity of that request. It was
consistently, “Just ask me and I’ll say yes.” But the whole notion of
“Just ask me” is a complex and difficult, expensive prospect, and I
don’t think folks adequately understood what they were looking for in that
respect.

So that’s sort of the next hurdle for us to begin to look at some of these
issues about what folks are comfortable with in certain forms of biobank
research. So we’ll have some focus groups in the upcoming months, throughout
the state of Utah, about our initiative for biobank and data federated
research, and see what our local public is comfortable with in this domain.

DR. FRANCIS: Thank you. We now have a little over half an hour for
discussion, and I’m going to invite committee members and others to ask
questions.

DR. GREEN: Leslie, my hand’s up.

DR. FRANCIS: Okay. So Larry, since you’re on the phone, and the phone folks
sometimes have the hardest time to get a word in edgewise, go for it.

DR. GREEN: I want to first of all thank Michelle and Jeff both for being so
useful and so on target, and I’m just very appreciative of what you’ve done
this morning. I have one question for each of them, it’s about harms and risks.
For Michelle, my question was just if she could tell us of any adverse reports
from the whole Arkansas exercise, related to complaints or concerns from
parents or advisory groups, or legal actions or known breaches in the
confidentiality policies that they adopted, or stigmatization by race and
ethnicity groups, any adverse effects. And my question for Jeff was, I’d like
to ask him to render his personal judgment and opinion about what would
actually constitute adequate public engagement concerning the use of biobank
data.

DR. FRANCIS: Michelle, you want to?

MS. JUSTUS: Sure, I’ll go first. You know, obviously we’ve had some adverse
effects. But the College of Public Health here in Arkansas does a very good job
of evaluating this. And they’ve really found very little, if any, causes. I
mean, one of the big concerns was that BMI assessments could cause eating
disorders. And their evaluation report has not shown that at all, from the
youth and the parents that they survey. Our data doesn’t necessarily show that,
although anorexia could probably be picked up in the underweight category
increasing, but bulimia obviously doesn’t necessarily mean a drop in weight.

But as far as confidentiality breaches, there have been some anecdotal
reports that I’ve heard that schools have actually given the report to the
child and not followed our strong recommendation. And there have been some
cases of children being made fun of, due to that. So I think the schools have
learned quickly to do this in a confidential manner and that it is important to
get these reports to the parent in a confidential manner.

As far as the College of Public Health also does, like I said, a parent
survey, as well as a survey with youth. And they have found that 75 percent of
parents are not at all or only a little concerned about classmates finding out
BMI measurements. So there is still a 25 percent of parents that are concerned
about it. Our protocol at our center is that, if we do hear a complaint or
receive concerns from parents or schools, we have that investigated. We find
out what happened and try to address it with additional training to prevent it
from happening again.

We also do have our community health nurses do spot checks with schools, to
ensure that they’re following protocol. But it is a serious situation and we do
take it serious, and we obviously want this to be a helpful tool for parents,
and not something that is harmful to children or to families. And I hope I
addressed your questions.

DR. GREEN: You did very well. Has there been any adverse action taken
against the State of Arkansas?

MS. JUSTUS: No.

DR. BOTKIN: Yes, great question, and I guess I would say the following
certainly depends on the particular context. But I personally am comfortable
with, in general, an opt-out system, despite what our own data showed about
parents’ desires in this particular context. I think an opt-out system
adequately protects the interests of people, while allowing this sort of
important research to go forward.

However, I think there has to be some clear notification of what people’s
options are. People have to be given an explicit opportunity to opt out. I
don’t think this is a circumstance in which it’s appropriate to bury people’s
options in the paperwork, and have them call a phone tree at the hospital or
health department, in order to have their sample or data excluded. So I think
it has to be upfront and clearly stated in ways that people would understand.

I also think that an element of transparency here is essential, where there
ought to be public reports, newspapers, television, opportunities to present to
the public what’s going on. There should not be any suggestion that this is
being done in the basement behind closed doors. And so, I think engaging with
the media about these sorts of activities is going to be important. I think
that, in and of itself, will reassure people that there’s nothing too nefarious
going on.

So I do think there are challenges with figuring out how to do this in
effective ways. Vanderbilt, with their BioVU program, I think has done a pretty
good job with implementing an opt-out approach, and they’re finding that 95
percent of folks are not opting out of their biobanking initiative, and I think
they’ve done a nice job of community engagement, assessed public opinions about
how they’re approaching this and maintain public trust in Vanderbilt’s efforts
here. So I think it is possible to do this in the right way.

DR. GREEN: Thank you.

DR. FRANCIS: Thanks. So I’ve got Sallie and Paul and Walter and Marjorie.

MS. MILAM: Okay. I’ve got a few questions. I think I’ll just ask a couple
of general ones, and then hold the rest until everybody has a chance. I’m
wondering if you could each speak to the different identifiers that were saved
around the data in the databases. So were you saving name, address, birth date,
SSN, that kind of thing? And then, a follow-up question for Michelle. We heard
a lot about Jeff’s process of educating and notifying the folks around the
consent decision. But I was wondering if you could also speak to that process,
if you had one, around the collection of obesity information.

MS. JUSTUS: Sure. First, the data component piece. We do get all of the
demographic-type information from the Department of Education, which includes
name, date of birth, gender, ethnicity. We get what’s called “free and
reduced lunch,” which again is a proxy for socioeconomic status, and we do
have all of that. A lot of it, we have to have in order to calculate BMI, but
once we get the information out of our web-based system to store it and do
analysis on it, we do de-identify that information. And we actually have IRB
approval from the University, once the data’s pulled from the web system, and
so we have to adhere to all the IRB, the data security components of that.

Can you repeat the second part of the question? I want to make sure I
answer it correctly.

MS. MILAM: Sure. I’m wondering, as the children were lined up at school to
get weighed, was there any sort of discussion with the parents ahead of time,
were there community meetings, was a letter sent out? How was the process
explained to the parents around the consent decision?

MS. JUSTUS: That was really left up to the schools to decide how they
wanted to handle that. Some of the schools do actually send out letters to
parents, notifying them that this screening tool will be assessed, just like
vision and hearing in the schools. They send out a generic letter about all the
screens. Some of them put it in their handbook at the beginning of the year
when parents registered. But because it is state law, there’s not a required
consent or they don’t have to get permission from the parents.

In the initial years, the law was silent on if a parent could even refuse
for their child to participate. Our center, I guess, interpreted it, or gave
the school an out, because we didn’t want any child forced on a scale. And so,
what our center did was on our form, for a reason that the child couldn’t be
unable to be assessed, they actually had a place for the school to check that
the parent refused or that the child actually refused. So they weren’t put in
an awkward position and forcing a child to be assessed.

Since the original act was passed, there’s been some amendments to the law,
one being that, now parents do have the option to opt-out. But it is the
responsibility of the parent to write a letter to the school, and it is not the
school’s responsibility to notify the parent and to give the parents an option
to opt out.

DR. BOTKIN: Quickly, with respect to the newborn screening samples,
typically, of course, those differ somewhat by state, by they’ll have name and
identifying information for the family, address, birth date, the baby’s weight
and identification of primary care provider, to whom the results would go.

Now, typically, specimens that are being stored will be stored with all of
the original data that’s associated with that card. But in most circumstances,
or virtually all, investigators who access those samples would receive the
identified samples. There has been at least one example otherwise for that, in
which samples were being used to test for CMV, cytomegalovirus, that can have
hearing implications for babies, and they wanted to be able to get back to
families with information about prenatal infections for CMVs, so that the
families could address potential hearing loss in the babies.

But mostly, it’s de-identified. Some of the research here has been quite
appropriately done with de-identified samples. Some of the early uses were with
tracking HIV infection in mothers in New York and Massachusetts during the
1980s. These specimens were used in a de-identified fashion to see which
communities, over a period of time, were seeing increases in HIV infection, for
example. So those sorts of geographic locations may well be retained with the
samples for that sort of epidemiologic purpose.

DR. TANG: Thank you. And I found the presentation very interesting. Some
questions, I think mostly for Jeff. I have four of them, they’re related. So
when you talked about the focus groups and surveys, and asked them about would
it be okay if further research was done on the blood samples, did you explain
who would do the research? For example, was it just the Public Health System,
and if not, who did you say would do it?

Similarly, in the ASU case, we talked about the diabetic whose tissue
sample was later used for set-in schizophrenia. Who did that? And did you
mention in one of these cases, maybe it was biobank, that the group who
acquired the information, sold or shared it with other groups?

The third goes into your explanation that, if people are shown the video
that explains what else could we be doing, people really appreciate the
education and probably would consent even in an opt-in case. Do you think that
that kind of willingness extends beyond the case scenarios that you presented?
I don’t remember if that was just case scenarios about newborn screening, or
does it expand generally to public health, clinical research in general, and
performed by whom? So that’s all sort of related, but how much did the folks
that you queried understand the broader context, and how much of your results,
do you think, expand to the broader context?

DR. BOTKIN: We did not address too explicitly the sharing of samples within
the video itself. We had a series of questions on the survey about how much
would you trust different entities to do research in an ethical fashion, and we
had academic researchers, public health, federal agencies and private
companies. And there was a clear pattern where academic institutions received
the highest level of trust, the federal government and private companies had
the lowest level of trust. To use these in an ethical fashion is how we
expressed that question. So I think we, at least in that context, gave them a
sense that there would be potential access by a variety of different types of
investigators to the samples.

The question about whether these issues extend beyond the case at hand. My
sense in the literature is that they do. I think the literature pretty clearly
shows that the majority of people understand healthcare research, are willing
to share samples and data, but simply want that element of personal control
about that. And I do think what our experience was, and I think this is
reflected in the literature, is that you have a pretty solid minority of folks
who are highly concerned about this arena, and have high expectations for
privacy and control. And I think it’s an interesting question in sort of
political science, how you deal with minorities who have strong opinions about
these kinds of issues. But it seems to me the majority is pretty accommodating,
if you engage them.

DR. TANG: So you mentioned that you teased out who do you trust. But when
you asked the question, “Is it okay?” what was their understanding?
Is it okay just for the public health service agency who obtained the original
sample, or is it okay to pass it on to others?

DR. BOTKIN: Yes, good question and we did not ask that. We simply said,
“Is it okay to use this for different types of research?” But with
those questions, we didn’t break that down by would it be okay for different
types of people to do different modalities.

DR. TANG: So considering the context of the survey, chances are they were
saying this newborn screening and by the person who got it? I mean, that’s a
projector.

DR. BOTKIN: Probably.

DR. TANG: But it sounds a little bit like that’s okay.

DR. BOTKIN: Probably. I think that would be a reasonable assumption, but
don’t know.

DR. SUAREZ: Thank you both for just a terrific presentation. I have a
couple of questions for Michelle. I’m fascinated by the degree to which this
population based detail, child BMI data, is being collected in Arkansas. And I
was wondering if you know of how many other states are collecting it this way
across the country? Is this a one-state project at this point, or do you know
of how many other states are doing it?

MS. JUSTUS: I know that there are many other states that are doing it now.
There’s very few that are doing it statewide, so it’s just Arkansas. A lot of
states are doing it just in certain districts or communities, but not
necessarily statewide. I think there are now maybe one or two other states that
are doing it statewide, or are trying to do it statewide. I don’t know that
they’re actually there yet, but there are some that are working towards that.

DR. SUAREZ: Interesting. And then, my other question is about how do the
providers get this type of information. So this is collected by schools and
maintained by the Department of Health, Department of Education, I believe. But
do you share this information with providers, in any way?

MS. JUSTUS: We do not share it with providers. The Child Health Report
that’s sent to parents, there is a statement in there that says, “Seek
your healthcare provider for further assessments,” because it describes
how it’s a screening tool, and that they should really go to their primary care
physician to have further assessments if they’re concerned, and to take a copy
of the letter. And we have heard reports from physicians that some of them are
receiving or having families come in with their report.

We are actually working towards through a whole health information exchange
type system that’s going on in our state. We are working towards having a
student health record at school, which would be, in the best case scenario, I
guess, would be typical to a medical record file, and would then be able to be
accessed by the physical, if there was permission from the parent. But we’re
not close to that, but that’s just something that we’re working towards.

DR. SUAREZ: Great, because that links to my other question, which is, you
probably know under the Meaningful Use Program, EHRs are now required to be
capable of, and providers are expected to begin, capturing BMI in their
electronic health record systems. And so, we’re going to see as we see it into
the future, I guess, hopefully 100 percent compliance of every patient’s
electronic health record having BMI recording and maintained.

And then, of course, we’re going to have this information being collected
on a population basis, so how do you see the two interacting into the future?
You seem to be leaning towards a concept of certainly making that connection
between the school health record and the record maintained by the provider. Is
that your sense into the future?

MS. JUSTUS: Yes, absolutely. We are at the table with the state plan for
the entire state talking together through their electronic medical records. And
so, the school piece is going to be a component of that. The details of how
it’s going to work and all of that are still to be determined, but that’s
definitely something that we’re having discussions and trying to figure out the
best way to do that. Right now, the early childhood population is one that’s
been left out of these assessments, which we also want to include.

And the early childhood children are actually required to have their BMIs
done by a physician, and reported to the State Program Office on Early
Childhood. So we’re working with their office also. It’s a pilot type thing to
see how we can get their data and include that in this, and also provide a
similar report to Early Childhood. So there’s a lot of different pieces, where
we’re trying to figure out the best way to do that here.

DR. SUAREZ: Great. And I have one quick question on the privacy side, and
this is mostly for Dr. Botkin. There is a lot of talk about consent. But
particularly, I haven’t heard too much lately about the role that privacy
boards and IRBs play in deciding ultimately in the case of research, and I know
in public health, public health agencies use also IRBs on privacy boards to
make this type of decisions about obtaining their proactive consent.

Do you have a sense of where privacy boards fits into the perspective of
consumers, and IRBs, I guess, and are they understood well enough by consumers
to be the trusted place where decisions, such as authorizing of the collection
of information for research, without consent or with consent, do they trust
that on those privacy boards? I don’t know if that’s something that you cover
in your analysis and in your survey, but your perspectives on that?

DR. BOTKIN: Yeah, well, part of our project involved interviews with
mountain states newborn screening advisory boards. And these are boards of
interdisciplinary boards, almost always including lay participation, that
advise health departments about newborn screening programs. So we interviewed
all of them in the Rocky Mountain West, specifically about this issue, and it
was pretty clear that they did not perceive themselves to be the public
advocate role here. They had much more participation by clinicians and some
specialists, who were speaking to the more technical aspects of newborn
screening, as opposed to the public perspective.

And it’s pretty clear the public representatives on these boards also had
not been adequately supported or schooled to see themselves as representatives
of the public, as opposed to simply people who might have a wise opinion about
issues to offer for the discussion. Most typically, the lay advocates on these
advisory boards are people who have affected children for PKU or one of the
conditions, and speak from that perspective, as opposed to somebody who’s just
a general public member.

IRBs are, of course, involved in all of the research access to the
specimens, and typically it would be the public health department’s IRB, as
well as the investigator’s IRB, who would take a look at these. And generally,
with the identified specimens, they are not considered to be usually human
subject concerns in this particular domain. Privacy boards, because it’s a
public health enterprise, it may well be that in many circumstances, HIPAA
wouldn’t be involved.

DR. SUAREZ: Yes, it wouldn’t, but in some cases, actually public health
agencies have gone an extra step in saying, “We are not covered entities,
so we declare we’re not, or we’re not considering ourselves covered entities.
But we believe that there is significant value in creating and using privacy
boards, in making our determinations for how to collect and how to use health
information.” And so some state agencies actually have IRBs themselves,
even though they are not covered by HIPAA, but they certainly in many instances
are covered by research regulations that require IRB-type activities.

DR. BOTKIN: So clearly the IRBs are involved. We’ve not heard, at least in
the mountain states region, health departments using any other privacy
protection functions to look at these issues.

DR. SUAREZ: And then, my last question is about there’s an issue of
obtaining the action petition to do it. And then, the other big question and
concern in many cases related to consent is, the longevity of a consent
decision. And so, I wanted to ask you your perspectives on that. I know I used
to live in Minnesota. I lived there for about 20 years, and worked there, so it
has a very stringent privacy regulation that affects actually research and
requires proactive solicitation of consent for research purposes, as well as
consent for disclosures for treatment or payment-related functions.

And the big decision in the state back then was the longevity of each of
these consents. And most common business practices was well, at least once a
year, we will be requesting or asking a consent again to do this or that, the
general kind of open consent to use or disclose data. So what’s your
perspective on the longevity, if you will, of the consent?

DR. BOTKIN: Yes, that’s a great question and I don’t know that there’s been
much discussion beyond the issue of should children who become adults have the
opportunity or should there be a requirement to recontact those individuals,
and get the informed consent of the then adult who contributed the specimens as
a child. I think our focus groups and discussions with participants, they
tended to favor that notion, that you would contact these people after 18 years
and get their permission to continue to store the samples. I think, again,
without much realization of the cost and complexity of that sort of
expectation.

More broadly speaking, I just haven’t seen that much discussion of this
particular issue. I think particularly if you’re using an opt-out approach, you
simply allow that opt-out opportunity to extend, but I’ve not seen
circumstances in which there’s been a formal consent model that has required
repeated positive consents for this type of distributed specimen or repository,
simply because there’s not that frequent contact with the individuals to make
that a realistic expectation.

DR. TANG: Thank you.

DR. FRANCIS: Marjorie?

MS. GREENBERG: Thank you, and thank you to both of our presenters, very
interesting and thought provoking testimony. I had a question for you,
Michelle, and Walter actually asked part of my question, which was whether
there was any direct communication with physicians. And of course, I think
we’re probably both of us had in our mind the experience in New York City with
the hemoglobin with the A1cs. And you answered that and thank you.

I saw, it was on your slide, but we couldn’t see what it actually said, and
that was, “What should you do about this in the Child Health Report?”
And what I’m wondering is, whether this initiative, which is clearly an
impressive statewide initiative, is associated with, and particularly whether
resources are associated with strategies for addressing childhood obesity. As
you pointed out, everywhere throughout the state, there is a problem or an
issue, though in some cases, more than others.

And I guess this would be the longer term research, but whether by if there
are initiatives such as increasing healthy food choices in the school or more
physical activity in the school or some of the other strategies I know are
being used, whether there’s any evidence that, by informing the parents of this
and making this such a visible statewide initiative, there’s more receptivity
to participating in these initiatives or addressing them. I guess it might be a
little early to know that, but obviously at the end of the day, that’s what we
are looking for, would be to decrease childhood obesity. So I’m just wondering
what your experience or thoughts are on that.

MS. JUSTUS: Right. Yes, we actually here in Arkansas have said that we’ve
halted the epidemic, so we’re not continuing to have an increase, which the
rest of the country has. But there are definitely other components of Act 1220,
I just go on the BMI piece of it. But one of the pieces of it is to have a
child health advisory committee, which is a state appointment committee that
addresses those very things in schools. So we have actually done several
things. One is that we have very high nutrition standards in our school for
vending, for a la carte and things that are sold within the school day. So
actually, a lot of the changes that have just been nationally are in the
process of being changed, we have already been doing here in Arkansas.

Another piece of that is that we actually did make recommendations to
increase the amount of physical activity and physical education in our schools.
Unfortunately, because it was an unfunded mandate and schools already have so
much on their plate, a group of people have took that back to the legislature
and actually had that overturned. So we did have increased amount of minutes
for a short period of time, but then, it was actually taken back down, so it
was decreased back to the original state. So we’re having to be creative and
come up with innovate ways to address this issue.

Physical activity and education is one that we’ve really struggled with a
lot. And actually, we have a program that started, I guess, the first year of
implementation has been this current school year. And another group will start
next school year, but it’s called “Child Wellness Intervention
Project,” and it’s funded by the Arkansas Tobacco Settlement Commission.
And basically what it is, is the schools that get this grant are required to
increase their number of physical education and activity minutes from 60, which
is state law for elementary schools and middle schools, and they’re required to
increase that to 120 minutes per week instead of 60.

So we’re starting to do that, we’re also evaluating that project to see
what the outcomes are of that. So we’re doing many different things. We also
have a program, and I don’t want to take up too much time, but we’re also
working on an initiative called Joint Use Agreement, which is funded by our
state through Tobacco Excess Tax Increase. And that is the grant program that
funded to a school and to a community organization to partner together to open
facilities after outside of school hours, for the community to use for increase
physical activity. And we’re also trying to figure out how to evaluate that.
It’s a little more complicated because you have people coming and going, and
it’s not a set group of people to evaluate. So there are other efforts in place
that we’re trying many different things to see what may work.

MS. GREENBERG: Thank you.

DR. FRANCIS: Thank you very much. I think we’ve come to the end of this
portion of the panel. What we’re going to do is take a 15 minute break. And in
the last hour of the day, we are going to be inviting everybody to participate
in thinking about lessons going forward, so we’ll hope that you, Michelle, and
on the phone, I don’t know if that’s possible, and Jeff, could be able to be
around the table later today, as well, 3:00, okay? And a 15 minute break and
we’ll be back at 11:00.

(Break)

DR. FRANCIS: So we have one addition, Seth Foldy from CDC, our liaison,
thank you very much. And I’m going to turn it over to Sallie, who is going to
be chairing this session.

MS. MILAM: Okay, we’re going to start our panel two. We’ll focus on data
management, governance and uses. Today’s been just incredibly exciting, and I’m
looking forward to hearing from the next three individuals. We have Staal
Vinterbo on the phone. Dr. Vinterbo, are you there, are you with us?

DR. VINTERBO: Yes, I am. Thank you very much.

MS. MILAM: Great. And we have Denise Love here with us in person, and
Rosamond Rhodes. I thought what we could do is to let each of the speakers give
us a very brief bio, and then perhaps ten to fifteen minute presentation. And
we’ll go in the order of the agenda, and then we’ll open it up for discussion.
So Staal, if we could start with you.

Agenda Item – Panel II Data Management, Governance
and Uses

DR. VINTERBO: Okay, a brief bio. So I’m a computer scientist by training
and I’m currently an Associate Professor in the Division of the Biomedical
Informatics here at the University of California, San Diego. And by main
interest in machine learning and privacy, preferable in combination. So yes,
that’s a very brief bio.

MS. MILAM: Staal, we’re having trouble hearing you. Are you on
speakerphone?

DR. VINTERBO: Okay, I just turned off the speakerphone; is this better?

MS. MILAM: That’s a lot better.

DR. VINTERBO: I’m a computer scientist and I’m an Associate Professor here
at the Division of Biomedical Informatics at the University of California in
San Diego. And my main research interests are in machine learning and privacy
technology, so that’s a very brief bio.

MS. MILAM: Great, and I think we have our slides up on the screen, so if
you just want to let us know when to advance, we’ll be able to support you here
on this end.

DR. VINTERBO: Okay. Good morning, everyone. So what I am going to be
speaking about today is whether there are limits to privacy preserving sharing
of data. And my main take-home point, if you advance to the next slide,
take-home point, is that in general, a purely technological solution to privacy
preserving sharing of patient data might not be possible. And before I go into
this, why that is, let’s look at the current state, if you advance the slide,
please.

So currently, sharing of data is practically impractical terms done in
three different ways, and this is governed by HIPAA. It’s the complete sharing
of data, including Protected Health Information, PHI, and then there is the
limited data set, which is an almost de-identified data set. And then there is
so-called fully de-identified data. And the two first sharing types require
oversight by IRBs.

And what do we mean by de-identification, and this is specified by the
HIPAA de-identification standard. And this standard has two alternative
formulations, as most of you are aware of, I assume. One is the Safe Harbor,
which demands the removal of 18 predefined information items, all of which are
either explicit identifiers, like Social Security numbers, or can easily be
combined to form identifiers of data subjects.

The other option is, or the other standard option, is the statistical
standard, so called. And essentially, it says that an expert declares that the
re-identification risk in the data to be disseminated is very small. So what
usually is the case is that overwhelmingly, the Safe Harbor standard is being
used currently to de-identify data.

And there are some problems with sharing data currently, and one of them,
if you advance the slide to the next slide headed “Problems”, is that
this IRB oversight is costly. And since the researcher has to write an IRB
protocol, submit it and wait for approval before any research can take place.
And depending on the institutional culture, this might actually be quite time
consuming and painful process.

On the other hand, the institution or the IRB have to process this protocol
and administrate it, so there’s also a cost incurred here. Furthermore, it is
difficult to do this kind of thing across institutions, because they have two
individual IRBs and requirements are such that you have to have collaborators,
and both your collaborator and you have to go through the same administrative
process.

And from a technical standpoint, if you advance the slide please,
de-identification by the Safe Harbor yields data with limited utility. For
instance, geographic information that is specific enough for epidemiology
studies, for instance, is removed by the Safe Harbor requirements. And other
types of limitations and utility of the data that has been de-identified with
the Safe Harbor, has been pointed out in the literature.

And secondly, de-identification by the Safe Harbor does not really prevent
re-identification, so it’s not even sufficient for privacy. And the combination
of these two things is from a de-identification standpoint, the major complaint
these days. And the problem with de-identification by the statistical standard
is that the statistical standard is so vaguely defined. Literally, it says a
person with appropriate knowledge, and then using appropriate tools, determines
that the risk of re-identification is very small. So this type of statement is
so vague that it just doesn’t really lend itself to consistent quantification.
So very few people use this standard in practice.

And one of the main points is also that, inferences about sensitive
information can be made without re-identification. So one can make an argument,
which I will do now, that de-identification, whether you use the Safe Harbor,
the statistical standard or some other type of de-identification formulation,
is not really sufficient for providing privacy that we would like to see, so
called what I like to call “believable privacy.”

And abstractly speaking, this is because de-identification has a
directionality from data to identity, and it is this one-to-one association of
data to the identity that de-identification is designed to disallow. Now, it
doesn’t really say anything about going the other way, so if you know someone
already, you don’t really need to de-identify. And we have to, as an example,
please advance the slide, hello? Okay, I’m still there.

If you take a look at this slide here, many institutions provide a service
for their researchers that allows them to query how many patients that fit a
particular pattern they have in their data repository. These queries are often
called “count queries.” So here is an imaginary example of such a
query interface. And I am querying for how many patients that have secondary
diabetes are of age between 30 and 31 and are male, that my institution has in
its data repository. And I get a count back that says “three”.

Now, to this query, I add that they also have HIV, that they’re
HIV-positive. And again, I get the count “three” back. So now, I
immediately can infer that anyone that has secondary diabetes is age 30 and is
male, also is HIV positive, and I’m not re-identifying anyone. Say my neighbor,
Bob, just told me yesterday at his 31st birthday barbecue that he has secondary
diabetes and he lives right near to the hospital, so I know that he goes to
this institution. So now, I can immediately, because I know Bob, infer that
he’s also HIV positive.

And note that none of these items that I’m querying about, also that are
included in the HIPAA 18 that are supposed to be removed, none of them are
uniquely identifying. And since there are three or “N” that fits both
queries, I’m not re-identifying. I can’t tell who it is uniquely, so there is
no re-identification involved at all. But I know Bob, so this is an example of
this insufficiency.

Now, a point of discussion is, if you advance the slide, please, is are
these insufficiencies of de-identification too isochoric to be of practical
concern. And currently, there is this discussion going on where some of my
colleagues, they claim that, “Well, we think so.” So it’s not really
of a practical concern because usually methods do a little bit more than the
standard requires, and so on and so forth. And the arguments that are presented
are sort of an empirical nature, if you wish.

So for instance, an empirical study, so a re-identification study, sort of,
“Oh, we were able to re-identify X percent.” So now, if this X is
very small and you can sort of try to argue that, “Okay, so this is
comparable to having an airplane disaster happen to you while you’re
flying,” which is very small. And without discussing the ethics of it, you
could say that’s acceptable. But it is not really a valid upper bound because
if you are not able to do this, it doesn’t mean that someone else is not able
to. An argument such that it requires an expert to do this, I don’t think are
really very found.

And the other thing is that, okay, we haven’t really seen media attention
around any problems with de-identified data, so we can assume that nothing has
happened, because it should have, right? If something wrong had been done, then
the media would certainly have picked up if it was a really big problem,
because we see media attention about personal health information being lost and
laptops going all the time. And to this, I ask you to note that breach
reporting exempts de-identified data from a regulatory standpoint. And there
are no tracking requirements for de-identified data. So if you go to a bank and
you are denied your loan application, you don’t really know that it is because
someone re-identified you or identified as being in a cancer registry, and
therefore, you’re a too high risk for this loan.

And what could a possible alternative be, if you would please advance the
slide. So I think of the ideal for individual privacy, note that I’m saying
individual privacy here, is that information is privacy preserving if what can
be learned about any individual is independent of this information. So the
consequence is this, is that we are allowed to share information about the
populations. And also note that this implies de-identification, and also
protects against my example with Bob. And it’s a very strong requirement for
privacy, but it allows very detailed information about the population to be
disseminated. Now, unfortunately, if this independence is taken in a
statistical context, complete independence is not feasible, because this
requires an infinite data set.

If you’d advance the slide, please. But there are some practical approaches
and definitions that go a far way towards this ideal, and one I’m going to
present briefly is that of differential privacy. And this differential privacy
bounds the change in the likelihood of learning anything about an individual by
his inclusion in the data. And it is a property of an information access
method, as opposed to a property of data, and because it is much easier to
prove quantities about methods than it is to prove the properties of data.

And there are access methods to data that provably guarantee differential
privacy. And I’m going to present a sketch of one on the next slide, if you
would please advance it. For this count query problem, basically a blue Bob
here, I have a particular query I’m asking. And the counts I get, if Bob is in
the data set is X, and if he’s not, then I get Y. And the difference between X
and Y is at most one.

And if I add noise to the responses, X and Y, I get a probability of
returning an answer with a density that’s given by these two halves, centered
on X and Y. And the differential privacy is the ration between these at any
point X. And if I use a particular noise that looks very much like these halves
here, then I can guarantee that this ratio is never going to exceed a
particular bound. And this is very important because it emulates, or at least
it approximates, this ideal of independence. And it is provably boundable, so
you can say something quantitative about it.

But of course, nothing is for free, so there is a fly in the ointment, and
here is a very important point, is that this research around this suggests that
there is a general property of a finite privacy budget, meaning that there are
only a few trips to the well of information that you can go before violating
privacy. And this is for the count queries, so if you had noise, you can ask
the same query a bunch of times, and then you can average out the noise and
find the real answer, which is the right little graph here.

And so, if you think about it, every new query extracts a little new piece
of information from your data. And if some of the data that is finite, in a
finite data set, is sensitive, sooner or later, you will start extracting this
sensitive information, so that’s kind of the intuition behind this idea.
Furthermore, the more information you have about your patients, the smaller the
budget is, the fewer queries you’re allowed to ask before you enter this
sensitive area, if you wish.

And this has, for instance, severe implications for genomic data, because
whole genome sequences contain an enormous amount of information. So if you
want to release information about genome that capture its entirety or are
useful for general analyses, you will have a very hard time doing that without
jeopardizing privacy, because of this result.

So how can we deal with this finite budget, if you advance the slide,
please. So one option is to use all the budget up front, and to create a
representation of this information, that you can then ask questions of in
perpetuity. And that means that you’re never allowed to access this data again
in a privacy preserving manner, in order to guarantee privacy, but you can
access the extracted information, though. Different uses might need different
information, so it’s not really the information that you’re extracting by you
spending the budget up front, might not be suitable for all types of analyses.
And as I pointed out, for high dimensional data, such as genomic data, the
budget is really very, very small. So you’re not able to extract much
information.

Or which I think is in general a more feasible approach, or a more general,
at least, is to leverage in the environment in which you allow these queries to
happen, or these questions or data access, information access, to extend this
budget. And the principle is like in medicine, is to substitute some treatment
for prevention. And this treatment could be trust, so you’re sort of not
requiring as stringent privacy guarantees because you trust the person you
share this information with.

And to do so, this trust requires that you to know who you’re sharing the
data with, and that you’re able to detect any misuse of this trust or breach of
trust, and who is doing it, and that you have a mechanism of effectively
sanctioning the perpetrator. And this is more a regulatory question around, for
instance, data use agreements. And I think technology should be developed to
support this kind of process, as well.

So if you advance the slide, please, my conclusion is then that
de-identification, regardless of how you phrase it, as a definition of privacy,
seems insufficient for believable privacy. And current theoretical research
suggests that there are limits to truly privacy preserving, sharing of data,
using technological means alone. And if you advance the slide one more, and I’d
just like to acknowledge my collaborators, funding sources. Thank you very
much.

MS. MILAM: Thank you, Staal. We’ll go onto Denise.

MS. LOVE: It’s a pleasure to be here. My name is Denise Love. I’m the
Executive Director of the National Association of Health Data Organizations. I
won’t have slides, so I’ll speak from my testimony. And I am reflecting that
Utah is well represented here. I’m wondering if it’s a reflection of our
expertise, or that we just want some spring, because the weather has been
beautiful here and it’s been a pleasure to actually visit spring.

Anyway, as Executive Director of NAHDO, I work with states formulating data
collection policy, specifically around healthcare data sets. My bio is that,
well, a long time ago, I was nurse. Then I got into healthcare finance and
manage care policy. I served nine years at the Utah Department of Health,
developing and instituting their initial hospital reporting, HMO-reporting
systems. And now, through NAHDO, I work on the ground with other states, doing
similar work. And so I represent about at least two decades of this work in
data policy.

NAHDO is a non-profit membership and educational association. It was
established in 1986, spun off of the Washington Business Group on Health, at a
time where they were escalating healthcare costs, and purchasers wanted some
transparency and accountability, and I feel like we’re back to the future here.
But NAHDO, since that time, has developed and worked with states as they
advance their reporting agendas. I believe that NAHDO and its members have been
at the forefront of putting large scale healthcare data bases together,
multipurpose or repurposing the data, and also have been at the forefront of
releasing comparative reports to the public on providers.

Today, there are 48 states with in-patient hospital discharge data
reporting. Forty of these states have mandates and operate under mandates.
We’re seeing a new kind of data system emerge, which is bringing up some new
dynamics and conversations, and that’s all payer claims databases. And those
are a little more complex in that they bring in eligibility, medical claims,
pharmacy claims, data into one agency, from public and private payers.

Our members have been linking their data sets with the hospital data sets
with vital statistics, cancer and other registries to fill some data gaps as
they attempt to measure outcomes and population metrics and variation. The
states have long relied on the release of public data sets, research data sets
and interactive web query systems to disseminate the data. Again, these data
sets are state funded largely, there’s no federal funding. So we are seeing
variation in how some of the dissemination occurs on the ground.

So I welcome this conversation. I feel it’s quite timely and I’m pleased to
be here to pick your brains and see where we might want to go, because we are
demanding more of our existing data. And the hospital data and some of the
other large scale data bases are our workhorses, yet, we’re falling short, and
the data are falling short. No single data source that we collect today
captures all the information that we need. These information gaps, as I said,
are being filled through strategic linkages across data sets, but these
linkages pose huge challenges and I’ll talk about that.

So we need to think about how this linkage occurs. We need standards for
how the data are captured in the first place, because we’re seeing some of this
variation inhibit those linkages, and inhibit the integration of the data
across the system. And then, we’re seeing a huge discrepancy in release
practices, by data agencies in states and by data source.

So in this conversation, we believe that lessons learned through NAHDO and
its members can inform future data policies to improve our national information
sharing and infrastructure. The premise is that if we can solve some of the
issues we’re having around administrative data, even out some of these
practices, it is my hope that when we get to that magical time of clinical and
HIE and EHR and whatever you want to call it, we can draw on those lessons
learned and those policies, because it’s just going to make our data exchange
sharing much more complex. I listen to the conversation on BMI and I sat here
thinking, “Yes, there is a hope that the electronic record will capture
BMI, among other things.”

But what happens when we take our administrative data and link to that for
outcomes and cost effectiveness? I think it just explodes. It’s not a single
data set anymore. It becomes a melded data set with the added complexity, so I
think this conversation just needs to happen. So I’ll talk a little bit about
the need for the standards in patient and provide our identifiers, because
that’s causing some grief on the ground. Again, the need for improvement in
data sharing and data exchange, and then some recommendations that we came up
with.

So on the collection side, we absolutely need identifiable data captured on
the front end. Some states have done a workaround by saying, “We’ll
collect the de-identified data from the providers or payers,” which just,
as I call it, neuters the data up front. So what you’re going to do with it is
limit it from the get go. I understand politically and legally why that might
happen, but we really need to capture the robust identifiers at the front.

Even when the states are collecting these fields and data sources, we’re
finding different formats. The same data sets vary in the formats across states
and jurisdictions and data sources. Again, that hinders the analyses, linkages
and applications. One example that I’ll bring up is, many states with their
hospital data, have relied on Social Security number of the patient, as one of
the identifiable fields. Again, I call it the “demographic suite of
fields,” of patient fields.

The Social Security number, when combined with the date of birth and the
date of admission, date of discharge and gender and some other fields, it does
create a unique record. But now, we’re hearing from payers and providers that
they are no longer asking for Social Security number, which wasn’t perfect to
begin with, but it will just diminish the availability of that field. So
compounding that, then you have many of the discharge data systems where
concerns of privacy never collected in the beginning, patient name or patient
address. So as the Social Security number drops off, what’s there to replace
it?

So when we advise with states, they could back and change their rules and
say, “Now we have to collect the patient name.” The problem is,
having that conversation with legislators in this day and time poses huge
risks. So that we find ourselves sort of punting at this point. And then, if
they do collect it, we’re finding these names and formats vary. Cancer
registries do not equal discharge data fields, and again, the linkages are a
little noisy when you start linking with registries to say, “Define an
episode of cancer care,” and look at other outcomes of interest.

So if we can get address in hospital data or in another public health data
set, and we’re lucky enough to do that, what we’re finding is that they’re
capturing often just one field. But that may be a P.O box in a rural area,
which doesn’t help with our geocoding. So distinguishing between the patient’s
billing or mailing address and their residential address where they reside is
important for exposure, analysis and other types of geocoding. But again,
having that conversation with legislators is a little prickly and a little
tricky right now. Then if we have the cleaner data, then we can get smart
de-identification and encryption and algorithm, and that is our hope, but we’re
not there yet.

Then, we get to the release aspects of data. So even if you have a
perfectly captured data set that’s identifiable, and you have all of the unique
fields and you were able to get address, that data is not being shared, or not
being shared very well, even with a public health department. Because of
sensitivity now, you’ve added power to your data set, you’ve got say the holy
grail of the patient demographics in your hospital data set, for example. Well,
that just means that maybe you’re not going to share it with anybody, or very
few people. So we’re seeing this lockbox mentality of, “We’re going to
keep it under lock and key until we figure out what to do with it.” And
this is where I’m going with this, we aren’t figuring that out very fast. But
NAHDO gets quite a few calls from agencies who want to share the data.

Now, you could say IRB, it could go to an IRB, but not really, because some
of this linkage in public health departments isn’t bona fide research. I mean,
these are enhancements of data bases, and some of the applications for
evaluation are gray areas, so not bona fide research. So it is pretty uneven,
some states have figured it out and others have not. There may be legal
restrictions, as well, in the state, but I maintain that most often, it’s fear
of what could happen if the data are shared, but also lack of resources. Many
of our data agencies don’t have any more people, and then the light is barely
on. And these kinds of data sharing initiatives are hugely intensive, in terms
of workforce and figuring it out across the system.

MS. MILAM: And you have about five minutes, please.

MS. LOVE: Okay. Many agencies do deploy statistical and management controls
to release their anatomized data. We are seeing the one-way hash encryption
that some states have applied and have been using for some time. All states
will aggregate their fields, such as dates, and I won’t get into the
mechanisms. We feel that these de-identification methods in play in most of the
states that NAHDO works with have proven to be an effective first line of
defense to protect patient identity.

When combined with data oversight, data use agreements that stipulate
authorized uses, I think the states have created a workaround around some of
the issues. But still, we can do better and we must do better as we try to
repurpose our data and get more utility out of it for the public’s good. And I
won’t even bring up FERPA and health and epidemiology, that is for another
time, another place. But that’s a classic case where you have this huge silo,
but a huge need to share with the public health department.

So again, we’re seeing a huge amount of variation and practice, and we’re
seeing huge gaps in information about populations, and we think that we can do
better. So NAHDO welcomes a national discussion, led by this committee, around
these complex issues. We would like to see greater cooperation across states
and data sources. And we need to maximize utility of existing data because
we’re not going to get too many more data sets funded and collected in this day
and age.

So we need messaging, we need, and I heard that earlier today, policy
makers and the public, what is the message? What is the utility? What’s the
value proposition? Why are these fields important? How do they help the public
good, because society does benefit, and so we need a consistent and deep
message. We need to encourage states and others to have uniformity and
consistency of their demographic fields across the public data sets, in format.

We will be watching HITSB and what they’re doing with the demographic
model. We know that some of the new names are long and hyphenated, and some of
the existing standards don’t accommodate those fields. One of the examples that
we brought up is a project underway by CDC and the National Program of Cancer
Registries and NAHDO, and we’ve been harmonizing the discharge data bases with
the cancer registry databases. In some cases, the hospital systems will change
their standard and sometimes it makes sense for the registries to change
theirs. But the belief is, harmonization across these data sets will facilitate
linkages of cancer registries and hospital data sets, and it will reduce
provider burden to report.

I don’t think we have time to get into the huge issue of provider
identifiers, but that is another kind of linkage and standard problem that’s
wreaking havoc, as states try to drill down in their data and assign
attribution to the provider and to the physician, and messaging around the
importance of a unique number is critical. We believe that de-identification
will continue to play a huge role in data exchange, but we need smart
de-identification. We need expert panels to help us define an analytic
framework, that puts some sort of intelligence into the de-identified data sets
that are linked. For example, if we could do a better job at the hospital
discharge data level, by having the data agency that has the raw data add smart
flags. This was a readmission, this was a readmission to the same hospital, you
wouldn’t need as many linkages. You would have some intel embedded into the
data set, and you could send a de-identified data set out the door, without
having to have the specific identifiers on that in every case.

So we also need to redefine or rethink how we talk about PHI. PHI is
changing, as the field of genetic and biosignature data expands, and we see
more sensitive data. And so, some clarity is what it is, what it is not. Other
messaging information, model exchange policies come up because we are not doing
a good job in exchange. And so, we really need to make it a guidelines or some
sort of best practice, and highlight how it works and what the benefits are.
We’re seeing that geocoding enables us to connect the dots, but this added
power creates heartburn because people are worried that it will identify the
patient, and it does inhibit data exchange.

We have some legal problems with interstate transfer and jurisdiction
exchange of data because again, a readmission in Maryland needs West Virginia
data to really look at those readmission rates, but the legal prohibitions and
political concerns inhibit those kinds of exchanges. Again, I sometimes think
of PHI as we mix up the clinical world, so where there’s a clinical end point
and an intervention, you absolutely need that patient identifiable information.

NAHDO and its members and the users of our database really use anatomized
data sets for statistical and research. We need to know it’s an unique
individual, but not who that is. And sometimes, I think those conversations get
blended together. So I offer NAHDO’s expertise in the field to join this
discussion, and think of ways we can enhance our data sets. As we see, all
payer claims databases take off the issues of identifiers, de-identification,
methodologies for encryption are just adding more complexity, and that isn’t
even counting all the clinical data that is about to be merged out there. So I
will conclude my testimony, and thank you again.

MS. MILAM: Thank you, Denise. Rosamond?

DR. RHODES: Okay. So a little bio, I’m a philosopher at Mt. Sinai School of
Medicine. I’m Director of Bioethics Education. I teach our annual Research
Ethics course. I’m also Professor of Philosophy at CUNY Graduate School and
Professor of Bioethics in the Union Mount Sinai Bioethics Program, where I’m
Associate Director. So recently, I’ve been working on an NIH project on the
human micro biome, and privacy and confidentiality have been big concerns for
us. So I’m going to approach this issue a little bit like a philosopher.

Okay, so privacy. So what I understand it, privacy is a concept from
ordinary morality, common everyday morality, and it’s different from
confidentiality. Privacy identifies areas that are safeguarded from the
scrutiny and intervention of others, and it’s marked off from public space by
natural boundaries. It’s protected from the intrusion of others by laws, social
practices and social sanctions. So domains of privacy are things that are
separated by natural boundaries, so what’s in my thoughts, what’s inside of my
body, what’s inside of my own bedroom, what’s inside of my home or my computer
or my mail, we could go on and on with the list.

Now, privacy and common morality is a protection, but it’s not an absolute
protection. It’s primarily a protection from unwanted government intrusion, and
exceptions from privacy protection are allowed for the sake of the public good.
So we do allow the police to break into your house if they think something
nasty is going on that violates serious laws. They might even be able to search
your bank accounts and other records for the public good or public safety.

Now, aside from this protection from government intrusion, the task of
maintaining my privacy is largely left in the hands of individual citizens. So
privacy, in common morality, is not a guarantee, except it’s a standard of
protection against the government. And if you think back to movie pictures I
liked, “Rear Window,” the Hitchcock movie, you see people looking
through the windows that other people leave unguarded. If you want your bedroom
kept private, close the curtains. If the windows are open, people are welcome
to look in, and nothing terrible is done.

Now, this picture is not a mistake. It’s actually, I think, my most
important slide. So if you think about children riding bicycles, if you want to
protect your child from harm, what would be your bicycle riding policy? So if
you really want to protect children from harm, you might think they have to
wear helmets, they have to stay on the bike path. They shouldn’t go riding
alone, they should go in company. But you know, they can really still get hurt
if they wear helmets or if they’re on a bike path or even if they’re in the
company of a parent. So if you’re really serious about protecting the child
from harm, you’re going to say, “No bike riding.”

Now, if that’s your policy, “No bike riding,” you can then ask,
“Is that a good policy?” So a good parent, I think, encourages their
children to ride bikes because you want the child to learn other things. You
want the child to learn to explore the world, to socialize with other children,
to manage risks. So for a good parent, you provide safeguards, but you
recognize my child could be hurt physically, but we get these other benefits.
And I think good public policy, with respect to anything, has to balance the
goods with the harms, and come up with a reasonable course that navigates both
of these concerns.

So important questions are, “What would be a good policy? What would
be a reasonable policy?” So when you come to protecting privacy, such as
HIPAA rules or absolute guarantees of no breaches of privacies, you can ask,
“Are these protections reasonable or unreasonable?” And failure to
take into account of other reasonable and legitimate social and personal goals,
I think, is being unreasonable. So when we collect data and mass data sets, of
course, somebody could be re-identified and they might not like that. They
might choose otherwise. But I think in constructing our policy, we want to
consider real important social and personal goals, like advancing science or
protecting people from harm.

And it’s also important to point out that when we say we must absolutely
protect privacy, we are being paternalistic. What I mean by that is we’re
saying, “This good of privacy trumps everything else. Forget about
everything else and I’m going to protect you, whether you want to or not.”
Now, Madison Powers at Georgetown calls this kind of paternalistic attitude
towards research “Marxist” because big brother knows what’s good for
you and is protecting you. And I’m suggesting, with Madison Powers, that this
paternalistic protection of privacy is unreasonable and also unjust.

So if you ask me personally, I may not care a great deal about protecting
the privacy of my samples. At my institution, we have a biobank and I have
signed up for it, and what they say at the beginning is, if you sign up for it,
we only accept people who have a medical record ID. And that medical record ID
is going to be linked with your biobank sample, and it’s going to be used in
research. We don’t know what it is, so we can’t tell you what it is, and we’re
not going to ask you about it again. And you can always withdraw your unused
samples, but not your used samples. But if you want to sign up, we’d really
love to have you. And we even offer an incentive, I got 20 dollars for signing
up.

So I don’t care about people using my samples. In fact, I care a lot about
I want it used as much as possible, because I want the researchers to find out
about people like me, so what they can find out might help my children and my
grandchildren. So I may care more about advancing biomedical knowledge than I
do about the absolute protection of my privacy. And I may care most about
helping my fellow man.

So confidentiality; so as I see it, confidentiality is a concept from the
professions, and we see it occur in the priesthood and the law and medicine.
And confidentiality is especially important because it relies on the ethic of
those professions, and it gives people a reason to trust that the information
that they share with these professionals will be kept sacred and shared only
within the profession. Now, think back to the cartoon diagram I gave you about
privacy, and you’ll notice the difference. So confidentiality identifies a
space for professional interactions, where privacy is safeguarded from the
scrutiny and intervention of others, and it’s marked off from public space by
constructed, non-natural boundaries.

So if somebody comes into the emergency department, they’re going to be
examined by the residents and the medical students and reported to the
attending in the emergency department, and then they might be sent up to the
floor, where they give their history to the physician who greets them. And that
information is communicated with the whole team of residents and attendings and
nurses and all kinds of other specialists, and to the pharmacy department, and
the things will go for special tests and there might be surgery involved. So
when we’re talking about confidentiality, it’s not two people knowing this
information like in privacy. It’s shared broadly and that sharing could go on
through many buildings and many different spaces. And I think it’s important to
notice this difference between confidentiality and privacy. These are different
concepts and we’re very comfortable with accepting confidently in medicine.

So the question is about handling of research information. Should it be
handled according to standards of privacy or according to confidentiality? So I
think these concepts need to be distinguished from each other, and in the
treatment and biomedical research, information about people should be treated
according to existing standards of confidentiality that govern other medical
information. For example, information in treatment needs to be shared with a
whole array of people on a need to know basis. And I think the same should
apply to research. So participant and public safety, as well as providing for
the public good, may sometimes be more important than privacy.

So again, we can ask the question, do we want standards of confidentiality
or standards of absolute privacy guiding research? And I think we’ve come down
on the side of confidentiality, because confidentiality is already the
prevailing standard in a lot of research that gets called by other names. So
when we get the common rule, they carve out certain kinds of research that
doesn’t get called “research,” and there, we use standards of
confidentiality and it works very well. So all public health surveillance, if
somebody comes into my hospital and they have SARS, it gets immediately
reported to the Board of Health, with all kinds of identifying information
because public health people need that information to track it. And we don’t
ask them for their informed consent before we share that information. It’s
necessary we do it and we accept it. It’s also done standardly in hospitals and
we call it “quality assurance” and “quality improvement,”
and we do it with registries, as well.

So in all of these circumstances, there is largely no objection, and also
we already trust these agencies to uphold standards of confidentiality. Now, in
one of my activities at Mt. Sinai, I’ve been involved in some research from the
Emergency Medicine Department. These were studies called “Voices One”
and “Voices Two” about community attitudes towards emergency
research. So this is research that’s done under the final rule, so research
without informed consent. So it doesn’t look exactly like what we’re talking
about, biobanks and sample banks and large data banks. But there is the
similarity that here, you’re talking about research where informed consent
cannot be done. And our study was specifically focused on “What are
community attitudes?” So we ask people “If, because of some health
emergency, you can’t give consent, who would you trust to make decisions for
you?” And people said, “I want to decide for myself,” and we
explain again. “Well, what if you couldn’t? What if you were unconscious?
Who would you want to decide for you?” And they would say, “My
daughter, my son, my husband, my loved one.” And if you explain,
“Well, we couldn’t contact them. Who in your community would you
trust?”

And we did this in multiple focus groups and then in large surveys, and
people said not what you’d expect, not the clergy, not their political leaders,
not their neighbors. The people who they said they would trust most would be
health professionals. “I want health professionals making these
decisions.” And if you look at public health surveillance, well, then the
Board of Health makes decisions about when should surveillance be done, what
information should be gathered, who should get it, and we trust that this is
largely done well.

When you talk about quality assurance and quality improvement, you have
again boards in the hospitals of professionals making these decisions according
to the ethics of medicine. And when you talk about registries, they are largely
overseen by professional associations who are trying to collect information on
whether this new hip replacement device squeaks or has other problems, and they
want to track it. And virtually everyone is involved in these data gathering
activities. It’s all research, meant to guide future practice, so it is
collecting knowledge to be used for others.

MS. MILAM: Rosamond, you have a couple of minutes left.

DR. RHODES: Okay, I’ll go fast. I’m almost done. And we do it without any
serious discomfort. So we’ve already talked about the need for widespread
research participation, in addition to the general gathering data about
obesity. We have on the horizon, human micro biome research, genomics, the
promise of personalized medicine, and there are these new research techniques
that will facilitate research that we couldn’t have done before, so we want
widespread participation.

And up to conclusions, so I’ve been arguing that when medical
confidentiality is upheld, in medical treatment and research first, people are
not harmed. And also, we should consider if we’re thinking about harms and
benefits, people are not harmed on the one side and you can get significant
public good. And then, if you keep the desired benefits in mind, then with
appropriate confidentiality limitations, data from biobanks and sample banks
should be shared in order to significantly increase the research use of
samples, identifying information should be limited to reflect the need to know,
including the need to recontact people.

And where possible, and with informed consent, when samples are taken,
material remaining from clinical uses and other research should be available
for additional research purposes. And when informed consent is not available,
there should be something like a process of consent, which is an institutional
system, a board of professionals that meets and says, “What information
should be shared, when and how and when it’s appropriate?” And I’m done.

MS. MILAM: Great, thank you, Rosamond. Staal, are you still with us?

DR. VINTERBO: Yes, I am.

MS. MILAM: Wonderful. We’ll now open it up to questions for all three
panelists. I’ll kick it off with just a quick one for Denise, and then we’ll go
around the room, we’ll work the table. Denise, I’m wondering about your
recommendation around guidance for data release and data exchange at the state
level. I’m aware that NAHDO and others have inventoried and produced reports
around different statistical disclosure methodologies, to de-identify or
otherwise protect the data.

But is there guidance out there for states and public health who generally
aren’t regulated by HIPAA, that would tell them, guidance, how to select their
methodologies, which methodologies to use, when is it adequate, when is enough
enough, what data features can be released to this group versus that group? I’m
wondering if there is anything out there that people can point to, and if there
isn’t, do you see a need for it?

MS. LOVE: There is nothing formal out there that I’m aware of. States share
with each other, so the best practices are pretty good practices arising to the
top, just through state to state sharing. But there is no formal, “This is
how you de-identify a data set and methodology,” and there is a great need
for that.

MS. MILAM: Do we have other questions? Leslie?

DR. FRANCIS: Yeah, I want to address this to both Staal and Rosamond
actually, which is in a way I think the two of you have somewhat similar
conclusions, namely that de-identification isn’t the way to go and that the way
to think about protection is governance of data uses or misuses. So when you
talked about dealing with a finite budget, detection of misuse, and when
Rosamond talked about limiting to reflect the need to know.

What I’m interested in is, if you have further thoughts about either how to
detect misuse, what would count as misuse. For example, the Havasupai thought
it was misuse to have given their data for one reason, and then to have it be
used for a different type of research. And what kinds of mechanisms there might
be with respect to misuse prevention. This is all at the level of, we’re not
talking about individual opt-in, opt-out, the data are there. What we’re
interested in thinking about is, how to either decide what counts as misuse,
detect it or prevent it.

DR. VINTERBO: Do I start off?

DR. FRANCIS: Sure.

DR. VINTERBO: So this is a very good question, and I think it hasn’t been
really answered. And if you think about detection of misuse, for instance,
there are examples, as you pointed out, with the use of the data. This is
fairly easy, well, in my mind at least, there might be things I’m not thinking
of, but there are instances where this is easy to detect, because you wrote in
your IRB that you were thinking of doing this, and you’re now doing something
completely different, and someone can detect that.

However, if you think of it in a context of the query to a database, and
the example that I gave with this mechanism that allows you to question or
query how many patients you have, the detection of your intent behind these
queries and the actual information that you could actually distract from, a
combination of queries, in the general case is undecideable from a theoretical
standpoint. You cannot really tell what your intention was and what information
you can compute out of this. So in this sense, it’s a little bit of a
pessimistic result, so this is the worst case. But I think arguments can be
made for this kind of auditing for data use, that there are at least mechanisms
that can allow you to filter out sort of use outliers, if you wish, sort of
unconventional uses of information that could be audited by a human, that can
make inferences that machines cannot do.

And so in my talk, I was limiting myself to sharing of data. I think there
are ways of doing research where what you share is not data, but it can be
information they aggregate that is extracted from a local context, and are then
composited into a result that couldn’t be derived from any single local
context, so a sort of a multi-party computation, if you wish. And the extreme
of that is sort of a very secure multi-party computation. And but this lists
the extraction level, either up into sort of an informational realm and you’re
not sharing data anymore. Or you implement computational mechanisms that do
provide privacy guarantees, while at the same time allowing computations to
take place that employ all the information available, but not sharing it.

So but these are still fields under development and are not ready for
employment to prime time, but this is kind of maybe something maybe we should
think about when going into the future. So for the present, I think you are
right that Rosamond and I share this view, and I unfortunately don’t have a
very clear technological answer on how to address the detection of misuse. And
I think it has to be considered in specific contexts of what mechanism you use
to access data, and how that can be audited and so forth. Thank you.

DR. RHODES: So I agree that it sounded to me as if Staal and I were very
much on the same page. And also the focus of trust, as being the primary
grounds for protection and also procedures, structural processes. So in our
biobank, for example, we have two levels of oversight. So first we have a
community board that includes physicians and people from our different
populations, and a subcommittee of that is devoted to the biobank. And every
project that wants to use the biobank not only goes through the IRB, but goes
through the community board for the assessment of the appropriateness of the
study, so that approves the study.

Then there’s a separate only professional group that reviews the study and
decides which information should be released to the researchers. So there’s the
biobank sample, the genetic DNA as a sample or as just the data, and then it
can be linked to the medical record, which gives you a great deal of
demographic information, and they’re deciding which of this demographic
information is relevant to your project. Nothing is off the table, it’s all
available, but you have to demonstrate that you need the information.

Now, in terms of illegitimate concerns or illegitimate uses, my ears perked
up when I saw the words on the paper. I perked up about the Social Security
number. I can’t imagine any need to know, the Social Security number in
particular, and then even if it facilitates research, I think there you have a
big danger of people’s identity has been stolen, and it has gotten them into
huge economic problems. So I’m really concerned about the Social Security
number.

And in our micro biome research, what has come out again and again is the
concern that people have that their research information will be shared with
law enforcement or immigration. In our community, there are a lot of people who
could be illegal immigrants, and while they’d be eager to participate in the
study, they’re concerned about who gets it. And our biobank is supposedly
subpoena proof. They’ve filed a certificate, but I think we need a national
assurance, a real bright blind barrier to protect research information from
being shared with law enforcement and immigration.

MS. MILAM: I have Walter and then Paul. Walter, did you have a question? I
couldn’t tell.

DR. SUAREZ: I think Paul went first.

DR. GREEN: Sallie, would you add me to the list?

MS. MILAM: Sure, got you, Larry.

DR. TANG: Thanks, very interesting panel again. I’d like to sort of compare
Rosamond’s presentation with Jeff’s around this whole consent and use for other
purposes, because I think you had sort of somewhat contrasting views.

DR. RHODES: I thought we were on the same page.

DR. TANG: So you used the word “paternalistic,” and the way you
used it was, you didn’t want somebody to say you couldn’t do things from a
privacy perspective. You could almost flip that and think paternalism could
also mean we to somebody and this guy will decide how we will use your data. So
it’s interesting you could actually have two different authoritative ways of
looking at someone else making a decision for you.

What I thought was interesting about Jeff’s presentation was, you know
what, actually the majority and the super majority of folks, when given
information which satisfied their need, their desire to have choice, and still
yet contribute to public good. And that’s where I saw your paternalism said,
you know what, we really need to use this information for the public good. And
really not necessarily, I thought I heard, we need to check with folks.

Now, you talked about why the use of your individual tissue could help
other people like you. What about, and how do you reconcile this, if studying
your tissue sample informed others about other people with similar tissue
samples, that could be used for whatever those other people want it to be used
for. It could eventually come back, and Jeff talked about the group risk in
underwriting, for example, or in other things that may come back to harm the
other people, even if it’s not you. How do you figure that into the thought and
your description of paternalism in how people should be doing some of these
things?

DR. RHODES: So my understanding of paternalism is what a good parent does,
through acting for the good of another, even when they don’t want you to do it.
So when I’m taking this information, my information, when I come into the
emergency room with SARS and it gets reported, that’s not for my good, that’s
for the public good. So it’s not an instance of paternalism, it’s a different
principle. It’s justified by the public good as opposed to, “I have to
protect your privacy, that’s for your good.” So I’m distinguishing those
concepts.

And I think making privacy protection so vigorous is paternalistic because
what you’re saying to everyone is you really want your privacy protected over
and above everything else. And I think Jeff’s data shows that, while people
like to be asked and like to be participants in the decision making, when it
comes down to it, what they care mostly about is, if my child has a problem, I
want to protect my child. And if you can learn more things to protect my future
children, my neighbor’s future children, stranger’s future children, I think
it’s a good thing and it’s worth doing, even if I don’t get to consent. So I
think these are slightly different concepts.

MS. MILAM: Walter?

DR. SUAREZ: Yes, thank you to the presenters, fascinating discussion on new
areas in privacy and confidentiality, I suppose, or same areas looked at from a
different view. I wanted to create some distinction. It seems to me that we’re
mixing a number of aspects, and I wanted to separate two important areas,
because I think privacy and confidentiality, even though it applies directly to
them, they apply a little differently.

One is public health, and public health has functions and responsibilities
and activities that are completely separate from the other activity, which is
research. And I think we’ve got to look at the two and we’ve got to look at the
elements around privacy, the collection of data in the first place, and how
public health and when and why and where and all those things, can public
health collect data. And then, the same concept around researchers. And they’re
different, because I think it’s important to distinguish them because I think
that public health responsibilities are quite distinct in reality, and are a
community good that is also important, as well as the research side a community
good. But it’s a different type of community good, if you will.

And then, the other element in my two-by-two is the release of information
or disclosure. And so, public health ability to disclose information, whether
it’s through reports into the public or into entities that identify whether
it’s population groups or individuals, as in providers or systems or whatever,
never really identifying individual patients certainly, or consumers. But that
disclosure function and release function is different from the research side,
too. And so, I wanted to explore that distinction in your minds, in the three
of you, the presenters, because I think when we talk about privacy and
confidentiality and those concepts, and we try to bring them together and link
them in public health and research particularly, it creates some confusion, at
least in my mind. So I wanted to explore that distinction and see if you agree,
there is an important difference that need to be taken into account when
defining policies around privacy and confidentiality, how they apply to public
health versus research.

DR. RHODES: I can talk about it, because I was the one who challenged the
difference. So we get this sharp line coming out of the common rule. And I
think conceptually, there is not the sharp line. So first, the focus of public
health, everybody says, is the public, and everybody says the focus of
treatment is the individual. Not completely. So when you have a lot of patients
in the doctor’s office, and one of them is coughing, you worry about the
others. And in the hospital, we make decisions that are not always for the good
of the individual, who gets into the ICU, who gets out of the ICU, who gets put
into a room with special airflow because they might be contagious. So we’re
making these decisions in the context of treatment, with regard to the bigger
public.

And in public health activities, we’re also focused on the effect on the
individual of a policy. So Typhoid Mary, we all know her name, and she got put
on that island because she posed a risk to others. And when we have contact
notification programs, we take care to protect people’s confidentiality, even
though it’s not absolute. So there’s a constant balancing by public health, as
well as by clinical medicine, both the public and the individual. It’s more
common in public health, less obvious in treatment, but I don’t think there’s a
sharp difference.

Also, when you talk about these activities like surveillance, what is your
goal? Your goal is obesity screening, whatever it is, your goal is an
intervention and you have a hypothesis. Obesity leads to shorter life
expectancy, other health problems, or whatever the hypothesis is, you start
with the hypothesis and your method is collecting data in order to reach a
conclusion and decide what to do. And we do that in clinical medicine, we do
that in public health. I don’t see a marked distinction, and I think that there
are a couple of sharp lines that get created by the common rule that
conceptually make no sense. The difference between innovation, doctors can try
an FDA-approved drug for any new use. Bless your heart, you’re free to do it.
But if you want to study it and learn something, then you have to go through
all of the rigmarole that we all know.

Now, is there a sharp distinction? I could tell you story upon story, where
you’ll see that distinction gets blurred, because when the doctor has the idea
of helping this patient with this intervention, there’s a hypothesis. This is
just speaking very generally, and you’re going to observe what happens and try
to draw a conclusion from it, and that conclusion is going to guide your future
treatment of other patients, and it will guide what you teach the residents and
the fellows and the medical students.

MS. MILAM: I’m going to have to cut you off, Rosamond, I’m sorry. We have
two more people to respond, and Larry has already indicated he has a question
and we have five minutes. So with that said, Denise and Staal, do you have
anything that you want to add?

DR. VINTERBO: Yes, really briefly, that I think we often need to
distinguish between the clinical care and research. And I agree with the
questioner’s assessment that there is a distinction between disclosure for
public health and disclosure for research. And I also would like to comment
really briefly on Rosamond’s sort of analogy between, or a statement, that
privacy is only for protection against government, which I don’t really think
is necessarily true. And yeah, that maybe confidentiality could also be viewed
as a mechanism to provide privacy, and this seems to be how it is being used in
the professional context that she outlined. So yeah, that was very brief. Thank
you.

MS. MILAM: Denise?

MS. LOVE: When it comes to making data policy, it is very important for the
states to distinguish between collection and release, and we are very clear
that they should not really be lumped together. So you collect very detailed
information, be it Social Security number, and we could talk about that all
afternoon, but that does not get released. And so, those policies have to be
clear.

MS. MILAM: Thank you, Larry? Are you still with us?

DR. GREEN: I’m sorry, am I there now?

MS. MILAM: You are.

DR. GREEN: Sallie, I was saying that I’m sitting out here, really
struggling, with trying to consolidate this very productive morning and these
great presentations, and to sum up these conclusions that align with the
jurisdiction of NCVHS and the interest of our subcommittees. And what I would
like to ask your indulgence to do is, I’m going to try to make up right now a
couple of sort of sum up these statements and invite the three presenters to
correct them in dissent from what I’m about to say.

It goes something like this, what I’ve been hearing is that we have an
emerging world of health-related information that has already exposed weakness
and insufficiencies. And the current law, the current rules, current
regulations, current typical practices of insurers, payers, and doctors and
researchers. And that this exposure has actually compounded challenges that
were already large, to properly protect individuals and populations from harm,
from health information, and sharing it, something like that. And that we’re
being presented with something that I would call nearly a stunning opportunity
to reexamine both individual and population health information use, and that
we’re at a juncture in the country where it is really urgent to reexamine and
consolidate a sensible approach to privacy and confidentiality.

So I need to stop here, hold that meandering in your thoughts, you three
presenters, if you can, and I have a much simpler other summary conclusion from
the morning, and it would go something like, “There is no sufficient
approach resolving these confidentiality and privacy issues, using a purely
technological solution.” I’d like for you guys to disagree with those.

MS. MILAM: We’ll start with Denise and then we’ll go up to Rosamond and
then we’ll end with you, Staal.

MS. LOVE: I agree that we are exposing weaknesses and insufficiency with
our current practice. There is a risk to populations, but I less agree, because
I think from in terms of public health and state law, they’ve done a remarkable
job with the protection, and I don’t want that to be lost in the discussion. I
just think we can do better. And I don’t think technological approaches alone
will solve the issues. I think it’s much more sociologic and complex than just
the technical solutions alone, so I agree.

DR. RHODES: I think we have already been treating a lot of our research
data as under guidelines of confidentiality. And I think we do need to
reexamine some of our research rules that make people jump through hoops to
call to either anonymize data or to call it something other than human subject
research, when they’re talking about biobank and sample bank data.

MS. MILAM: Thank you. Staal?

DR. VINTERBO: Yes, I agree with Denise and also the statement made by the
questioner. But I would sort of be a little bit cautious and say that just from
a technological standpoint, I think the sharing of data is problematic. Whether
this also applies to sort of the more aggregate sort of information content,
that probably remains to be seen and I think there is a large opportunity for
technology to help where sharing of data might not be possible. Some other form
of collaborative mechanism can be used, so but yeah, I agree.

MS. MILAM: Thank you. I want to conclude with thanking our panel. Your
presentations were fabulous and the discussion was really, really interesting.
We’re at 12:35. We’re going to break for lunch now and we will reconvene here
in one hour. Thank you.

(Whereupon, a luncheon recess was taken at 12:35 p.m.)

A F T E R N OO N S E S S I O N (1:30 p.m.)

DR. FRANCIS: This is the third panel. Have we got people here on the phone?
Maybe we can ask the people on the phone to introduce themselves?

Agenda Item: Panel III –
Communicating Results

MS. MEREDITH: Well, there are three of us in this room. It’s Janet
Meredith, 2040 Partners for Health.

MR. WARE: George Ware, Taking Neighborhood Health to Heart Co-Chair.

MS. STEWART: Tracy Stewart, Board Member 2040 Partners for Health, and Food
Subcommittee, Taking Neighborhood Health to Heart.

DR. FRANCIS: So we have really two groups here that are going to help us
talk through the question of communicating results. And we have Debbi Main, who
is here as the fleshly representative of the Colorado Group, the distance
representatives are on the line and have introduced themselves. And we also
have Kathy Alexis, who’s the Clinical Quality Initiatives Manager from the
Community Healthcare Association of New York, who is with us here, great.

DR. MAIN: Well, I don’t even have to introduce my team now because they
introduced themselves. But you guys can’t see it on the phone, but George is
right here in this picture, and there’s Tracy in the picture. So Tracy, they
can see at least the two of you. Janet, you’re not in this picture. But thanks
for coming back from lunch. I appreciate it. I was, like, “Oh, man, this
is risky.”

So in fact, you have our bios, but this is just listing and I know each of
our team members on the phone actually talked about their role in this project.
So I was originally the Lead Principal Investigator on it from the University.
Janet is the Executive Director for 2040, and Tracy and George actually live in
our neighborhoods, so that’s how this whole thing started. In fact, George, I
told the story earlier about you as a skeptical person living in a
neighborhood, who wasn’t sure if CBPR, Community Based Participatory Research,
could actually work. So George joined us so that we could prove it to him, and
he’s still with us, so I think that’s probably a good sign.

So I was sent questions. In fact, Maya sent some questions to us about the
questions about confidentiality and some other things. And basically, I think
we’ve sort of addressed the questions, and I hope that this presentation is
sort of framed to help you answer the questions. But our basic premise is just
this: that we believe that enhancing confidentiality, trust and relevance of
community-based health information is best addressed early. And I should’ve
actually underlined that phrase “early.” We believe it’s best
addressed early and in an ongoing, meaningful way. And then, I’ll talk a little
today about this, but by actually engaging people who live in the
neighborhoods, and I’ll talk about our project where we’re doing very local
level data collection and dissemination.

And so, really involving people on the ground in designing sort of your
data collection methods, interpreting findings, thinking really clearly about
how to get the information out in many ways. And then, I think this is a
critical piece, too, for us is that using data to develop the next steps. So I
think the point of use is really important, as well.

So what we’ll do during the presentation is, first of all, just talk about
some of the challenges we’ve encountered in a project called “Taking
Neighborhood Health to Heart,” and then how we’ve addressed them. And
then, I really want to talk about primarily some of the methods and processes
we’ve used to get really data findings out to the community in a way that helps
to increase trust, make it more relevant for people who live in these places,
and make it more relevant also for people, like Janet and others, who are
working in the neighborhoods as community-based organizations. And then
finally, actually making it relevant and useful for researchers like me.

So a quick map of our neighborhoods, and I don’t know how many of you are
aware of Stapleton. It used to be our former airport and is now still one of
the largest redevelopments in the country, and actually specifically designed
with what they call “active living in mind.” Right, so wide
sidewalks, lots of green space, mixed use where you can walk to a store, you
can walk to a restaurant, so making it easy to be outside and active. So with
the redevelopment, you’ve had these other neighborhoods, northwest Aurora, east
Montclair, what we call Park Hill and northeast Park Hill, who have been
exposed for decades to the old airport, and all of a sudden, you have this new
sort of redevelopment put in place. And it really presented a really
interesting opportunity to begin to think about community health in a really
different way.

The other thing that happened is we actually moved our medical school out
to what we’re calling the Anschutz Medical Campus, which was formally
Fitzsimmons, just down the street from Stapleton in these neighborhoods. So a
lot of change going on, and a lot of really interesting opportunities to
understand kind of health on many levels, in a very local level.

So just a quick description of what we call our footprint, in terms of the
demographics. And the thing to note is the real differences in our
neighborhoods, so these aren’t like Stapleton versus Park Hill versus east
Montclair. If you look at sort of racial composition, education, a number of
things, these are very, very different places, which again, presents really
interesting opportunities when you think about collecting data and sharing data
across very different neighborhoods.

So just a quick snapshot just to let you know how we started, and I think I
already covered some of this. But it started with a grant out of NIH, to fund
community-based participatory research. And the number one goal initially was
to begin to engage people in the five neighborhoods in sort of a whole effort
on data collection dissemination. And then, the second phase was to begin to
collect critical information on both residents, as well as sort of the health
of neighborhoods, and I’ll talk more about that. Our key focus areas were
physical activity, healthy eating, obesity and cardiovascular disease. But
again, we collected a number of different kinds of data and I’ll talk about
that.

And then, the third aim of the grant was just to begin to make sense of the
information we collected, and identify sort of using it to talk about next
steps with community. And then, a research focus was really understanding the
impact of these built places on health of people, as well the neighborhoods, in
terms of health disparities.

Okay, lots of information. I think the key message from this is, again, we
have lots of information collected in different ways. So we did a random
household survey of initially 950 people or adults, and then we followed up
with almost another 200 people who lived in apartment buildings, because we had
a hard time actually getting into apartments to collect data and recruit
people. So we had a household survey, we also collected very extensive data. So
for example, if the household was recruited, we collected data around their
houses basically, their neighborhoods, by looking at sort of sidewalks,
lighting, all sorts of different features.

We also looked at sort of resources in neighborhoods, so we collected very
detailed data, again based on community requests and interests on food. So
where are the stores, if you walk in the store, how much does this cost? So
really, we got inside the store, looked at availability, price and quality of
produce. We actually went to parks, a number of parks in the neighborhoods. We
went into the parks and said, “What’s there?” So it’s not just having
a park there, but it’s the amenities, the lighting, all the other things that
make a park actually useful and accessible. And then, again, we had collected a
lot of different information from surveys and others on safety, racism and
discrimination, trust among neighbors, and then we have a lot of census data,
as well. So lots of different information to describe sort of the context of
these places.

So if you think about all the information that I had listed on the previous
slide, and the fact that community were really involved, well, first of all,
the key was they were involved, right? That’s one of the key messages is
everything I just talked about, people were involved in what’s in the survey,
to the point where we talked about sampling frames and how are we going to
randomly select households? What’s in the audit, what do we pay attention to if
we walk into a park? Anyway, lots of involvement.

We actually hired and trained community members as really actually data
recruiters. So in this particular project, we had community members as
recruiters, and then we had a follow-up phone call from a computer-assisted
telephone interview survey unit. But we also trained people, community members
on qualitative data collection because, I’ll talk about it later, we did
household meetings with people to kind of disseminate findings.

And then, the other thing that came up, and this came up fairly early in
the project is, okay, we’re collecting a lot of information on people who live
in these places, and we really want to sort of talk about the real issue about
some of the abuses that have happened in the past. So I actually think this was
one of our biggest sort of wins in the sense that we got it out there fairly
quickly. How are we going to prevent any abuses from sort of coming to our
neighborhoods, because people were worried about that from historical
incidents. So that led to, in fact this is sort of what I’ll talk about a lot,
is the data review and dissemination committee, and Tracy and George are
involved in that on the phone, so I’m sure they’ll jump in later. But that’s
how this started is, we have a lot of data, how are we going to responsibly
sort of be stewards of this information for the neighborhoods?

So the data review and dissemination committee is anywhere from ten to 15,
depending on the month, we meet monthly. Early on, we met more than once a
month. And it really is composed of both residents, as well as researchers, and
through this whole process, and again I think this is a lot of important
upfront stuff that happened, but we got together and developed principles for
how are we going to use the data and how do people ask for data. So if
community groups in the neighborhood want to use it, what should we ask them
about how to request information, how to use information. So a number of
processes were put into place early to actually have that conversation about
what makes sense.

The other thing that happens, so we have principles, we have our large data
sets with all kinds of information. And then, the other thing that I think was
really important is, before we started sort of releasing information to
everyone, there was a commitment with the DRAD, along with 2040, to release the
data first to community members. So we had a big health summit where community
members were invited. We also invited everybody who agreed to be contacted from
our household surveys. So again, everybody got to come and see the data release
for the first time. And I think that was a big deal in terms of sort of
creating trust, and people not feeling like we just take off with their data
and publish their findings. But instead, we disseminated first to community.

So some of our key issues, in terms of the ownership, so when people
request data, projects requesting data should benefit community. Okay, so that
was one of the sort of do no harm. Projects should benefit community, and there
are places in the form where people write about how they’re going to use the
data. A lot of sensitivity in terms of when we release data, we only release
data in certain ways. And to date, we’ve only really given people release
reports with the data aggregated, depending on the question. But also, when we
begin to disseminate and show data, even in meetings and things, we came up
with some principles to how we can be more sensitive to not sort of
stigmatizing neighborhoods and populations. And I’ll show you some examples.

But early on, we have five neighborhoods. So when we showed all our slides,
it’s N1, N2, N3, N4, N5. Now, granted, you can look at them and guess,
everybody always does the first time. I think I know my neighborhood, but I
think the point is really important. It’s symbolic in that we don’t want all
the neighborhoods, “Oh, look at Stapleton. Oh, look at Park Hill,” so
we just showed all the data blinded. Then we have neighborhood briefs, and I’ll
show you the face of those. But we did every neighborhood, one at a time,
versus all the neighborhoods together, so we never have data, at least in the
briefs, where you show all the neighborhoods kind of contrasting one another.

And then, even in our maps, because we do a lot of work with sort of maps
and showing patterns of data, so the lowest level of reporting in maps is block
groups. So in fact, we talked about this a little bit earlier. And then, I
think this is key, a commitment to involving the community in interpretation of
data, so it’s not just showing survey data, but we also show sort of other
patterns of data, or we show kind of social conditions in neighborhoods, to
kind of begin to make sense of what we’re seeing on some of the individual
level data.

So those are, I think, some of our key principles around ownership of
community, and really communicating the sense of trust among all of us. So let
me just quickly show you an example, these will go fast. But this is a great
example, this was like our health summit. This is a copy of a slide where, in
this particular one, we show Colorado, we showed all the neighborhoods
combined, and then again, N1, N2, N3, N4, N5. And in fact, even to this day, if
we’re showing data, we tend to just use these slides to just show the
distribution with neighborhoods.

And then, same thing, again patterns showing broken down by neighborhood.
Just a quick example of the focus on conditions and resources. In fact, this
was a very interesting map in that we actually showed this to our community
group, Taking Neighborhood Health to Heart, our big council, and to actually a
few other neighborhood groups. And this, again, the point is, everything is at
the block group level, but you can begin to see patterns and see that it’s not
just Park Hill or it’s not just northeast Park Hill or east Montclair, but
there’s some common patterns across neighborhoods. And in fact, this slide,
along with some other slides, where it was one of the early interests became
food, because all of a sudden, we hadn’t collected data on food, what’s inside
a grocery store yet. They saw this and they started saying, “What’s going
on? What else do we need to be paying attention to, to understand why this is
happening?” And it started a whole sort of thread around food and security
and food access.

And this is some of the data that we got from that project, where basically
each of these is in the neighborhoods is a grocery store or a corner market.
And the green means percent that have all the fresh fruits, we had 22 fruits
and vegetables, and what proportion were actually in the stores. And if you
begin to see the patterns, so there are some stores way off here and a few
right over here, but for the most part, having a store doesn’t mean you’re
going to actually have fresh fruits and vegetables readily available, much less
affordable.

I have another really interesting slide that I don’t have here in this
presentation, where it talks about price. And that’s another sort of
mind-blowing slide in the sense that, in the stores that actually have it, for
example, one of these stores is very, very expensive. So again, I think the
point is to show sort of neighborhood conditions. And then, very similar in
terms of what our geography student called “health spaces,” but it
really shows the distribution of parks and open space in dark green, bike
routes, rec centers, things like that. And as I’ll talk about later, we
actually, by mapping these kinds of things, people have actually begun to use
our data to argue for the big gaps. Right, there’s nothing in some of these
places in terms of stores and in terms of rec centers and parks. And so, these
kinds of data are pretty useful for that.

In terms of sort of what we’ve accomplished, the data review and
dissemination group, as I said, we spent over a year in interpreting data. So
it’s not one of these things where you just go, “Okay, get the data out
there.” I mean, it really is carefully looking at data, figuring out the
best ways to actually communicate and disseminate. So one of the first things
we did is, we created each neighborhood has a series of, I believe, five or six
briefs in English and Spanish, so we make everything available in Spanish.
Actually in all the neighborhoods that had newspapers and newsletters, we wrote
a story. It was like a half a page sort of story about neighborhood data and
this project.

And then, we actually on a request by request basis, we provide data to
researchers, students, community-based organizations for grant writing, things
like that, so we provided a lot of data. And then, often our community members
primarily are involved in posters, workshops, national workshops, went to
Canada a couple of years ago, a group of our community members. So, a lot of
work just talking about sort of, the importance of kind of their role in
neighborhood health and actually disseminating data.

So DRAD was awarded, in fact the University of Colorado has a CTSA,
Clinical Translational Science Award, and DRAD actually, in conjunction with
2040, applied for a grant and was funded a grant, first of all, to collect more
data in apartments. And this, I think, is a very cool thing in that they have
what they call “house meetings.” So our community members were
involved in facilitation trainings, and they took the information from our
briefs, because we know that some of the neighborhood association meetings,
only some people go to those, other people don’t. So the goal was how do we
actually spread the word in a very informal way about what’s going on? And
these were amazing and what came out of the meetings, so shared briefs and
summary sheets.

And then a lot of what happened was, all these other things emerged about
what were important to community members that we didn’t ask about in the
survey. So actually this process of house meetings, I mean, I think it’s
something that we’re pretty committed to because we’ve learned so much about,
number one, sort of how to do it, but number two, and most importantly, how
it’s pretty powerful as a way to kind of hear committee member stories about
other things that matter that we didn’t ask about. And then, all people who
participate in the meetings, then we get them to start coming to our community
meetings. So it’s sort of one of these processes that feeds itself, and keeps
momentum and interest going.

So that’s what the briefs again, five briefs, and one for each
neighborhood, so it’s five times five neighborhoods. And then summary sheets
again, the point is just to show that we also give a really one-page summary of
different areas that are actually presented within the briefs. And really, the
point is to get the data out there and the findings out there for conversation
and use. All briefs are in Spanish, as I said. And then, I think this is my
second to the last slide, but I think one of the other take home points, I
think, from our group is the whole issue of use, so how data are used. And if
you feel like data will be used, you’re probably more likely to want to be
involved.

If someone comes to me at my doorstep and says, “Do you want to
participate in a household survey?” I’m like, “Oh, I remember seeing
that five years ago in the newspaper, and I know what happened as a result.
They put in a new park down the street.” So it’s that kind of process of
sort of being involved and using data that will then reinforce the fact that
people want to use more data and collect more data and participate.

So one of our neighborhoods did a health impact assessment, and they were
off the radar in terms of a rec center, and then all of a sudden, they became
back on the radar, and they got more money to improve a rec center, because
they actually took data and said, “Here’s what our findings are in terms
of physical activity, in terms of obesity,” and maps of what the gaps, so
used data for that. Two or three weeks ago, I got a request from one of our
local elementary schools. They were talking about diabetes in their health
block, so they wanted their neighborhood briefs about chronic conditions,
physical activity, things like that, so we sent those.

Again, lots of communities use it for grant applications. Here’s one, they
shared the survey, in fact, 2040 recently requested for one of their projects
where they were working with medical students, and they wanted to know findings
across neighborhoods and across other demographics on every experience of
discrimination. So they requested, we gave information for them, and they’re
going to have a follow-up project and collect some more data with focus groups.
Again, I talked about this where, because disseminated data, all of a sudden,
the whole issue of food access kind of rose to the surface and became a really
big deal and continues to be for us, where Tracy and others are writing grant
proposals to try to fund some of the work within our neighborhoods.

So this is actually a snapshot of, to me, the key take home points of what
we started with, is first of all, the arrows just keep going on and on. There
isn’t an end and I think that’s one of the points is it really is an ongoing
process where it’s really meaningfully engaged in community, in terms of all
sorts of things, methods, sort of what’s relevant, what’s not relevant. And
then, paying attention to sort of some of these larger issues. I think the key
is paying attention to what matters to people, and then in this case, in our
community, this was really important, so we wanted to make sure that this whole
system has information that’s useful and meaningful.

When we were here in February, I know both Janet and Tracy really talked
about the importance of sort of more qualitative data, and we found that out
like crazy when we did house meetings, where all of a sudden, you start having
people tell stories. You learn a lot about some things that you want to follow
up with, sometimes with more quantitative data. And then again, sort of it
keeps going on, but analyzing data and share findings to improve actions. So I
think one of the pushes we keep getting from community is, “Okay, we want
to use it for something. We don’t want to just collect data. We think it’s
important, but what’s next? How are we going to use it for actually policy and
action?” And again, it just keeps going on and on. So that is the end of
my presentation, thanks.

DR. FRANCIS: For those on the phone, we’re going to have questions
afterwards. We’re going to hear right now from Kathy Alexis, concerning
childhood obesity prevention in New York City community health centers, best
practices and lessons learned. And there is a common theme about using data.
The three community examples we have are all obesity, or at least in part
obesity examples.

MS. ALEXIS: Good afternoon, everyone. My name is Kathy Alexis. I’m the
Clinical Quality Initiatives Manager at CHCANYS, also known as the Community
Health Care Association of New York State. Long name, so we just say CHCANYS,
and thank you for having me here. Just to give you a brief introduction to
CHCANYS, my apologies, this is actually a wrong year. We’re now 40 years old,
so I think we’re still trying to claim that we’re young, but we’re a 40-year
old organization based in New York City. However, we do serve all of the
community health centers throughout New York state. That comprises of more than
60 parent organizations and approximately 457 satellite sites throughout the
state.

We work to ensure that all New Yorkers, and particularly those living in
underserved communities, have access to high quality community-based healthcare
services. And as you see here, our mission is basically to focus on retaining
and expanding primary care capacity, investigating in primary care health
information technology, especially now as many locations throughout the country
are adopting EMR systems, implementing primary care home standards, reforming
the primary care payment system and developing the primary care workforce.

So our childhood obesity program was initially funded by the New York City
Council, in conjunction with the New York City Department of Health and Mental
Hygiene, to create what we call the New York City Prevention and Management
Consortium. The funding structure unfortunately in New York City has not been
to our advantage. Because even though the grant cycle begins, it’s a 12-month
cycle, unfortunately, by the time we go through contract signing and approvals,
and it has to go through the mayor and then the commissioner and all that, our
project ends up being just about five or six months unfortunately. But with
that, we’ve still seen some great accomplishments throughout the five or six
months, which I’ll share with you.

For year one, which was only a five-month project, it was a very
conservative project. We only worked with the community health centers, and
remember these are only community health centers throughout New York City. In
year two, we bumped up by a month, so we were now a six-month project. In the
six months, we were able to include participation of school-based health
centers. We worked with community-based organizations. We also partnered with
other community resources, as well as incorporating what we called “parent
ambassadors.” Year three, we bumped back down to a five-month project, and
because our funding was cut dramatically, we were not able to use the same
resources that we used in year two. And so when I show you our data, you’ll see
that it’s going to reflect that in our data, unfortunately.

So the aim of our consortium was to improve the overall screening rate of
children using the expert recommendations stated by the National Initiative for
Children’s Healthcare Quality, which is NICHQ. And our basic focus was on
children between the ages of two and 18 years old. So here’s a long list of all
the consortium participants. We worked with approximately eleven parent
organizations, which meant 20 sites. They were all from four of the five
boroughs. The fifth borough that was not part of the project was Staten Island,
and unfortunately, if you all know anything about New York, Staten Island is
usually the forgotten borough. They’re not always so included, but only
because, at the time that we were starting this project, Staten Island did not
have a funded federally-qualified health center. They were not designated yet,
and so we couldn’t really have them participate. Even though we still shared a
lot of our resources with them, they couldn’t really officially be a part of
the project at that time.

So I’m pretty sure that you all are aware of the childhood obesity
epidemic, especially that which is in New York City. Overweight and obesity
rates nationally for children have grown exponentially. We also know that being
overweight and obese can lead to a myriad of health problems, and even a
decrease in life expectancy. But what I wanted to focus on was the fact that,
at least in our health centers, the recording of BMI was not yet part of a
routine practice. And basically, providers just weren’t comfortable in
addressing the issue with patients and families. And so, CHCANYS saw this as
issues that we could address throughout the consortium. We felt that providing
some kind of resources, training to the providers, incorporating the parents,
that this will then make them a part of the initiative and further take this
message home to their children.

And again, you may all be familiar with the terminology for BMI categories.
But what I wanted to concentrate on is that, no matter what the terminology you
look at for the consortium, it was geared towards the 85th and higher BMI
percentile, so particularly those who were overweight and obese. Now,
particularly in the school-based health centers, once the BMI and weight
classification and physicals were completed, the provider that was set at the
school-based health centers, particularly nurse practitioners, they would call
the parent immediately, right after the physical, and tell them, “This is
what happened at your child’s physical today. This was the result of the BMI.
This is how we are now classifying your child.” That was something that
didn’t happen prior to this consortium for a lot of these health centers.

So the data. All of the children, between the ages of two to 18, this is a
list of our patient population of focus, who received medical attention at the
clinic site in the previous 12 months, regardless of treatment or diagnosis.
Now, as you see, as I said, in year one, we were very conservative, we only
used health center patients. In year two, we moved onto using school-based
health centers. So for year two, we were charged with only having a reach of
2000 children. As you see here, we reached more than 24,000 children. That we
considered a great accomplishment, because I think at that point, not only did
we know how best to reach the children, but the health centers were able to
come up with strategies on how to reach the community, as well.

Despite the size of the teams or the health centers, they were able to
document the BMI at very high rates, covering almost all of their target
populations. So once again, everyone is over, I would say, 95 percent in
documenting their BMIs. The consortium had great successes with process
measures. As you see here, in every year of the initiative, 85 percent or more
of the children were classified as underweight, healthy weight, overweight and
obese. This measure was tied directly to addressing appropriate BMI
documentation and classification as a part of routine practice. So with that,
participating providers and their assisting staff were no longer allowed to
just eyeball a patient. They had to actually go through the process of
collecting the weight and the height, and put it in according to the BMI growth
chart. The obtained the BMI percentile and then made the required
classification and made the required recommendation for each of the child.

Of our children included in the population of focus, these were the
percentages for each initiative year of those patients that were identified as
overweight or obese. As you see, as the initiative went on, steady increases of
patients who were overweight and obese, close to half, were seen at all of the
participating health centers. So in addition to weight classification, we
wanted to monitor whether or not children classified as overweight and obese
were being given the appropriate follow-up care. In this case, that was the
nutrition referral. Although each year we were able to reach our target, the
highest numbers were reflected, of course, as of in year two. So by year three,
the percentages dipped to its lowest point. This was really due to the changes
in staff. We had a few health centers that participated in which a nutritionist
was not available or went on medical leave or, due to funding that was cut,
they had to have some layoffs at the health centers. So we had a goal of 20
percent of the diagnosed children having a nutritional counsel, and once again,
as you see, that was a great success.

Our third and last process measure really tied into systems changes by
setting a goal of 50 percent of diagnosed children having a follow up with a
healthcare provider regarding their BMI. Because having follow up with
diagnosed children requires sustained resources within the health center
system, this is why we see a variance in the results. In year one, we had some
progress. Year two, the teams did remarkably well in reaching their goal. And
then, in year three, once again, it dipped due to loss of staffing and other
loss of resources. And so for example, though we did referrals for a
nutritionist, a lot of the nutrition counseling was not only done by a
nutritionist, but it was also done by health educators, by the nurses,
sometimes by MAs. And then, if those resources were limited, unfortunately the
actual visit was not possible for the sites.

So again, here you see that it reflects the same pattern. This is the 40
percent. We had a goal of 40 percent of overweight and obese children in the
population of focus reporting a healthy behavior. Once again, we had a dip
lowering to for year three. But for year two, we feel that the reason why we
had a higher percentage for year two was this was when we had a higher
production of materials to the patients. We partnered with the 5-2-1-0 Campaign
that was set up by NICHQ and we shared all of their materials, not only with
the health centers, but we did a great campaign in sharing the materials with
the communities in which these health centers served.

Out of all the measures that we tracked over the course of the three years,
this was the toughest measure to achieve. Actually having the patients reach a
healthy rate or reach the BMI, we found that it required a lot more work than
just the five or six months that we were allotted. This is definitely a change
that required us to follow the trend for longer than that time period. Although
we did not meet the goal of the 20 percent, CHCANYS was happy with some form of
a result, as you see with year one. They really were not collecting how many
patients were moving onto healthy BMI or healthy weight. And at least at this
point, they were starting to collect this information. And a lot of that was
because, as health centers were starting to implement their EMR systems, there
were flags being placed on the system to remind the providers to ask these
particular questions. How is the patient doing, what are they doing at home to
change their weight or change their activity?

This is where we started encouraging self management goal setting, where
once again that was made a flag in the EMR system to ask what goals are they
looking to adapt into their daily changes. And during their follow up session,
the providers would make sure that they address the patient or address the
parent, of whether they followed through with that goal setting.

So I gave you the why, the what, the when. I’m going to go into now how did
we do all of this and what were some of the strategies we put into place. First
of all, none of this work would be possible if we did not obtain buy-in from
senior leadership. We felt that it was important to engage the senior
leadership because in the end, they were the ones that were responsible for
proving time, providing resources, as well as ensuring sustainment of the
success once the grant dollars were gone. Unfortunately, we are now in a
position where we’re looking for funding, so we’re not moving forward with the
project, because New York City Council did cut the funding to a lot of the
community-based projects. But though we’re not actively funding this project, a
lot of our health centers are still maintaining a lot of the successes that
they experienced through this project.

Each year, we provided an extensive training on the chronic care model and
the model for improvement, which were foundations of the approach or the change
that the consortium took to make changes with the health centers. We also
developed key partnerships. CHCANYS realized that we couldn’t really do all of
the work ourselves. We had to partner with the Children’s Museum of Manhattan,
which specialized in teaching the staff of the health centers, as well as the
parents, on how to address healthier eating and physical activity in a fun and
interactive way.

And kind of like a side note, one thing that they did was a nice little
demonstration, and this was mostly for kids, again, remember, you have, two,
three, four, five-year olds, and they did a demonstration of what’s poop and
where did it come from. And for them to actually understand what you eat, this
is how it’s processed through your system. And you want to make sure that your
body is working well and producing good things, and so you want to eat well and
eat your broccoli and eat all of this. So they had a really good way of how to
talk to kids about what’s going on with their body, and basically how important
it is to conduct physical activity.

We also wanted the initiative faculty to come from a health center. We
didn’t want to bring outsiders to do this work, that’s not really what we’re
about. And so, our faculty was a peer health center, the Urban Health Plan,
which has been, if not nationally, but definitely locally, known as pioneers in
conducting a lot of our collaborative work. We also provided teams with
mentorship from returning teams. So as we moved on every year, we had another
site come on as our mentor site. That site would be responsible for scaling up.
So if they started off with using their health center, they would then scale up
to a school-based health center, or they would scale up to another, if they use
one site. If they’re a multi-site organization, they would move to a second
site or a third site. So we always feel that that was a way for them to spread
and sustain the work that they accomplished.

Best practices were also a key to our consortium from strategy
implementation. We wanted all teams to focus their efforts on practices that
were already tried and true. So we had teams refer to what we call our
“Childhood Obesity Change Package,” and I can always share that with
you afterwards. But it was definitely a change package that we shared with the
sites to say that according to the care model, if there were certain changes
that you’d like to implement, here are some ideas, here are some options that
you can use.

As the initiative took place, we knew team members needed skill building
opportunity on an ongoing basis. After the initial learning session, teams were
provided with trainings on motivational interviewing, behavioral activation,
general nutrition and other topics, as needed. We also used our health
educators and other disciplines within the health center to help us with cereal
sugar demonstrations.

We found that patients are wasting a lot of time in the waiting rooms at
these health centers, so why not make use of that time by doing a
demonstration. And the best demonstration out there to date is the cereal sugar
demonstration. Every time you show them a bottle of soda and ask them how much
sugar do you think is in that bottle, and we actually show them, the expression
on their face is remarkable. And I think it immediately has a lot of changes.
It promotes a lot of changes in their behavior.

Next, we engage the community through the use of team selected parent
ambassadors. So parent ambassadors was a new program, a new aspect of the
program for year two, where we identified parents who were patients of these
health centers. And we used them as voices of the community, and we made them a
part of the health center team.

So whenever the health center had a meeting or wanted to talk about
strategies on how to address the community, the parents was part of that team
and they were able to say, “That’s not going to work in the community. The
parents that I know, they’re not going to understand what you’re saying. This
book that you’re presenting in front of me, I don’t understand it, and so my
friends may not understand it, so that needs to change.” And we felt that
was an integral part of the team moving forward and providing resources and
service to the community.

The parents also shared the information. They were trained on how to talk
to other parents about healthier eating and physical activity. They shared this
information at their PTA meetings, they shared it at their church. If there was
a health fair or a block fair, they had tables at these health fairs and block
fairs, and they shared the information. What was best about that is that it
wasn’t coming from another doctor or a nurse or something. It was somebody that
was just like them in the community, probably a next door neighbor, that was
sharing the same information. And we found that it worked.

At the end of every year, we had what we called a harvesting session for
the health sessions. And these were just forums to share best practices among
the teams. But we also invited the senior leadership of the health centers of
CHCANYS, of the funders. We also opened it up to the community to be a part of
these forums, so they can see the data that was coming out of the health
centers, and they can also learn about what resources is available.

So lessons learned and there were a lot, a lot of lessons within the past
years. We always built on the foundations, lessons learned from previous years.
We also found, once again, leadership buy-in was integral. For the sites that
we were not able to maintain, the leadership buy-in, they were not able to come
back just because the support wasn’t there for them to continue this work. As
FHQCs are striving to achieve patient-centered medical home status, CHCANYS has
focused our collaborative to mirror that model. And we did that by adapting a
multi-disciplinary approach. We found that integrating current resources and
addressing the patient’s care as a team further addressed their needs in a more
efficient manner.

Healthy eating and physical activity definitely, we felt, should be
introduced to the parents and children in an interactive, creative and fun way.
We found that, a lot of times, if we shared this information with the kids,
they ran home and shared it home with their parents. And the parents were kind
of forced to do something about it, because they felt like they saw that their
kid found this really important to share with them. They were like, “Okay,
we’ll have broccoli for our dinner tonight,” or “We’ll have
this,” just because little John brought that home.

And another, we had a focus group with a lot of the parents who were part
of the parent ambassador program. And what they shared with us is that, the
reason why they take their children to McDonald’s or the reason why they take
their children to all these fast food places, and especially children of
immigrant parents, they felt was because they weren’t home a lot. They were
working, mostly because that’s really what they had to do. And so if they
wanted to find a way to bond with their child, the way to bond with their child
was giving them what they want. And what do kids want? They want to get that
new toy at McDonald’s that is being advertised these days, and so that’s what
they did. And they shared with the teams that if there was a way that the
greater organization, whether it’s the state or a national, if there’s a way to
change the advertising towards children, for example, with McDonald’s, why give
those toys, because those toys are really what the kids want to get. They
bother the parent, the parent feels they want to bond with their kids, so they
take them to McDonald’s. And so there has to be an effort together, not only
just with the health centers, but nationally to have a change.

There was adoption of best practices, which required creative strategies in
regards to the finances and human resources. As I said, with the finances being
that a lot of the funding was cut, not only to CHCANYS funding, but also to the
funding of the health centers, we had to think about different ways of using
current resources, the staffing. Like I said, the waiting room demonstrations,
those are just ways that we try to bring the information to the community. And
providing ongoing coaching and incorporating team feedback through the
initiative assured maximum success, and we did that by having collaborative
calls.

The structure of our project was that every week, we had a collaborative
call where the health center teams came together, shared their successes,
shared their challenges. We troubleshooted a lot of problems. We also did a lot
of work on discussing how to perfect their EMR system so that it can collect
the data that they’re looking to collect, and then they can then disseminate to
their quality improvement team internally. And so, when we’re looking at next
steps for the teams, we’re hoping the teams that we worked with in the past,
and the teams that we hope to work with in the future, will sustain any of
their system changes so that they can scale up and or spread. Currently in New
York City, we have 100 percent implementation of EMRs.

In New York State, it’s 88 percent. So with that, we continue to use
electronic health records to mainstream and ease the data reporting.
Unfortunately, in New York State, we have 12 different EMR vendors, so that
makes it really difficult to kind of standardize a practice throughout the
state. But once we have an idea of how each of the EMR systems work and what
the main pieces are to them, then we can assist the health centers on how to
use their data.

And for CHCANYS overall, we’d like to continue working with our partners,
whether it’s with the community-based organizations or with the community, to
further the work that we have, secure continuance, trying to secure funding for
the project so that it can continue. And most of all, we’re looking to spread
this project statewide. Right now, as I said, the project is mostly New York
City based. Though some people think New York City is the entire state, but
it’s not. There’s a whole other world outside of the city and we’d like to just
take this further and bring it to the communities outside of the city. Thank
you.

DR. FRANCIS: Thank you. I am going to open it up to questions from
committee members and the group more generally.

MS. MILAM: Debbi, I’ve got a question for you. You talked about data
release and just going down to the block level. Could you speak a little to how
you determined that block level was appropriate, the right level of aggregation
and what other sorts of release rules you put in place and how you knew they
were right or what testing you did? Where you drew them from? Thank you.

DR. MAIN: So it was actually through community meetings. We were trying to
figure out, and based on if we sort of distributed the survey data, and number
of people per, we wanted to have enough people. So it was around anywhere from
15 to 35 or 40 in terms of numbers. But I think, and I’m going to punt it, too,
to my community collaborators, because it was more than just the numbers. I
think part of it was the message. And I don’t know if someone in Colorado hears
this and wants to kind of jump onto this answer.

MR. WARE: Well, this is George. And certainly one of the things that we
were concerned about was stigmatizing various neighborhoods. And so, after a
lot of discussion, we just came to and learning what size the block group, how
many people that might encompass. We thought that that would be an adequate way
of being able to describe the neighborhoods, but not to the point of
stigmatizing them.

There were points where we talked about, especially with the neighborhood
audits, where they went to and looked at the conditions in the neighborhood,
and looked at the things like windows. We just didn’t want it to be the case
that someone might be able to say, “Oh, you don’t want to live in a
certain place, because look what the data is showing about that
neighborhood.” And so, it was through a lot of discussion that we said
that that was probably the level that we should be doing the analysis.

DR. GREEN: I’d like to follow up on what George just said. Before I do, let
me declare that I’ve got a conflict of interest, but I certainly have a duality
of interest because I’m on the Board of Directors for Partnership 2040. That
said, I have a question to follow up on what George just said, and I also
wanted to ask it to Kathy, also. Can you comment, can you actually tell us
about particular harm that came to your communities because of communicating
the results of your work? And then, the second part of my question is, can you
just continue, as George was, can you also give us a listing of the fears of
harms? Actual harms and fears of harms, that’s really the questions for both of
you.

MR. WARE: I’ll start off. One of the things, it was even for my skeptics
becoming involved with Taking Neighborhood Health to Heart, was I work for the
state health department. And when we had done various surveys and focus groups,
people complained out how often information was gathered, but it wasn’t used to
benefit. They didn’t see where it actually changed anything. And in fact, they
also talked about harms that were done. And I don’t recall hearing specific
examples that they gave of information that was used by the health department,
but they did have this overall sense of all it does is, this is just one more
example of, in the case of one of the communities that we were serving, we were
serving around disproportionate rates of STIs among African-Americans.

They said this is just one more example of what’s wrong with our community,
and people were just very resistant to taking part in any type of work that the
health department was doing related to that history. And so, that’s’ what I was
bringing to the table when I became involved with Taking Neighborhood Health to
Heart. But I can’t give you a specific example of when that happened.

MS. STEWART: This is Tracy. I just wanted to chime in. One of the things
that did happen through the CBPR piece that was very enlightening and might
kind of go along with what you’re talking about, is the harm that’s been done
when you look at African-American and Latino communities, specifically from a
top down research perspective, is that you already walk in with assumptions
about what you’re going to find.

And so, the harm that’s been done in this community is that we have never
looked at environmental conditions around asthma. But when we did the CBPR
piece and we started gathering data there, and the way that people answered the
questions on the surveys, we started to realize that there is this incredible
explosion of asthma, both in adults and children, especially in the northeast
Park Hill area. And what was interesting about that is that, if you were ever
in Denver, you’d see that we have a lot of environmental factors that are going
on alongside I-70 and Smith Road and all that. And those things had an impact
on the community.

But for years, because of the way research has been done in these
communities, and it’s an African-American community, we only went in looking at
diabetes, heart disease, high blood pressure, the typical known factors.

The other harm that’s been done, and we just had a big conversation about
this, in a couple of instances is that one of the other things that popped up
for the communities were issues around mental health. And again, for years,
we’ve been looking at hypertension as sort of, “If only people could eat
better and walk more,” and not looking at the stressors of life,
especially for communities of color, people living in those communities, and
how that stress and that lack of care on the mental health level plays into a
physiological phenomena, which might be considered a defense mechanism. So
there has been harm out neglect.

DR. FRANCIS: Kathy, do you want to jump in on that, too?

MS. ALEXIS: Yes. I just jotted down three notes in thinking about that
question. And one fear that I remember parents sharing with us is that this
could easily be another great project introduced into the community, and once
the funding is gone, it’s taken out of the community and nobody follows up. I
can only speak for New York, I feel that that is something that the people in
the community are accustomed to, especially folks from the government coming
in, doing something, and then just leaving with the successes and not leaving
some kind of foundation behind. And so, a lot of the work that we do at the
health centers is to ensure that some of this work is sustainable. We’re not at
100 percent of doing that. Unfortunately, it is very difficult, and as there
are high turnover rates at the health centers. But I think, for those sites
that are motivated to keep this work going, they do try to find some way to
sustain it.

There’s also the fear of low self image on the children. They feel that, if
you keep talking about weight and physical activity, for those children who are
larger, that there’s some kind of low self esteem or low self image. And so
with that, one thing I forgot to mention in my presentation is that, from the
parent ambassador program, one of our health centers, one of our mentor sites,
they took that program and developed into something totally different and made
it a peer-to-peer mentoring program, where the peer-to-peer, they identify
children who were part of their patient panel, who was diagnosed as overweight,
and they lost a considerable amount of weight, and they identified those kids
to be the peers in the community.

And so, these were the kids that they learned how to talk to their friends
about physical activity and healthier eating. And they were able to go out into
the community and talk to their friends about, “Hey, this is what you
should be doing,” or “This is something else you can eat
instead.” And a stipend was given to the kids, these are kids, want to
keep their interest, so we gave them a stipend to keep them as part of the
team. But they did learn a lot and they were able to share a lot of this
information with their friends.

A challenge that we did have was, once again, we’re dealing with
underserved communities, a lot of it, especially New York City, are immigrant
populations and where the idea is a big child equals a wealthy family. And so,
if you’re coming to this family and you’re saying, “Your child is
overweight. He really needs to lose weight,” and they’re, like, “What
are you talking about? He’s great. He looks healthy. That’s a good child,
that’s what you want, that’s what we want in our family.” So the challenge
was to kind of change that mindset.

And really, the only way to do that is to have a culturally sensitive
format at the heath centers, folks that understand the culture. And New York
City being what it is, there are so many cultures there, it’s just a matter of
making sure that everything, all of the resources and all of the trainings, are
all culturally sensitive.

MS. MEREDITH: I have one thing to add if there’s time. This is Janet in
Denver.

DR. FRANCIS: Okay.

MS. MEREDITH: We did a childhood obesity study in these five neighborhoods.
And one of the issues that was raised many times was the issue of using BMI,
and that BMI is a very sensitive issue because with people’s different
backgrounds, they tend to grow and weigh differently, their bones are heavier.
And this sense that, if you categorize people all as overweight or obese
because their BMI is in the top 15 percent of national average, it doesn’t
necessarily reflect that a child is overweight or obese, and that that itself
is stigmatizing.

And in talking to our researcher, we had a lot of discussion about the fact
that it’s one of the few measures that’s available. It still doesn’t make it
necessarily an accurate reflection of health. And it was funny because, you
know, I think there was a comment earlier about how the medical professionals
need to do more than just look at a child. They need to measure BMI to see if
they’re healthy. And part of what we’re saying is sort of the reverse, which
is, “Okay, do your BMI thing, but then take a look at the child. Because
there are lots of kids who you would very quickly say, all right, this kid is
healthy.” So the BMI issue is alive and well, and truly an issue with
different cultural backgrounds.

DR. FRANCIS: Walter?

DR. SUAREZ: Thank you. I have two questions, one about resources, the other
is about funding. They’re kind of the same, but resources meaning resources in
terms of the, well, let me start with this. Both efforts, and I see a lot of
initiatives around this, use CBPR, Community-Based Participatory Research,
which is something different, I guess, in terms of how research is done in
community-based oriented research, involving individuals from the community,
directly helping define the research agenda, define the data analysis, the data
dissemination, and even perhaps the intervention into the work.

So my question about resources is, because I did this type of research back
in Minnesota and the most significant issue we identified was the need for
training community health advocates, community health workers, whatever we call
it. So the need to have this new group of people at the community level that
are going to help support the community in identifying all this information,
using it and ultimately achieving improvements in the community health at that
level.

So my question about resources is, do you think that there is enough of
that kind of resource in the community at this point, or is there a need to
really look at finding ways to training and to bringing in and increasing the
pool of this type of individuals and resources that are needed at the community
level. Do you have that experience in terms of resources?

MS. ALEXIS: I feel that there are not enough resources out there,
especially when you’re thinking about community health advocates. I know that
we are starting to work with community health workers in New York, but
unfortunately, a lot of the work that they use, and particularly patient health
advocators, and community health workers, there’s so many different titles that
you can place on that one entity.

But if you wanted to speak of patient health navigators, they’re usually
used in the cancer field, and a lot of the research has been around colorectal
cancer and other types of cancers. We’re now starting to research the use of
patient navigators and diabetes care management, and I think slowly into, and I
think there has been some work about, diabetes care management and childhood
obesity, and using the patient navigators to assist the parents and the kids,
not only in how to navigate their care within the system, but also how to
identify the resources in the community, how to identify how to get it, how to
use it, and it’s really slow.

Actually, I’m hosting a webinar next week, particularly on how to use
patient navigators and diabetes care management. And the information is not
really out there, especially if it’s not around cancer, you don’t really know
how to use it. And I’ve found like a lot of people are craving the answers on
how to not only identify the right people in the community, to be these patient
navigators or the health workers, but also how are you going to sustain the
program and pay for it, because right now, there’s no reimbursement for that
resource, if you include that. So really, it’s a much needed resource, but
there is no way to sustain it because there are no dollars behind it.

DR. SUAREZ: Well, I don’t know if you had any additional comments.

DR. MAIN: It’s a whole different kind of resource and infrastructure. I
mean, part of what happens for us, because we’re really talking about
collecting data, disseminating data, ideally using data for advocacy and policy
change and things like that. So it’s a different kind of infrastructure, but
part of what happened, in fact, within the project, what, six years ago or five
years ago, is we actually started really developing capacity. And even our
teenagers, I mean, we do some inner generational work where we’re building
capacity within people who live in the neighborhoods, where now, in fact, we
have two of them, one of them is now a data analysis.

And so, it’s a different sort of level of infrastructure and resources that
I think is really challenging because of funding, but our model ideally is to
sort of train people who are very comfortable in community and data collection
and dissemination and some other things, in more than one language actually.

DR. SUAREZ: Exactly. And so my second part of the questions really, it’s a
two-part question more than two different questions, is about funding and how
to support this type of efforts long-term, because most of this I refer to as
projects. And one of the principles on community-based participatory research
is, you don’t come to our community to do a project. We own and we want to own
and we want to maintain, and we want to keep running with it. And so, how do
you see finding the funding that is needed to help support those kind of
initiatives? Is it a funding that gets incorporated into the funding at the
state level of communities?

DR. MAIN: I think it’s a great question. And in fact, your whole point
about it’s not a project. Finally, I should say, I changed this from project to
initiative, because part of the figure is, as we keep going and depending on
what happens in our analyzing data and making sense of it, we keep collecting
more data, which is not cheap. And so, part of it is self-funded, part of it
grant funding, but I think you hit the nail on the head, is we don’t have the
consistent infrastructure and funding to really make that figure kind of
realize and sort of be realized in a full way. And I think that’s the exciting
piece is to figure out how to do it really well, where you don’t have to keep
hiring people for different things, but you have a very talented group of
people who can do this work really well. It’s challenging.

DR. FRANCIS: There are a couple of other hands, but I can’t resist asking
you a question before I go to them. So you collected your own data, neither one
of you used existing data sources for a different purpose, or maybe you
contemplated it. But one of the questions for us is, what sort of
confidentiality, if any, how should we be thinking about, say it would’ve been
really useful to use clinical records. Now, Kathy was mentioning that some of
the information that you collect will go back into clinical records. But did
you do any thinking about using other data sources, and if so, getting
community input into the permissibility of that?

MS. ALEXIS: There was no thought of that, I have to be honest, I don’t
believe so. I think the PCA, we’re in a different position in that, because we
are working with the health centers, it would be the health centers to collect
that kind of information. And I think that makes a good point in which we can
assist the health centers on how to do that. But I think, as the PCA, because
we’re at a different level from the community, we probably would not be able to
do that kind of data collection. But we could definitely work with the health
centers or at least how to set up a system to do that.

DR. MAIN: Does anyone from Colorado want to respond?

MS. STEWART: Debbi probably spoke for us pretty well there.

DR. FRANCIS: Okay, Paul, and did I see Marjorie, too? Paul? Marjorie, then
first.

MS. GREENBERG: To Debbi, you’ll think this is what I always say, but it’s
what I said in February, too, that this has been really very exciting testimony
and testimonials and information. And I thank you both. I’m inspired by both of
you and by what you’re doing, and at the same time, concerned. I’d like to
think that you are just a tip of the iceberg and that you represent similar
things going on all over the country. And I know there are some and we had nine
exemplar communities, or 11, thank you. But still, I don’t think it’s true. I
know it’s not where we’re putting most of our money in this country. So I’m
trying to think, what can we do to kind of move some of this forward.

But actually, although we were talking, it may seem somewhat disparate, but
how all of these presentations that we heard today have sort of come together.
We heard from Dr. Botkin, and I thought it was such an important point from the
beginning, that frequently research, biomedical research or other research,
that is even if it’s de-identified, the goal has been to fly under the radar.
That has actually not just been the outcome. I think in many ways, many times,
it’s been the intention.

And I remember a hearing, and Maya, you may have been there, soon after
HIPAA came out, I’m sure Gayle was there. And we were sitting in the basement
of a hotel in, I think, Silver Spring. And I won’t mention what agency said
this, but it was after HIPAA had come out and the privacy rules and everything.
They said we were doing fine before, people didn’t really know what we were
doing, but it was good and it was for the public good. And now, we have this
problem. And these were not bad people who said this, and they were doing good
work. But that, I think you just put your point on it, that it will come back
to bite you at the end of the day, if nothing else.

And then, I just tie that in with what we heard this afternoon, where not
only did they not try to fly under the radar, you were all flying together,
holding hands. The more people knew about what you were doing, the better, and
not just so you could do it, but so it would meet people’s needs and it really
would impact on population health.

And then, I come to the middle of the sandwich here with Denise, who kindly
joined us today. And your first recommendation here was that you would like to
see the national committee and certainly with NAHDO and other organizations and
the department and everyone else, I’m sure, but lead the effort to develop
messaging for the public and policy makers.

You said specifically about the need for identifiable data, but to improve
the public’s health through evidence-based decision making. And so, I feel that
is very tied also to this whole idea of we have to dispel the view that it’s
better for people not to know what you’re doing. We have to find more effective
ways to reach out to people, and you have certainly some best practices here,
to engage people.

And then, some of these issues about, well, certainly suing people or going
to court or whatever, I mean, there will always be some that will do that. But
it’s like they’d be suing themselves, because this is part of the process. It’s
not these people doing something to those people, as you said, not a project or
whatever, not even an initiative. It’s an organic situation. And so I don’t
really have a question, but I just wanted to sort of bring those strands
together that are in my mind, because even so, I don’t think this is well
understood. And yet, it’s so compelling to hear it.

I did have one specific question about these 12 different EMR vendors,
which both Paul and I sort of groaned. And now, some of these may well have
come on line before this whole meaningful use initiative, and that could
happen, I guess. And so, that’s an interesting point, that they didn’t maybe
need the funding that’s part of meaningful use, so they didn’t require to be
standardized either. I’m hoping that that can’t happen now, as people getting
the incentive payments or whatever, that the organizations do have to have
standards in place, so they aren’t just 12 different systems, that these
systems can talk to each other. But have you found this to be a significant
issue from the point of view of comparing data or sharing data?

MS. ALEXIS: Yes, absolutely, because they do not speak to each other at
all. And I’m relatively new to the whole quality improvement world, and so, to
figure out what happens with each EMR, how does each one of them work and the
different lingo. I heard about jellybean the other day, and I’m like,
jellybean? I’m like, what does that mean? But all the different EMR vendors has
a different format or a different platform. And there’s no way someone coming
into these health centers from the outside can understand what that means, so
that we can provide the type of assistance that they need.

And then, with that, there’s no way that a patient coming from New York
City, that decides to move to Albany, that patient record, there’s no way the
information is going to transfer over for that patient. And so, you’re going to
start anew. So having all these 12 vendors, I mean, it’s great, it’s nice to
have options, but sometimes the way my brain works, I don’t really like that
many options.

So there’s just all these options, it doesn’t work when you really want to
deliver the kind of care that you’re looking to deliver to the patients in such
a big state, because it’s big and there’s’ all these different sites. And as I
always try to tell people, when you look at one community health center, you
look at one community health center, not one of them are the same. And so, it
would be helpful to kind of fix.

MS. GREENBERG: But they have a lot in common, right?

MS. ALEXIS: They have in common, yes.

MS. GREENBERG: I mean, they could be more similar.

MS. ALEXIS: Yes, they can.

DR. FRANCIS: Paul, you had a question?

DR. TANG: I’m struggling with how to formulate it. One of the interesting
things, who said it, it was in the Colorado House meetings, and in the sense,
what that represented was a sort of a local focus group. But you said there was
new information that came at you, and I’m going in the direction of
ethnography. In other words, in trying to guess or deduce something from even
data, what do people really need? What gets in the way? And then, Kathy
reminded me of that when she talked about the patient navigators.

So in a sense, how do we discover what really gets in the way of health? I
can’t remember the program, but I think it was in New York, where this woman
started out trying to help people with their health in free clinics and all,
and found out that it’s pretty hard to be healthy and homeless, and ended up
turning into really a community-based effort to deal with needs that interfered
with health, just like education.

And so I’m circling around how do we understand all the various things. And
then, if we understood that well and understood what their perception, the
community residents’ perception of their needs, then wouldn’t we have a natural
job description for a navigator. And if we really had a ethnography-based job
description of a navigator, then wouldn’t it get sustained. That’s where I’m
ending up. Wouldn’t it get sustained? Because if there was a true perceived
felt need for something, then we would find a way. We, the community, go back
to ownership, would find a way to make it happen. The ownership can’t happen
after the grant. It doesn’t happen before the grant, I mean, because of the
grant. It’s got to happen because it’s needed to happen.

And so, that’s where my question boils down to the ethnography and how do
we discover what is, one, the real need, but also marry it with their perceived
need, so that you get ownership. So I’m asking it as an opened-ended question,
how do you deal with that? Am I even on the right track, and then wouldn’t we
have a job description for a navigator?

MS. MEREDITH: Can I take a stab at that, here from Denver? All right. This
is Janet. So there are a couple of things that we have been finding in talking
to community advisory groups about health. And one, this doesn’t directly
answer your question about navigators, but it brings in a couple of issues that
I think influence this. And one is that, there is no sort of generic way to
understand these issues. You really have to understand what’s happening to
people in a specific place. And once again, mentioning that qualitative
research is what tells the story. There is a story of what happens to people,
and it’s never been more apparent to me than when we had our group together,
talking about mental health issues in our neighborhoods, and what happens to a
family when they have a child, even up to say a 30-year old child, who suffers
from severe mental illness. The data is never going to tell the story, it’s all
about the qualitative information of what really happens to people.

I think one of the challenges with CBPR, and this now rolls into the
question about funding, is that it is not a linear process. You have to be
willing to collect data, look at the data, do qualitative fact finding, and
then determine how you’re going to do programs or interventions or whatever you
need to do, to try to change things, and then see what works. One of the big
problems that we face is that, you referenced that that this is really an
organic process. There really is no funding for organic processes. And people
tend to focus on funding, either one piece of that or needing to know where
it’s going in order to be willing to fund.

And I think that we are really onto something big here. But the problem is,
we’re fighting tooth and nail, like every step of the way, to find the right
funder, to define what the outcomes might be, before we know them. And I think
there has to be a different way of thinking about long-term health and the
organic nature of it, if we’re going to fund it, structure it and be
successful.

MR. WARE: And this is George in Denver. One of the things you mentioned,
ethnographic research and how do we know real needs versus perceived needs. One
of the things that was, I think, the beauty of our doing the neighborhood
meetings, the household meetings, was that people began to engage around, it
wasn’t just the sense of someone taking the information away and saying,
“Oh, based on what we’re hearing, this is what we’re thinking needs to be
in place.”

There were people in community who were beginning to own what the next
steps to what needs to be in place. And that sense of ownership, the beauty of
this is that you don’t necessarily have to wait even for a funder, even though
we could use the funding, but for a funder to say, “Oh, yeah, we’ll fund
that initiative.” There are some things that begin to happen at the grass
roots, and I think our food subcommittee that we have, that’s taking a look at
how to make food more accessible, healthy good food more accessible in our
neighborhoods. That’s an example of, at the grassroots level, through this
project, through this initiative, through the work of Taking Neighborhood
Health to Heart, that’s an example of people at the grassroots saying,
“We’re going to take this on and we can’t just wait for the funding.”

DR. FRANCIS: Thank you. So we’re sort of past the three o’clock point, but
what we’re going to do is continue with this discussion actually. But I’d like
to invite people who’ve been sitting around in the sort of audience or not
really audience, former earlier in the day participants. If you’ve got thoughts
you want to make sure that we don’t lose hold of, because what we’re going to
do is continue this discussion, but with an eye to what are our next steps.

DR. GREEN: With apologies, could I jump the line because I’ve got to go.
And could I just notice one thing from the afternoon, and as people are getting
organized to talk? Is that okay?

DR. FRANCIS: Sure.

DR. GREEN: This last session, yeah, I’m taking it back to the title, the
community is a learning system for health, using local data to improve
community health. I think this links back to the morning session very nicely,
and leads me to conclude that enabling committees to be a learning system for
improved health using local data, it is much more a sociologic than a
technological problem. And secondly, that the whole country is simply missing a
sustaining enterprise for communities to improve the local health. The
country’s invested in projects that come and go, but the communities need an
enduring mechanism and a way to sustain the opportunity to work together with
the healthcare providers, as were so beautifully presented this afternoon in
those community health centers.

But we are missing a place to pull the provider community, the
administrative data and the insurer community. There’s no place for them to
come together. And I thought that just literally leapt through the phone lines
out here today, listening to people talking. So that’s my contribution to the
follow up discussion and thank you for letting me do it. may I jump the line?

DR. FRANCIS: Thank you very much for being with us, and I’m sorry you’ve
got to go. Other comments?

DR. FOLDY: Seth Foldy, CDC Atlanta. I’m going back to the morning’s
discussion on security, privacy, confidentiality, and only one of the speakers
is still left. But something for the group to consider, the word
“consent” didn’t really arise during the morning’s discussion. But it
is coming up a great deal in discussions around the sharing of health
information, not just health data for various statistical or community sharing
purposes. But once again, around the sharing of information between two
clinicians, or between clinicians and public health. And it seems that some of
the things that are driving this new discussion, there are some discussions out
there about actually increasing the level of restriction on the exchange of
information, for example, between two clinicians caring for the same patient.
The requiring of higher levels of consent, or more explicit consent than is
currently encoded in the HIPAA legislation rules that have been in effect so
far.

And I think there’s a number of things going on around this. One is an
interest in addressing the issue of, again, our patients being given the
appropriate level of control over how their data is being used. There’s some
discussion that I’m hearing about an interest in trying to make it far more
granular which information might be consented for sharing, and which
information might be withheld, which I think raises lots of very interesting
and difficult issues regarding downstream effects.

I think one of the speakers, Rosamond, I was very glad to hear her bring up
the balance between privacy and other goals, other goals that may be very
important to the same patient, such as making sure their doctor knows what
their allergy list is, making sure that they don’t suffer a drug interaction
that might’ve been avoided, so there’s always a balance between privacy and
other goals, such as the quality or safety of healthcare, and larger social
goals, like public health awareness and community health threats.

So where am I going with this? So we do hear more talk about more consent
requirements on the exchange of health data. And I have heard even the work of
this committee cited sometimes as an important underpinning for the need for
those discussions and the need to reopen the discussion. I think there are some
really critical issues. One is, there’s been a lot of discussion about people
issuing consent about the future use of data ongoing. That strikes me as
something that’s very difficult for people to imagine how they would want their
data used a year from now, two years from now, when they’re unconscious, when
they’re awake. It seems like a very difficult thing to talk about.

There is a lot of discussion about people establishing a consent today
about the use of their data years down the road. There’s also discussion out
there about trying to come up with the new technical solution around consent,
and those of you who’ve studied the PCAST report are aware of this. I think
there is a hope being held out, and I don’t know how robust the hope is yet,
that you can take this kind of granular consent and attach it to a particular
piece of data and make it available into the future.

So I would just say that, this morning’s discussion touches on the ongoing
issues of consent that we’re starting to hear more about today. And the
conversations about consent, touch very much, I think, on the work of the
committee. And I’m hopeful that it will start to try and contribute to the
discussions going forward, because I think it actually has very broad
implications. If our speakers would have been here, I would’ve said, “So,
you didn’t say much about consent. What do you have to say about consent?”

DR. FRANCIS: If I could make just a comment sort of for them. My thought,
and I’ll just put this out as a group question is, what we’re here about today
isn’t patient care. It’s about uses of data, essentially for public health and
particularly plugging back into the community for local area health
improvement.

I think one of the questions on the table is whether consent is a relevant
model, particularly when there’s not a direct link to an individual. So those
could be separate questions, or whether there are other models that are better
models for protecting people. And so, that’s sort of partly what is an
alternative to individual consent and opt out is an alternative to individual
consent transparency. I mean, maybe that’s a coordinator, is an alternative to
individual consent, some kind of community-based participation in research
design, and then people get to opt out, if they want to, but those are some of
the models that are out there.

Or it could be that, if there’s community-based consent, we don’t even
have, I mean, I don’t know. How would we make sure we protect, in light of what
our structure is and whether we don’t have, if we’re not insisting on
individual informed consent at every moment. Those are the questions we’re
really trying to explore today.

DR. FOLDY: And if I could just add, I think people’s hopes that there will
be a major convergence of health information, collection and management systems
means in part we may not have such separate systems in the future for
collecting community health data from collecting individual health data, so
that the discussions necessarily becoming intertwined, unless they’re carefully
dissected out and discussed.

DR. FRANCIS: You were so close to me, I did not see your hand. Sallie?

MS. MILAM: Just playing off of Seth’s consent discussion, one of the
interesting threads that I found from panel one was around the consent issue.
And I’m looking back on my notes from Michelle Justus, and that was around BMI.
And with regard to consent initially, they had no consent at all. And then,
they moved to opt out, but no notice was required, and the opt out was really
onerous on participants. It required a written letter from the parent, to send
it into the school system, which from a consumer perspective, it’s just too
much work. Most people won’t do that much work to opt out.

And you compare that with Jeff Botkin’s response around blood spots, and
you know the survey data reflected that people really felt it was important to
have a meaningful discussion and understand what their information was being
collected for. But he also said that he actually personally thought that opt
out was fine. And I think what he was inferring that as long as there’s
meaningful notice, and people understand what’s going on, that they’re fine.

So the questions that I noted from my self were, this is a big difference
between Arkansas, who with no notice and they had no real fall-out from no
notice, but the issue was weight, versus Utah with blood spots, and the people
wanted notice, so that is a lot more sensitive information. So I was wondering,
is the dichotomy about sensitivity of information, or is it about what Jeff
also refers to the lawsuits that resulted around blood spots where people
didn’t know what was going on. So is it sensitivity is tied to real issues then
tied to action, in other words, suing? Or is it something else all together
where we have different cultures of privacy around the country and people are
reacting differently? So those are some of the thoughts that I had, at least
from the first panel.

DR. FRANCIS: Sallie, I can give you a little bit of an answer on the Texas
blood spot. I think two things that really concerned people were, in one case,
the thought that the data had been used for commercial purposes. And in the
other case, and I can’t remember if it was Jeff or Rosamond who mentioned this,
it was Rosamond, the use for law enforcement. And so some of it, at least some
of the concerns weren’t the sensitivity of the data, but the use to which the
data was going to be put, I think.

MS. BERNSTEIN: I know Larry’s gone now, but I think when he recommended
that we talk to the Arkansas people, and we didn’t have enough time to ask Miss
Justus, who I assume is not on the phone.

DR. FRANCIS: Let’s just check, is there anyone new on the phone?

MS. BERNSTEIN: Or who joined us from earlier in the day? Yeah, my sense was
that the very beginning, so remember that she told us that there was a very
short time they had to get the funding, get the legislation and then actually
do the thing, all in the first year, that there was actually some kind of
outcry at the very beginning, before they really got up and running, and the
second year, that there was some kind of backlash from the parents, after which
they got an IRB together and did a bunch of things. And she didn’t talk about
that, but that would’ve been my question to her because that’s what I
understood happened. I could be incorrect about that, I don’t want to say that
I know it. But my understanding is that there were, in fact, some pushback in
Arkansas before they got the thing off the ground.

And after that point, they had a procedure going forward. I don’t know if
anybody around the table knows about this. There were various nods and sort of.

MS. MILAM: But Larry did ask her that question, was there any fallout from
it. And if there was, she may have mentioned it to you, but she didn’t give
that response when Larry asked in front of the group.

DR. FOLDY: Did she not say that between year one and two, there was a
change?

MS. BERNSTEIN: She said later there was a change, yeah.

DR. FOLDY: So I’m thinking something triggered it.

MS. BERNSTEIN: Yes, when he did ask her about that, I thought she was
talking about, at the end, after they had collected the information and the
disclosure of the information or whatever, but I don’t know. So maybe one of
the things is to go back and I can go back to her and ask her specifically
about those things.

MS. MILAM: Well, if we feel like we want to follow up on consent, I know in
the past, when we’ve talked about consent, we felt like the policy committee
was taking the lead with that and we were going to focus on other things.

MS. BERNSTEIN: Well, not just about consent, just about what was it that
they did that got the community to buy in. So we were talking about
alternatives to consent, sort of can you engage the community in some way, get
political buy in, get legislation, get other ways that might not require
specific consent from individual people, because as we said, it’s burdensome
and administratively difficult and so forth. But the question is, what in fact
did they do? They had legislation, they went through the schools, they did go
back to the parents with this written report that they gave examples of. But
it’s worth just making sure that we’re clear about what happened there in that
program. I felt like I didn’t have enough time to talk to her. There were some
more questions, maybe around the table. So we can do that, though, we can go
back to her.

DR. SUAREZ: Yes, thank you. I just wanted to follow up on this point,
because I think there’s a common thread in a lot of this activities,
initiatives, project, programs. And that is that, there’s usually a state
regulation or law, or some sort of a regulatory activity that creates the
ability for the entity that’s going to collect the data, to collect the data,
and then define some of the parameters on how the data can be used.

Now, what we are seeing, at least going back to some of the comments that
Marjorie said, 15 years ago, there wasn’t necessarily that level of degree of
expectation in the community of transparency and sensitivity and ask me first
and everything. And so, a lot of activity that was going on back in those days,
fell generally under the authority of state agencies to do this type of efforts
and projects.

But now, more and more, we’re seeing the need to create legislation for a
specific type of program that deals with the privacy of that program. And my
concern, of course, is that within a state, there’s hundreds of programs, and
each program handling privacy a little bit differently because, well, this
program we use opt-in and this other program we use opt-out. In this program,
we ask consent first and only for certain things. It’s going to create even a
more difficult patchwork inside of state regulations that drive the privacy
process across this initiatives.

And we are just talking about public health. I’m focusing on public health,
because I think clinical care and care delivery and all that is now, there’s a
lot more regulated around that and there’s a lot of other parameters. But
public health is now, in my mind, and that kind of is our focus really because
the policy committee doesn’t really necessarily get too much into the details
of public health, with respect to privacy. But I think that is what is going to
be the challenge, is the creation of this multiplicity of approaches on privacy
for specific public health initiatives. And I think that’s biggest concern I
have.

MS. KANAAN: I hope it is all right for me to offer an observation. I think
that in some ways, what we learned from the latest presentations, particularly,
I think, the Denver one, is that sometimes we see these questions of privacy,
confidentiality, consent, etcetera, etcetera, most clearly when we look at them
in a broader context, and not just at the processes around consent or no
consent and so on. And it seems to me that, we haven’t called out the whole
idea of activation, but I think that’s really, really an important piece here.

And you talked about as community ownership, but looking at it from the
individual level, activation in terms of health, I think is a principle that
now is recognized. We’re talking about even a broader sense of activation,
which is the individual patient as a part of a community. And I think that at
least some of these projects that we’ve been looking at or these initiatives,
are helping people understand themselves as part of the community, and that
including, in many cases, leading them, empowering them into a kind of advocacy
around health and environmental determinants of health. And I think that needs
to be recognized as a part of what we’re talking about here, not just the
consent practices and the data handling practices.

DR. FRANCIS: Could I ask the two of you just one more question that’s kind
of specific? I know when we heard the Arkansas example, I mean, obviously the
thing they did was they sent results back to parents. And one of the things
that worried them from a confidentiality perspective was kids getting
stigmatized when the kids were given the information and taken back. Now, I
take it in New York, the families got the information, so I’m interested in how
that individual feedback was handled and what some of the issues were around
protecting confidentiality or from teasing or stigmatization and so on.

Maybe I’ve got this wrong, but my sense is that, in the Denver one, there’s
no specific health information specific to people, to individuals. So you’re
not, for example, going door to door and taking people’s blood pressure, or
figuring out body mass indices or anything like that. What you’re learning are
people’s perceptions of whether the streets around them are safe, but you’re
not feeding back information to individuals?

DR. MAIN: No, though Janet briefly talked about the childhood obesity
study, where we actually had people at the door, collecting data, doing height,
weight, face to face. Again, I’m not sure, I don’t think there were actual.
They did get feedback around also, they did fitness testing and some things,
but I think it was right there at the door. They didn’t get anything later in
terms of feedback.

In our surveys, we actually ask about, we sort of replicate. A lot of our
data are similar to the BRFSS, in terms of questions where it’s self-report
data. So we weren’t taking blood or any other clinical information in ours. It
was more self-report, some of which was about perception, some of which was
self-reported health behavior and other things.

DR. FRANCIS: Yes, I was just wondering, basically whether that kind of
information, rather than what’s in the grocery store, raised more concerns and
different kinds of confidentiality concerns. And I really meant to have that be
for Kathy, too.

MS. ALEXIS: With our school systems, particularly with the school-based
health centers, the providers would call the parents directly. And a lot of
times, it was like nurse practitioners from the schools. They would call the
parents directly and say, “This is the BMI, this is the child’s weight,
this is what you need to do, these are some suggestions of resources in the
community.” There was in-depth conversation with the provider and the
parent. And this was mostly for the sites that participated in the project.

We did not hear of any confidentiality issues, we didn’t hear of any
teasing, because we felt that the health centers and the school-based health
centers, they did really well in not really having the children stand out in
any way. For example, the scales were not in the waiting room or anything like
that. It wasn’t in a public arena. They were mostly in the exam rooms, so if
there was a conversation to be had with the child, it was done privately.
Nothing was done outside, in front of their friends or anything like that. So I
think in doing that, it minimized any possibility of teasing that would come
directly from the assessment of the provider.

But I think, like I said, with the health center that did their
peer-to-peer mentoring program, that helped a lot, when it came to the teasing
part, because it’s kind of like, “Well, that guy, he was large and he lost
weight, and now, look how cool he is. He got money to teach us about how to
lose some more weight.” So it really not only raised the self esteem of
the child itself, but it did put him in a place where he can now be of a mentor
to his friends. So I think that was really one of the positive aspects of that
project.

MS. GREENBERG: Your question started making me think about something, and
then just the answers. Well, a year ago or so, this subcommittee had a hearing
about the sensitive data categories or whatever, and adolescent health was a
major focus. And being the mother of a daughter who was once adolescent,
somehow they all have to pass through it, I guess, but weight can be a very
sensitive issue. Even if you say nothing, it’s sensitive. I mean, if the mother
says nothing or the parent, it’s sensitive to the child, and particularly to a
daughter. So I’m thinking of this dynamic where, was this also up through the
adolescent ages, where the nurse or practitioner called the parent?

MS. ALEXIS: Absolutely.

MS. GREENBERG: And how did they engage the child? I could see this being
rather inflammatory, and I just wondered how you handled it.

MS. ALEXIS: Yeah, one of the school-based health centers that participated
was a high school. And it was mostly elementary schools, middle schools and
high schools, and I would say the more challenging population was the high
school. And I think that has to do, there are a lot of social issues behind
that. The community that we were working in, there were just other problems
outside, kind of specific to what was mentioned earlier. There are so many
other social issues going on in which healthcare was just not priority for
these kids. We’re not even talking about the parents. Just for the kids
themselves, taking their health or eating well was not really the first issue.

But I feel that with the younger population, it was easier to share the
information on healthier eating and physical activity. But the problem was
really how to change the culture in the school itself, because you can’t really
ask a child to exercise more, where there’s no recess, or there’s nowhere for
them to go out. I mean, I grew up, my elementary school, our recess was the
street. They would close down the street and we would play outside. That’s the
reality for a lot of schools. And so, if you don’t even have that opportunity
to, let’s not talk about a playground, if you don’t even have the opportunity
to just go outside, it’s hard to have that conversation with a child or with a
parent to say, “Your kid should do more exercise wise.” So I’m not
sure if I’m really answering your question, but I think there it really
depended on the age range. The high school’s was much more difficult.

MS. GREENBERG: With the older children, I would think that although a
parent may observe that he or she thinks this child is overweight, or at risk
of being overweight or even obese, people make those distinctions, many parents
of adolescents have no idea what that child actually weighs. And the child does
not want the parent to know what he or she actually weighs. So often when you
take an adolescent to a doctor’s appointment, the parent isn’t even in the
room, and then, afterwards, there’s some discussion. But I’m just wondering if
the child was told they were going to tell the parents. I don’t know?

MS. ALEXIS: No, the child is told. I know that at the health centers, the
child is told that the parent will receive a call from the health center to
discuss the result of the physical, to discuss the results of the BMI and what
that means. The child is told that, so it’s a matter of what happens once the
child gets home. I don’t know.

MS. GREENBERG: There’s some interesting issues there that go back to the
whole discussion of adolescent health.

DR. FRANICS: And part of it, a core to the discussion of adolescent health
actually was that, in a number of states, the law gives different access
rights. For example, mental health information, unless there’s an immediate
danger, or reproductive or sexually transmitted disease information, without
the adolescent’s consent, the parent in a number of states, doesn’t have a
right to see that. So unless you have separate ways of handling some of those
types of information, you can’t even run a patient portal into an electronic
medical record for adolescents. So that’s part, that’s the kind of information
we were hearing.

One of the questions that I think we should also just have out on the
table, and I don’t know. We’re beginning on shy on time for a number of people,
but I think another issue that has been of concern with respect to consent,
non-consent, opt-in, opt-out, is shifting uses of data.

So, if something’s given for commercial use, or if something’s given for
research, and then it’s given for commercial use. But even within data types,
so I know discussions, for example, cancer patients entirely happy with the use
of their data for research purposes in cancers and related illnesses, but not
so happy with the use of their data, even for, say, mental health research.

And so I think one of the things we’re going to need to continue thinking
about is appropriate levels of transparency about data uses, and changes in
data uses. I mean, I wonder, for example, if the BMI data then got used for a
sexually transmitted disease study. Well, it would be really interesting to
find out whether the kids with higher BMIs are more or less sexually active.
That might be an interesting thing to find out, but that might be something
that would really raise hackles, right. So we’ve got Seth and Denise and Kathy.

DR. FOLDY: You are starting to pull apart three strands that I’ve heard
evolving in the discussion. And I think that Rosamond talked about this very
nicely, that when you’re talking about how data is used, that’s a different
question than talking about, and I think this came up when we were talking
about the data bases, the multi-pair data bases. So there are several methods
and there are several outcomes. Aggregating data, so you can’t de-identify it,
is one kind of method and one kind of outcome, and it has one set of effects on
what we can do with information.

Consent is another strategy. It has other effects on what we can and cannot
do with information. And then, really trying to control who uses the
information towards what purpose, which probably is not easy to engineer in
advance, and maybe even perhaps more of an enforcement. But in the end, it
probably involves trust, too, is a third approach with its own ramifications.

MS. LOVE: I come at this from a slightly different view than some of you
and I concur with Seth. And it brings me back to the large aggregate databases
that I’m familiar with, that we work with. And that’s why, I think we just have
to do a better job of coming up with better analytic products or database
designs, that have embedded intelligence to answer some of the questions that
those databases can answer. And the patient won’t even know that their data are
being used, and they frankly probably don’t care because it’s so removed from
their personal record.

And so, I really think getting smarter de-identification algorithms and
embedded intel, together will take away some of this opt-in, opt-out on the
personal health information, because I think that’s going to be onerous to
aggregate it for each individual study. We’re going to do a BMI study, we’re
going to send a query out, opt in, opt out, aggregate the data for one-time
use. I think that’s going to be onerous, and so we probably need both. But I
agree that we need a better aggregation methodology.

DR. FRANCIS: Kathy, I’d love to ask your reaction to the hypothetical.

MS. ALEXIS: In thinking of how we collected the data for our projects, as
was stated earlier, we did all of our own collection. We created our own data
collection tool that we used and we shared with the health centers. The health
centers now use it as a way of creating their own dashboard. Unfortunately,
because the primary care association is mandated by HRSA to not share data, any
data that we share must be de-identified. And that would be any sharing the
information with our funders, sharing the information with anyone, we really
can’t identify a particular health center to that data.

But I think in essence, we can say in this community, for example, a
community in Queens, they had about 75 percent of that population of their
children that was classified as obese. That was information we can share. But
then, if we wanted to kind of delve down a little bit deeper with that, there
were a lot of challenges. So I agree with other suggestions where we need to
have a wider standard as to how to use that data, and probably open it up a
little bit more so that we can see what it really says.

DR. MAIN: I think one of the issues that has to be put on the table, too,
is I’m taking your example, and what would happen if all of a sudden, what was
originally data collected for obesity was used for, I can’t remember what we
were using it for.

DR. FRANCIS: Sexual activity.

DR. MAIN: Yeah, STD’s. And my first reaction to some of that was, I looked
back at Kathy and I thought, here’s the deal. Kathy went in, developed
relationships, sort of laid out this long-term infrastructure for doing work
with community health centers and communities for a long time. Something like
that, it’s gone, right? And so, you will never have the opportunity then to go
back and do a really great study on STD and obesity.

And so, I think it’s thinking about the big picture. I think your point
about use now, use later, and you’re not going to know what happens later, but
you have to be really careful because you engage in this contract with people.
And honestly, even words like “embedded intelligence”, I think I
would not use that because all of a sudden, it’s like, oh, you’re doing
something. That’s sort of what got us here in the first place and the whole
trust thing. So just being really careful about how think about it now and
later, because these relationships, as Walter said earlier, these are
long-term. This isn’t a project, this is really a commitment. And so, my first
reaction is, oh, I worry about Kathy and her relationships and the community
health centers and their relationships with people, and the school-based health
centers.

DR. FRANCIS: Thank you. I think this may be a really great way to say what
our next steps should be, which is we’re going to start with an outline, with
Susan’s help, of what we’ve heard today about issues for trust, and
methodologies, things that seem like likely to work, things that seem less
likely to work. And then, see where we will be following up. But this is going
to be part of a report, or at least a sketch of a report, that will be at the
June 9th Health Data Initiative Summit, I think that is what that’s called.
Some of us will be there, and then the next step is going to be, we would
really like to come out of this with some guidelines for good things to do in
using the kinds of data sets.

I think we’re also going to want to look at questions like what can make
data sets more useable, and what kinds of recommendations should there be out
there?

MS. BERNSTEIN: Are you anticipating that you, or is anyone on the committee
anticipating that you might want to have another workshop in this series?

DR. FRANCIS: It’s quite possible.

MS. BERNSTEIN: I’m just throwing the question out there.

MS. GREENBERG: Just being sort of very specific now that today’s the 12th
and that meeting is June 9th, so we have the report from February 8th, that I
think has been vetted, etcetera. It’s going to go up on our website, if it
isn’t already there, and it’s certainly in a condition that we can distribute
it. The question is, there isn’t enough time to get this one, integrate this,
necessarily, but could there be some key findings or observations? Is the
subcommittee willing to work with Susan on that, so that maybe we could have at
least, if not integrated right into that document at this point, an additional
smaller document? That would require obviously on Susan’s part, putting this
together, and then some teleconferences, I think.

DR. FRANCIS: That would be our hope.

MS. BERNSTEIN: So I understood when we scheduled this meeting, that the
point was to have it, realizing that it was later than we wanted to have it
from the original scheduling, so that we would have sort of talking points or
bullets or whatever it is, to participate adequately in that meeting, not
necessarily to have a report written. Although, you know, if we could do that,
that’d be fabulous. I think to have enough information for somebody to
participate in the June 9th meeting based on what we did here, as representing
NCVHS.

MS. GREENBERG: Initially, we actually thought that we were being asked to
make some kind of presentation at that meeting. But it turns out, that’s not
really the type of meeting that it is. It’s a lot of demonstrations and a lot
of workshops. And so, what I have kind of worked out with Todd Park and Greg
Downing, is that we will have several members of the committee will be there.
Leslie’s going to be there, you’re going to be there. I think you’re not able?
Are you going to be there, Paul, and Justine. And Ed Sondik, and you can attend
whatever sessions you want, but I would ask you all to go to the Community
Health Data, at least some of you, to be at that Community Health Data session,
which Ed Sondik is organizing. And we can make available at that session a
document.

So the question is, we certainly have the document that’s came out of the
February 8th meeting. My question was, what you want to add to that, either to
that document or as a suite of documents or whatever, given the period of time
we have. Now, also obviously, you can speak up in workshops and whatever you
want to bring to it. But we don’t have the time, I don’t think, to fully
integrate today’s session into that document.

DR. SUAREZ: Is that document already approved by the committee?

MS. GREENBERG: It went out.

DR. SUAREZ: So it has been formally approved, so it’s ready for release?

MS. GREENBERG: Yes, we sent it out. It doesn’t have recommendations in it,
but we sent it out to the full committee. And it went through the
subcommittees, I think it went to the executive subcommittee. And if anybody
had any issues with it, we can stamp it “discussion document” or
something.

DR. FRANCIS: My thought in reading it was that it was an initial, the best
draft from the February meeting. But I had always understood that some of what
happened here would be.

MS. GREENBERG: It would eventually go into it, and that might be a final
product, that would then be sent to the department as approved, with a cover
letter that might have some actual recommendations.

DR. FRANCIS: Or that there might even be a need for another workshop,
because the goal of this is best practices in the kind of feedback loop
community research together with how to be appropriately protective so that we
don’t have trust disasters, of the kind that happened in Texas with the blood
spots, or that we were jokingly referring to, or not so jokingly, with research
that ended up surprising people.

MS. BERNSTEIN: I assumed that the document that we had from February was
incomplete without the rest of the pieces of the different workshops.

MS. GREENBERG: Well, it’s sort of a part one.

MS. KANAAN: Right, it was a snapshot of a particular moment in time. And
Leslie and I actually talked on the way over this morning about creating a
maybe one-page document with just the key bullet points from this discussion,
and these presentations initially.

MS. GREENBERG: It seems like it’d be a lost opportunity not to share that
document that’s already been.

DR. HORNBROOK: Leslie and Marjorie, this is Marc Hornbrook. I’m a member of
the committee. I have no conflicts and I’m from Kaiser Permanente Center for
Health Research in Portland, Oregon. And normally, I would be there in the
room, except that I’m trying to get a grant application out tomorrow. The thing
I was thinking about is the health information exchanges. Even though they are
designed for business purposes, the fact that medical information, as these
things work, flows back and forth across lots of different actors, pharmacies,
hospitals, insurers, FHQCs, government agencies, et cetera, Medicare, Medicaid,
state health insurance. And then these new health insurance exchanges, which
evidently are going to be a way to bring in 32 million US citizens.

It raises this notion of community health assessment, though aggregated EMR
data. And Marjorie, I’d sent you an email of an example of an organization
called OCHIN. That is tying together FHQCs through a common electronic medical
record. It happens to be the Epic vendor system. But they have a research arm,
and as a non-profit, they can get grants. So they’ve been doing research
projects. The problem is, of course, they don’t cover hospital care. They only
cover outpatient care in these FHQCs.

But we’ve been looking at the data and you get a very different kind of
picture of community health when you look at the clinical care, as opposed to a
community health survey. But I’m just wondering, somewhere in our strategic
planning, you should come back to this when we see more development of these
kinds of systems and data interchange developments, as we’ve been promised
through the Office of the Coordinator.

DR. FRANCIS: I think that’s a very good point and it’s actually part of why
I was asking whether any of the groups had integrated clinical data. So I think
we’re at a point where, we’re losing people with airplane needs, and so
including myself, I’m sorry to say. We’re going to bring this to an end and
thank everyone, but most especially, I need to say to Maya Bernstein, thank
you, thank you, thank you.

MS. BERNSTEIN: When I said thank the staff, I didn’t mean me.

DR. FRANCIS: I mean you, and I also need to say the same thing to Gayle,
who held everybody’s hands and to all the other staff.

MS. BERNSTEIN: To Jeannine in particular.

DR. FRANCIS: Yes, Jeannine, the person who would emails us and says,
please, please, please, get it done. Thank you.

MS. BERNSTEIN: So we’ll set up some phone calls and we’ll figure out, over
a conference call, if we’ll have a new workshop and when that might be and what
our next steps are.

(Whereupon, the meeting adjourned at 3:55 p.m.)

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