American Health Information Community

Population Health and Clinical Care Connections Workgroup Meeting #16

Thursday, March 29, 2007

**Disclaimer**

*The views expressed in written conference materials or publications and
by speakers and moderators at HHS-sponsored conferences do not
necessarily reflect the official policies of HHS; nor does mention of
trade names, commercial practices, or organizations imply endorsement by
the U.S. Government.*

[**\>\> Judy Sparrow:**]{.underline}

Thank you. And welcome everybody to the Population Health and Clinical
Care Connections Workgroup meeting. Just a reminder that we\'re
operating under the auspices of the FACA, which means this meeting is
being Webcast and a transcript and summary of the meeting will be
available within a week of its conclusion. Also there will be an
opportunity at the end of the meeting for the public to make comments.
And finally, most of the Workgroup members are here in the room, but I
believe some of them are on the line, so please remember to identify
yourself and speak clearly and distinctly while you\'re speaking. This
is so the transcribers know who to attribute comments to. We have a very
full agenda today. We\'re going until 3:30 in the afternoon. So I think
without further ado I\'ll turn it over to Dr. Lumpkin, the co‑chair.

[**\>\> John Lumpkin:**]{.underline}

I\'ll give Steve an opportunity if he has any opening comments. Okay.
Let me go through a little bit of logistics. You\'ll notice that we have
a set of testifiers, and let\'s see we\'re going to do lunch at 12:15.
Is that correct?

**[\>\> Judy Sparrow:]{.underline}**

Yes.

[**\>\> John Lumpkin:**]{.underline}

Okay. And then we\'ll finish with the afternoon panel, which is going to
focus more on laboratories. As an introduction to the panel, if we can
get the panelists to join us, maybe if we can go around the room and do
introductions so people on the line can at least recognize the voices
for the members of the committee and then we\'ll get the panelists in
position. I\'m John Lumpkin, Senior Vice President, Robert Wood Johnson
Foundation.

**[\>\> Steve Solomon:]{.underline}**

Steve Solomon, Centers for Disease Control and Prevention.

**[\>\> Shawn Fultz:]{.underline}**

Shawn Fultz, Department of Veterans Affairs.

**[\>\> Brian Keaton:]{.underline}**

Brian Keaton, president of the American College of Emergency Physicians.

**[\>\> Angela Fix:]{.underline}**

Angela Fix, with ASTHO.

**[\>\> Scott Becker:]{.underline}**

Scott Becker, the Association of Public Health Laboratories.

**[\>\> Amy Helwig:]{.underline}**

Amy Helwig, Agency for Healthcare Research and Quality.

**[\>\> Paula Soper:]{.underline}**

Paula Soper, NACCHO.

**[\>\> Erik Mettler:]{.underline}**

Erik Mettler, Food and Drug Administration.

[**\>\> Judy Sparrow:**]{.underline}

Anybody else on the telephone?

**[\>\> Jennifer Macellaro:]{.underline}**

Looks like we also have Laura Conn from ONC, Ed Sondik from the CDC, Jon
Einbinder from Partners, Healthcare, Annie Fine from the New York
Department of Health. Did I miss anyone on the phone? I think that\'s
it.

[**\>\> John Lumpkin:**]{.underline}

We\'ll go to our panelists and ask themselves to introduce themselves\'s
they speak. Couple of opening comments. As you heard, we are, we have a
very full panel. Each member of the panel has been asked to stick to 10
to 12 minutes, and in order to enable us to get through our agenda I may
have to be a touch obnoxious about that. So I\'ll give you a warning
when you\'re out of time and need to start wrapping up.

Just a couple of opening comments to put this into perspective. And the
panelists should feel free to, if necessary, modify their comments if
they can do that on the fly. This group began with the Biosurveillance
Workgroup, giving advice to the AHIC, which led to some recommendations,
particularly around case reporting. We\'re also in the process of
developing recommendations around adverse event reporting, so in many
ways that takes care of the data collection piece about that.

What we really are going to be focusing on in our next set of
recommendations is that now you know something is happening how do you
manage that? Part of that aspect, of course, in any outbreak or, whether
it be manmade or man-generated or a naturally occurring event, is to
continue to identify the scope of it, identify those who are engaged,
and, as part of the management, to do contact tracing, outreach, and
treatment. Other aspects of dealing with mass events where multiple
people are involved is how do you address the needs of those
individuals, how do you get prophylactic antibiotics, for instance, how
do you get, indicate a therapy? How would you manage bringing in
vaccinations if you\'re trying to manage that kind of outbreak? Those
are the kinds of issues we want to focus on, particularly related to the
data needs. Where are the needs to get data in from the clinical care
setting and where are the needs to get information and knowledge out to
the clinical care settings so they can become integral partners in
assuring that the population is first, protected, and second, for those
who have in fact been affected by this can get, receive the treatment
and care that they need. So with that we\'re going to jump into our
panel and Paula I think you\'re first.

**[\>\> Paula Soper:]{.underline}**

I am. Thank you. Can I get the first slide, please?

**[\>\> John Lumpkin:]{.underline}**

Just a word of warning for those who are doing the slides, having done
that, there is just a touch of lag, because it needs to go from here to
the display system and change, so \--

**[\>\> Paula Soper:]{.underline}**

I'll be patient.

**[\>\> John Lumpkin:]{.underline}**

\-- be patient.

**[\>\> Paula Soper:]{.underline}**

Thank you very much for the opportunity to testify today. We hoped to
have two local health presenters, but it was surprisingly difficult to
identify someone, an additional local person, to present in addition to
New York City because our members were just incredibly, incredibly busy,
I think it\'s because we have them running and they have their own local
obligations. So I did get input from our preparedness committee, our
infectious disease work group, our informatics work group and our
preparedness event practice centers. So hopefully I will be able to
reflect what they have asked me to testify about today and not put too
many of my own opinions in there. But that\'s probably not possible.
Next slide, please.

I did want to provide, it\'s probably very difficult to see up on that
slide, but I did want to provide some background information about the
role of public health in outbreak and event management. Local health
departments tend to be the frontlines for outbreak protection as well as
management of the outbreak and events. Certainly this differs state to
state. State reporting laws may require reporting to a local health
department, to a state health department, and there\'s some differences.
But by and large local health departments are really the frontlines.
Certainly states take on a greater role when data or the outbreak
actually goes beyond the capacity of a local health department or will
cross jurisdictional boundaries. These are some of the areas that local
health departments cover with surveillance and epidemiology. You can see
that by and large most health departments are actually doing the
environmental and the communicable disease surveillance by themselves or
with the state health department. So it\'s a primary area of
responsibility for state health ‑‑ local health departments. Next slide,
please.

We were asked today to present about four different scenarios, and I did
just want to mention that not all local health departments will actually
be responsible for these different types of outbreaks. And especially
with environmental. Food-borne may fall under environmental, natural
disaster may fall under environmental, vector-borne may fall under
environmental, and not all local health departments do environmental.
Though it tends to be that more local health departments do
environmental than state health departments. Next slide, please.

There are essentially, there\'s a formula for how outbreak
investigations are done. We know this. And I\'m not going to speak too
much to this. But we know that detection, identification, investigation,
management, containment, and I\'m not going to talk all that much about
containment today because I know that our next hearing is going to focus
more on that. But for detection, certainly active and passive
surveillance where data is coming from laboratories and hopefully from
private providers and from hospitals. In the passive surveillance, we
hope we get the data. In active surveillance, we\'re actually being much
more diligent about trying to get the data from the laboratories and the
clinical setting. And that would be the case reporting, the typical
information that you\'re asking for in case reporting.

The investigation is where we really have to try to get more information
to gather, to find out about the case, to see if this is potentially an
outbreak, to actually dig into the data some more, do interviews with
the potential cases. And of course prophylaxis and community disease
containment are methods of management and containment with isolation and
quarantine; vaccine, antibiotic, and anti‑viral administration;
education; then behavior modification. The vaccine, antibiotic, and
anti‑viral administration would definitely be an area where health
departments are going to need to both coordinate with the private sector
but also with their state systems as well. Next slide, please.

The needs for data differ from different types of outbreak, however,
there\'s really a common corset of data that we need, and I think
probably my fellow presenters in the field are going to speak a bit more
to that. But we know we need demographic information. And that certainly
can come from private providers and should come from the private sector
and from laboratories when a case report is made. It\'s going to be
important if it\'s a communicable disease to get contact, information
about their contacts. And that probably is not going to be able to come
from the clinical setting. Information about symptoms obviously it\'s
going to be coming from providers, not laboratories. Information about
treatment for the communicable disease, what type of drugs were
administered. And then exposure, you know how they were exposed probably
is not coming from the clinical setting. In terms of ‑‑ next slide,
please ‑‑ nope, sorry actually it was a slide back. I\'m sorry.

In terms of a vaccine-preventible disease, information about vaccine
coverage rates for the community is going to be important. So that\'s
where gathering data and immunization registry from the clinical care
setting is going to be critical. And also to be able to have access to,
for individual cases, for their vaccine history. I know that was a huge
issue in the mumps outbreak, multi-state mumps outbreak last year,
trying to get the vaccination histories and determine if it was a
vaccine failure issue, if kids simply weren\'t, or adults simply
weren\'t vaccinated. So that\'s going to be a major area where a lot of
electronic exchange of data would be very beneficial for an outbreak.

In terms of a food-borne outbreak, obviously the laboratory data is
going to be very critical there. But exchange of data with FDA is going
to be very important to be able to both get that data, that information
in from FDA into local health departments and get information sent out
to private providers about treatment protocols and what they need to be
looking for. Next slide, please.

We were asked to identify if there were any issues with or challenges
with getting access to clinical information for an outbreak or event
investigation. And we heard quite unanimously from our membership that,
no, there is no problem, that legally they have the authority to get
into patient records to get the data that\'s necessary. However, some
health departments are finding there\'s a perception issue with HIPAA.
That some providers just simply either don\'t want to open themselves up
to potential liability or just simply aren\'t aware that public health
does actually have the right and the legal authority to access data
under HIPAA. Next slide, please.

We were also asked to identify the potential of health information
technology for data exchange. And despite the work, for many years now,
of public health around electronic disease reporting, unfortunately this
is still primarily a paper and pencil and snail mail type of endeavor.
Many states do have disease reporting systems that are currently being
used by locals. However, these systems at this point often do not have a
module that would allow outbreak management. And I know that everybody
is just waiting with baited breath for the OMS. That was actually heard
pretty unanimously from our membership, that something that allows them
to exchange information to be able to link data across cases and across
exposures and across providers is really critical and something that\'s
standards‑based and would allow for data exchange with the private
sector, private healthcare sector, as well as with their partners within
the public health arena at all levels. So we\'re waiting.

We did hear consensus that health information exchange has the potential
to reduce reliance on manual systems, but there\'s some doubt that this
will ever be a paperless endeavor. There\'s just simply some information
that you\'re going to have to pick up the phone and call the patient,
the case, and see where did you, did you travel anywhere? What food did
you eat? It\'s never going to be a seamless paperless endeavor where we
can just capture this information from the clinical setting. However,
easy access to the patient history and to the patient files with the
providers would certainly make things much easier. Right now most
everything is done by case, by chart extractions, going to the
providers\' office and looking for the clinical data, looking for the
lab reports, looking for the treatment protocols that were used. So
there\'s certainly a considerable amount of data that will actually be
able to come from the clinical setting but it\'s never going to be the
end all, cure all, there\'s still going to be a need for some additional
data gathering.

However, for the public health sector to fully benefit and the
healthcare sector to fully benefit from automated disease reporting and
outbreak management, a further investment really does need to be made in
local public health infrastructure. We have seen that most local health
departments actually do have systems that can manage WIC, manage
immunization. A lot of them are doing outbreak management systems but
most of these electronic systems are done with, at this point, Access or
Epi Info, they are not standards‑based and not able to easily exchange
information. Next slide, please.

In terms of the use of standards \-- I\'ll try to wrap up very quickly
\-- at this point we have found from data collection that we\'ve done
with our profile survey of local health departments, we\'re finding that
only about nine percent of our local health departments report having
implemented federal standards for health IT, which is concerning, and of
course, this was about two years ago, so movement may have occurred.

However, we did find that 29 percent of local health departments report
using electronic health records. So we\'re not sure if these health
records are not using standards, if perhaps health departments just
aren\'t aware of using standards, but it seems that those health
departments that are aware of it are making purchasing choices based on
that.

If we could just skip to the slide titled Data Exchange with RHIOs and
HIEs, I\'ll just wrap up with this. We have a survey in the field right
now where we are surveying the use of RHIOs for exchange of information
for different types of data and we're partnered with the University of
Colorado as well as with ASTHO for this effort to survey local health
departments, state health departments, and RHIOs. We surveyed about 450
local health departments. At this point 103 have responded and of that
42 percent say they have some involvement with RHIOs. And of that, 19
have said they are actually exchanging data, clinical data through the
RHIO. And by and large, next slide please, they are using this for
disease reporting, for surveillance, for biosurveillance. So with the
jurisdictions actually using data exchange through their RHIO, they have
recognized that this is kind of the low‑hanging fruit to be able to take
advantage of this technology. Thank you.

**[\>\> John Lumpkin:]{.underline}**

Thank you. And we\'ll do questions of the entire panel when we get
through the presentations. At this point we\'re going to move on to
Marci Layton and Annie Fine, both with the New York City Department of
Health. They\'re on the phone.

[**\>\> Annie Fine:**]{.underline}

Yes, we're on the phone. Thank you so much. Can you hear me?

**[\>\> John Lumpkin:]{.underline}**

Yes, we can. Thank you.

**[\>\> Annie Fine:]{.underline}**

This is actually Annie Fine, not Marci Layton, testifying and I do very
much appreciate the opportunity to provide you with some practical
experience, perspective. I\'ve been an epidemiologist here over the past
11 years, and what I\'d like to do is give you a feeling how we manage
outbreaks at the local level, what our data needs and sources are, what
tools are currently available for data management, and where the gaps
are and some thoughts for the future. Next slide, please.

So I\'m going to review some recent challenging outbreaks starting with
the West Nile outbreak of \'99. Next slide, please. I\'ll move quickly
through the slides. I apologize. This outbreak was challenging in a
number of ways. First off, that it was a new and unexpected disease,
which, of course, required laboratory diagnosis that was not available
anywhere else besides in public health laboratories. Also it was a
regional event, which, as with many naturally occurring outbreaks, cross
jurisdictions, or intentional outbreaks, cross jurisdictions making data
management that much more challenging. We found it was extremely
challenging to track laboratory information during this outbreak.
Specimens were being sent to us in a somewhat uncontrolled fashion and,
with public health being the only game in town, private providers and
hospitals submitting specimens wanting diagnoses. We needed to link the
epidemiologic data with the laboratory data, and this was not a trivial
activity, especially since we didn\'t have any unique identifiers on
specimens that were received that we could match with epidemiologic
data. In addition, the fact that it was a huge media event and we had,
from elected officials, demand for data on a daily or sometimes more
than daily basis, really put huge pressures on us. And then, we tried to
do it with Excel and Microsoft Access and found them very much
inadequate. Next slide, please.

The next large event that we faced was anthrax in 2001. Next slide
please. And in this outbreak we were challenged by, as with many
outbreaks, having many, many more suspect cases than confirmed cases. We
had more than 600 suspect cases that required triaging, specimen
collection, et cetera, resulting only in eight confirmed cases, so
really a relatively small outbreak. But it was so complex because there
were site investigations that were needed at four major media outlets,
one hospital, and one postal service distribution center. And again we
had no system available at that time to manage the huge volume of data
that was related to laboratory specimens coming in from both suspect and
confirmed cases, from potentially exposed people at work sites where
there were nasal swabs collected, thousands of them. And then from many
environmental specimens that also had to be linked to patient exposures.
In addition, at that time there were more than 3,000 white powder events
which were, of course, false, but we didn\'t know those were false
threats at the time.

So the need to capture, describe, and easily retrieve relationships
between all these people, these sites, the specific exposures, the
environment, the courses of prophylactics that were administered, and
the laboratory results was basically very challenging and not possible
for us to do efficiently at that time.

Next slide, please.

In 2002 and 2003, as you all know, the next challenge we were faced
with, luckily not really as much here as elsewhere, was SARS. But,
again, a new and unexpected disease. Next slide, please. And in the
challenge with SARS, that was different, was that it was communicable
with a high case fatality, requiring complex contact tracing of both
home, work, and healthcare contacts as well as the need of case
isolation and quarantine of contacts. In Toronto after-action reports
from the SARS outbreak cited the lack of robust information systems as
their major impediment to outbreak control. First they tried using
Excel, and then when that failed they used a paper‑based system. Next
slide, please.

So those are the complex outbreaks, but all outbreaks do require certain
routine steps. Next slide, please. And these include first detection and
verification of the outbreak. Active case finding and, very importantly,
the case definition may change over the course of an outbreak. You start
out one way then you find out things that make you have to look for
cases in a different way. So it\'s very dynamic. We have to triage and
investigate all suspect case reports in addition to those that end up
being confirmed. And as Paula mentioned earlier, medical record review
and physician interview, interviews of patients and families about
exposure and contact data are really the hard core of the data that we
need to collect in addition to the laboratory specimens.

In order to do the medical record reviews usually we send public health
staff into the field, into the hospital, to retrieve and review the
records. And this is time‑consuming and labor intensive.

In addition, we perform laboratory testing, especially if it\'s a new
disease, that needs to be done at the public health laboratory, or if
it\'s an unusual disease. Contact tracing and management, environmental
investigation, epidemiological analyses to try to identify the risk
factors responsible for the outbreak, and then institution of control
measures and communication to the public. Next slide, please.

In more complex outbreaks, such as the ones I described before, we have
the pressure for daily summary of reports. We need to potentially
collect data at multiple sites in the field and it would be, that may
require data entry at the sites, although we currently do use a
paper‑based system. Multiple jurisdictions may be affected and that
requires some very close attention to data sharing agreements with other
jurisdictions. These outbreaks are extremely dynamic, some of the
variables are standard and consistent and others are very much
situation-dependent. And then there\'s a need from the public\'s point
of view and from our point of view to track patient outcomes as well,
which requires ongoing follow‑up over time. Next slide, please.

In addition, more complex outbreaks require potentially complex analysis
about exposures. And then, as I mentioned before, in a less controlled
situation, the laboratory specimens that, from the field often do arrive
with potentially inadequate documentation. They may arrive at the public
health laboratory with no record of them having been reported to an
epidemiology or surveillance database, and that poses challenges in
linking those specimens with the patients. We may have a need for stat
GIS analyses and maps. A need to link, as I mentioned, patients to
specimens, patients to contacts, people to locations, specimens to
locations, and the time dimension to all of these. Next slide, please.

In addition in order to manage all this, we need to manage our work. And
that means managing the assignment of interviews and chart reviews,
tracking down missing data, requesting and tracking specimens,
determining case status so that as things change we need to confirm a
case or rule out a case, and then all the measures that follow from
there, following cases to determine the outcome, and then tracing the
contacts and managing them, including possibly daily status checks and
potentially administration of prophylaxis. Next slide.

In order to do all of this we do have needs in terms of databases and
the databases need to be flexible. They need to be scalable. What I\'ve
described doesn\'t need to be done on a daily basis, but we need to use
something that can be scaled up from something that can be used on a
daily basis so that it\'s familiar to its users and there\'s no major
training needs in an emergency. Ideally, it would have pre‑existing
modules which could be easily modified. Needs to allow multiple
simultaneous users. Support work flow management. And allow, ideally,
bidirectional messaging with other databases, such as laboratory
databases, surveillance databases, and the Centers for Disease Control
as well. I\'m going to skip through, I think, a few of the next few
slides quickly. Next slide, please.

Ideally outbreak databases need to be easy to use and navigate.
Event‑based. Next slide, please. They need to support versioning. Data
entry screens need to be easily formatted. We need to be able to
generate unique identifiers. They need to be searchable. Next slide,
please. And \-- I\'m on the slide that starts with the user can ‑‑ there
we go. It\'s very important that the users of such a system can flexibly
initiate databases, modify questionnaires, define new variables, access
and edit pre‑existing modules, define vocabulary field validation and
skip patterns. Next slide, please. And that the system has the ability
to be able to interact with a paper‑based system because that\'s how we
do things now. And then the second bullet, which is message to and from
the public health laboratory or other reference laboratories and
integrate laboratory and epidemiologic data is really important. And
although electronic laboratory reporting is rapidly coming online,
currently in New York City, even within the health department, we do not
have bidirectional communication between our epidemiology databases and
our laboratory databases and that raises great challenges when specimens
arrive at the laboratory, as I mentioned before, to link specimens to
patients. Next slide, please. I\'m skipping one slide, so going down to
the next one. Thanks. The system needs to be secure and confidential. We
need to have user defined roles and access, with remote access possible.
And redundancy to support the system in case of any kind of electronic
or network failure and regular back‑up. Next slide, please. These are
additional characteristics that a system needs to have. I think I\'m
just going to skip this and go to the next slide.

So our currently available tools what do we have now? What will we use
for early pandemic influenza, what will we use for the next new disease
that comes along? Right now we have Microsoft Access, which is what I
think most health departments across the country are using. We have Epi
Info, Excel, which has proven itself not up to the task for a complex
outbreak, and we have the CDC Outbreak Management System which was
promising but whose development has been paused at the Centers for
Disease Control currently. And we also have the possibility now, we\'ve
used a customized solution, web‑based solution which our own IT
department can build for each outbreak as a potential for large complex
outbreaks, but that takes time and certainly not every local health
department has that capacity. We can also use Web‑based data collection
tools such as MR Interview and Survey Monkey for data collection, but
they don\'t really serve the middle needs of outbreak management. Next
slide, please.

So currently we have in the case of an outbreak we have patients who are
sick. Next, can you just click? And that\'s sort of our fire. And once
the fire\'s there, we have systems which can detect the outbreak to a
certain extent and although this didn\'t quite work, what that\'s meant
to show is that the tool in the middle which we\'re using, which is this
old sort of 1950s‑style fire truck, is not adequate for the job, which
is to intervene and control the outbreak currently. We\'re using
outdated tools. We really do have a major gap here, and as Paula was
mentioning, we need more robust tools to be able to do what we need to
do to protect the public. Next slide, please. Next slide?

The options for the future are, include the outbreak management system
either that CDC developed system itself or another outbreak management
system that would have much of the same functionality. We could use our
own plans here in New York City if that is not available, if development
does not resume, is to use Microsoft Access with a SQL back end or
perhaps use a customized Web-based system if we need one for more
complex outbreaks. There may be commercial options out there that we\'re
not aware of. There are some health departments that are working on
those currently and perhaps others that we\'re not aware of. Next slide,
please.

So in conclusion, as Paula mentioned, clinical data in the electronic
health record really are not sufficient for outbreak management the way
that we currently do it. However in the future there are some
efficiencies that could be gained from leveraging electronic
communication with clinicians. Examples include when we need a medical
record, if we could request a medical record electronically, and receive
it for suspected or confirmed cases in an outbreak, that would be
extremely helpful and would save a lot of staff time. If we could have
triggers for public health actions, for example, in a SARS-type of
outbreak, if a patient presented to an emergency department with
respiratory disease and fever, if there could be a prompt to the
clinician to get travel history on those patients, to get certain kinds
of specimens, to request that those, request testing to be done at a
public health laboratory so we can link the specimens with that patient
by a common identifier. If we could have a report automatically sent to
the department of health or if we could just provide guidance to the
clinician on how to manage the patient in terms of infection control and
other treatment, that would be very helpful. And then lastly an example
would be in a pandemic if we had to count cases, to be able to get
admission log data regarding numbers of patients admitted with
pneumonia. Those are ways that we can envision in the future that
potentially electronic health records could help us.

We do need to reinstate federal support for improved tools for outbreak
management such as OMS. State and local health departments must have a
strong role in designing and evaluating those systems because we are the
ones that do this on a daily basis. And lastly, information technology
infrastructure at state and local health departments should be
strengthened. Thank you so much.

[**\>\> John Lumpkin:**]{.underline}

Thank you. Next, Janet Hamilton from the Florida Department of Health.

**[\>\> Janet Hamilton:]{.underline}**

Thank you so much. This is Janet Hamilton. I am the surveillance and
reporting section administrator. And I wanted to take the opportunity to
thank everyone for allowing me to come today, and also comment that
talking about state outbreak needs in 10 minutes is incredibly
intimidating. There are a lot of really important needs at the state and
local level, and I represent just one small piece of that, and certainly
10 minutes represents an even smaller piece of that.

My presentation is ‑‑ and we\'ll go ahead and bring up the first slide,
please ‑‑ is more focused on an application-centric approach. Primarily
when I was thinking about this at the state level we have worked really
hard in Florida to try and think how we can do a better job of helping
to coordinate efforts at the local level. As you've heard this morning
already, at the state level we don\'t primarily do the actual sort of on
the ground bread and butter epidemiology of investigating the cases, but
we do provide significant support during outbreak investigations. And as
soon as the investigations go across jurisdictions we\'re also very
involved in I would say the information exchange piece. As soon as it
goes across jurisdictions often we are representing and communicating
information from a centralized public health information officer so that
we\'re able to provide clean and consistent information.

In Florida we\'re set up in a system where we have 67 county health
departments. Those county health departments receive information from
essentially the healthcare community to get the cases reported in and
then at the state office we support those CHDs. I am from the Bureau of
Epidemiology, but the way that we are set up we also have the Bureau of
Immunizations that functions in a critical role when we deal with
vaccine-preventible diseases. In addition, the Bureau of Community
Environmental Health so any time we have food- and water‑borne
activities, we are then coordinating with Environmental Health, who is
coordinating with the DACS (ph) and the Department of Agriculture. So
having a system to help manage both the counties and those of us at the
state level, depending on who is actually sort of the point person on
the outbreaks has become very important to us. I would say
post-hurricane in Florida, which is really post‑2004, almost every event
that we manage now we utilize the ICS structure in order to do that. If
the outbreak event is local, that is coordinated mostly at the county
health department with the state really providing information about what
specimens need to be collected, how to collect those specimens, various
types of testing that are available outside of the local level, and then
to additionally coordinate that piece.

So in Florida we have our surveillance module, which is a Web‑based
application. We call it Merlin. It doesn\'t mean anything except some
people thought it was kind of magical. And within our surveillance
piece, then we do have an outbreak piece. The outbreak module, sometimes
called the Merlin Outbreak Module or the MOM. So I wanted to talk some
about how we utilized that application as a state to coordinate our
efforts. So I\'ll be talking about why we developed it, some of our key
design considerations in terms of thinking about outbreaks, and then
some implementation and use. So if we can bring up the next slide.

In addition, Merlin has access by all 67 county health departments. We
currently have 950 users, approximately, across the state. So those are
local users as well as state users. At the state level, we review the
data, help to identify outbreaks that may have been missed or those that
are across jurisdictions. And then we also have some other large modules
including lead poisoning, perinatal hepatitis B, rabies, and electronic
reporting. Next slide.

This is really just talking about some of Merlin\'s sort of underlying
components. It is a SQL database with an MS Access interface structure.
It\'s ODBC compliant, so it\'s accessible, if you have the connection,
via SAS, also SQL. It\'s browser accessible. It\'s based off of the DOH
intranet site. So it\'s housed within the intranet. We can receive
information from the outside but we cannot actually push it back in the
current system structure that we have. We are in the process of
converting it from ASP, which started in 2000, to dot Net. So we\'re
about halfway through that process. We\'ve evaluated it against the PHIN
early event and detection standards, both the surveillance piece and
outbreak module piece. That evaluation process was very helpful for us
and we have some planned enhancements based on that evaluation.

In terms of thinking about the outbreak module when it initially started
I think at the state level one thing that we really wanted to do was
have a tool for both documenting and analyzing the outbreaks and then
secondarily to provide information to the local level that would
actually help them with their individual case management efforts. If we
can bring up the next slide.

So thinking a little bit more about why we wanted to develop the
outbreak module. We wanted to, first of all, facilitate more complete
outbreak reporting. We found that there were a lot of smaller outbreaks
that would go on at the local level that we would not hear about at the
state. They were managed and contained very well. These are small
outbreaks, for example, Shigella in a day care, or other items that
county health departments come into contact with and don\'t necessarily
need additional state consultation to handle them well. But when you
went to a county health department and said how many outbreaks of
Shigella did you have in day cares in the last year it was very hard for
them to sort through the papers in filing cabinets to actually have a
self‑contained location where they could then think about the next year
in terms of what materials might be helpful for them to develop in order
to help kind of streamline their process in terms of managing the
outbreaks at a local level.

Additionally if we had a tool at the state level, we could utilize the
tool as part of a training process to manage the outbreak
investigations. So if we had a tool then that would provide us sort of
an opportunity to bring people together in a hands‑on effort, I think
one thing we really struggle with in a training perspective is to
provide good hands-on training to county health departments. It\'s very
easy for us to talk about what should be done. But counties are
consistently wanting real sort of tools or cookbooks of how to address
certain common things, and if we had the outbreak module it would help
us do that.

Certainly once the outbreak was there we really wanted to focus on good
data collection and data review at the state level. Many times during
outbreaks the counties are so busy collecting the information that they
have very little time to then summarize the information. And if we could
assist with that at the state level and communicate that back to the
counties, it would be useful.

In addition, we\'ve found the outbreak module useful as kind of a drop
in surveillance tool. So maybe we\'re not sure that an outbreak is going
on. This year, for example, we had a concern of additional Cyclospora
cases in the state and the previous year we had a large outbreak of
Cyclospora, in the tune of about 500 cases, that was associated with
basil consumption. So we weren\'t sure if we were having that same thing
again, and the outbreak module provides us a location, essentially, to
post a questionnaire. So when you\'re doing your sort of on the ground
regular Cyclospora investigation, now we\'re trying to actually
determine if we do or don\'t have an outbreak going on, we can ask some
really specific questions and have those be standardized across
counties.

And as I mentioned, a simple way for state staff to actually assist
managing these outbreaks, if we can bring up the next slide, this is a
little bit of information. It\'s a schematic of how our notifiable
disease reporting works within Merlin. So we get information that does
come in through kind of a posting opportunity from medical facilities.
Right now that\'s a one‑way direction. We want to certainly work on how
we can make that bidirectional but it\'s not available for us now. The
main flow at this point in time is really from medical facilities and
laboratories either across that top line there, which is through
paper‑based and mail, through telephone calls and faxes, to the county
health departments that evaluate those cases and then report them into
Merlin and interact with Merlin to run reports, assign cases and case
managers, and then from there we report our information to the CDC
directly from Merlin.

The next schematic is looking at Merlin in terms of the surveillance
piece and the outbreak module and a little bit more of kind of the key
components. So we already had the surveillance module where we
essentially had the individual case profiles and then the case pieces.
We do have extended data for many of the cases which is kind of risk
factor questionnaires on reportable diseases. And then in the outbreak
module the key piece is the actual outbreak definition and then
describing that outbreak really in terms of person, place, and time. So
the setting piece and environmental samples, the people piece, the time
comes into the outbreak definition primarily, and really the ability, if
we can go ahead and bring up the next slide, to link the cases from the
outbreak module to the reporting module.

This is the home screen in Merlin. It\'s a little bit hard to read, but
essentially where I have circled at the top there you can see the
reporting section, which is the cases piece or you can immediately enter
into the outbreak piece. You\'ll also see at the top there is our
additional communication piece which is EpiCom, which is now on the
Merlin home screen, and EpiCom is essentially our state HON system.
You\'ll see a couple of recent outbreaks. This screen capture was done
recently, so for March 22nd, for example, you\'ll see a suspected
outbreak of norovirus in a day care facility, norovirus in a nursing
home. And it was really through this message board and HON system that
we identified in Florida our outbreak of E. Coli and hemolytic uremic
syndrome associated with petting zoos. So kind of getting the
information communicated to counties when they\'re going in to report a
regular case.

**[\>\> John Lumpkin:]{.underline}**

Twelve minutes.

**[\>\> Janet Hamilton:]{.underline}**

Okay. So let me just try to wrap up over the next slides here. So our
key design considerations, if we can have the next slide, is that it\'s
highly integrated with the surveillance piece so we have easy exchange
of records back and back and forth. That it is very easy to navigate,
that is, designing essentially for the lowest common denominator. During
outbreak investigations we have essentially people doing data entry that
are cross‑trained. So having the ability to enter in that information
very easily without a lot of training becomes important to us. Multiple
simultaneous users. And then we\'ll skip the next slide which really
shows how to link those cases together and move on to the next key
design considerations, which is that it\'s very flexible. It\'s easy to
implement. You can create and display relationships between the cases
and contacts, and also useful for both large and small outbreaks. So for
the small outbreaks you can essentially just do a face sheet documenting
the number of cases that were available and control measures put in
place, but not necessarily the need to work each individual case. And
then the summary piece.

I am going to go on to the elements of the module. This just really
shows the different pieces that we have within the module. The
definition, which consistently changes throughout the outbreak
investigation. The people, which is where you manage essentially the
pieces of the people, the contacts, linking them to settings,
environmental samples. Also having kind of a running event log
throughout the outbreak so you can go back and review what has and
hasn\'t taken place, and then some risk factor surveys.

And if we skip then the next few slides, which essentially are just
screen captures, one is an epi curve, the other one are line lists that
are automatically generated, then the next one is a descriptive analysis
that\'s automatically done, and the risk factor analysis. And we will
just look at the end, which is kind of the success stories piece, which
is that we are not currently requiring every portion of the outbreak
module to be utilized at this point in time. But it has really helped us
in terms of our data management activities at the state. Many times
these become a large media event, so being able to provide information
at meetings twice daily or multiple times, that the outbreak module
automatically summarizes the number of cases, the number of confirmed
cases, the number of cases linked to laboratory results, and these tend
to be the pieces that the media really wants. So if we can provide those
pieces very easily and consistently and clearly, then we can spend more
time essentially helping the counties with the investigation piece. And
thank you very much. I appreciate the opportunity and I\'ll welcome
questions when we can take them.

[**\>\> John Lumpkin:**]{.underline}

Great. Thank you. Our next presenter is Marion Kainer.

[**\>\> Marion Kainer:**]{.underline}

Good morning. Thank you for the opportunity to provide the state\'s
perspective on outbreak management. Next slide, please. I will discuss
the complexity of capturing exposure data, describe Tennessee's
experience in using CDC\'s outbreak management system or OMS, and
provide summary results of the CSTE needs assessment that was conducted
last month. And finally I will touch on some thoughts on current gaps
and recommendations for AHIC. Next slide, please.

Some communicable diseases that require contact tracing are transmitted
through droplet or droplet nuclei, the airborne route. Examples include
novel agents such as SARS, H5N1 influenza, and vaccine-preventable
diseases such as measles. Tuberculosis, or TB, is another example. Next
slide, please.

So why do we do contact investigations for TB? For the simple reason
that every case was once a contact. We perform contact investigations to
stop TB transmission, to identify additional cases, ensure proper
evaluation and treatment, to make them noninfectious, and cure their TB
disease, and to prevent newly infected contacts from developing active
disease. Because of the rapid progression from infection to disease
progression, the prioritized contacts were the HIV-positive as well as
young children. Next slide, please.

In late 2005, Tennessee had the opportunity to evaluate the utility of
CDC\'s OMS in managing a complex TB contact investigation. There was a
cluster of 19 cases that were genotypically linked. One of those 19
cases had over 200 contacts identified, and early indications were that
half of these were (inaudible). This was a particularly challenging
situation as the index case was HIV-positive, homeless, and used crack.

She exchanged sex for drugs and was babysitting for at least 14
different households over a 9‑month infectious period. Of particular
concern was the fact that many of the persons exposed were children or
potentially HIV-positive, which added tremendous urgency to this
investigation. Next slide, please.

To interrupt transmission we needed to collect detailed information on
the relationships to identify patterns that could lead to transmission.
Capturing relationship data also permitted our disease investigators to
use friends and family members to track down persons who for various
reasons did not wish to be found. We also needed to capture data on
exposures. In this case to multiple locations and shared activities such
as crack use. Next slide, please.

This diagram is intended to represent the interactions between persons,
location, and time, that is important to capture when looking at
exposures and potential disease transmission. However, exposure is
actually usually a duration and not a point in time. Next slide, please.

This modified exposure triangle is perhaps a better illustration of this
interaction. A subject is present at a location for a period of time
indicated at the base of the triangle. Next slide, please.

Here one sees subject A exposing a contact at a particular location for
a defined time period. Next slide, please.

Here we have a snapshot of what happened on one afternoon during the
nine-month infectious period with our index TB patient in Tennessee. She
engaged in shared activities, sex and drug use, with two persons at one
location and then went to a small crowded house with poor ventilation
where she exposed a six‑month old infant. This patient had over 200
contacts in at least 14 households and engaged in lots of shared
activities. I think most of you would agree that it would not be easy to
capture this type of information in an Excel spreadsheet and to be able
to use the data to prioritize contact investigations and ensure sound
decision-making. Next slide, please.

We needed to capture data on shared activities. And for all 200 plus
contacts, we needed to capture follow‑up information such as results of
TB skin tests to identify who was infected with TB, results of chest
x‑rays for active TB disease, as well as treatment information. Next
slide, please.

We used the beta release of CDC's OMS version 1.1.53. OMS allowed us to
capture demographic investigation-specific information, exposure contact
relationships between multiple entities, and to create relationships.
Next slide, please.

Here\'s the screen shot of the core demographic tab. Next slide, please.

In addition to the core questions that are common to all investigations,
OMS provides (inaudible) include any additional data specific to the
investigation through the use of supplemental data tables. Examples may
include risk factors, clinical information, laboratory testing,
treatment, study questionnaires, isolation quarantine, vaccinations, et
cetera. Also note the new version of OMS, version 1.2, has laboratory
and countermeasure modules that capture information on treatment,
vaccination, and isolation and quarantine similar to the core modules of
demographics and investigation. Next slide, please.

This is an example of the supplemental data form, and skip patterns can
be generated. Next slide, please.

But OMS is not just a data gathering tool. It provides incredibly
helpful reports on a daily basis that assist the work flow and provide
data for decision making. We generated reports in Microsoft Access
because that\'s what most of the investigators were familiar with.
Examples of reports generated included line lists, missing data reports,
and daily activity reports which made it possible to manage these many
contact investigations, decreasing the chances of a patient being
missed. Next slide, please.

We also used the data in OMS in social networking analysis to get a
better picture of where TB was transmitted. Next slide, please.

The data in OMS could be easily accessed for an ODBC connection. In an
unsolicited quote from an epidemiologist who was involved in the contact
investigation was the power of OMS is intoxicating. Next slide, please.

So in summary, Tennessee found OMS to be a powerful tool in managing
contact investigations. In conjunction with SAS, Microsoft Access,
social networking software, and GIS, use of OMS greatly improves our
epidemiologic response. OMS is a sustainable (inaudible) for managing
multiple and/or large contact investigations because of its ease of data
entry; standardized vocabulary; dynamic, versioned supplemental question
sets; and ease of data extraction and analysis. Because of all these
factors Tennessee has implemented OMS version 1.2. In fact, the reason
I\'ve not been able to attend in person is because today is day three of
an intensive training course in the new version of OMS for our regional
and central office epis. We believe OMS is a powerful tool in our
toolbox. OMS is also a crucial element of Tennessee\'s response to H5N1
influenza. Next slide, please.

In February of 2007 CSTE conducted a survey among 50 states and 11 large
city public healthcare jurisdictions. It was done to assess the need for
an outbreak management system, a request from CDC. CSTE also gathered
data on which features of an outbreak management system were considered
most important. Next slide, please.

Fifty out of 50, 100 percent of states responded to this assessment.
Next slide, please.

Here\'s a summary of the findings. State and local public health
departments stated that it is very important to have a system such as
CDC\'s OMS. Most jurisdictions do not currently feel prepared for data
management of a large complex outbreak. Many jurisdictions have not
developed an in‑house solution and were planning to evaluate or
implement CDC\'s OMS 1.2. Next slide, please.

It was (inaudible) CDC\'s OMS as a possible solution. However, there was
limited hands-on exposure to the most recent version 1.2. And there were
concerns over whether the application will continue to be developed and
supported to meet the outbreak management needs of state and local
health departments. States and public health jurisdictions want OMS to
be able to exchange messages with surveillance and laboratory systems.
States also expressed some interest in having OMS able to be deployed
both as a Web‑based and as a client server application. Next slide,
please.

CSTE recommended to reinstate federal support for CDC\'s OMS 1.2 in
providing deployment and training. To reconvene the OMS working group,
to await feedback from experience of CDC\'s outbreak management system
1.2 in the field and input from the OMS working group before evaluating
future enhancements, and to prioritize specific high-value enhancements
such as messaging. Next slide, please.

This slide shows the importance of OMS exchanging messages with other
systems.

[**\>\> John Lumpkin:**]{.underline}

Marion, your time is about up.

[**\>\> Marion Kainer:**]{.underline}

Yep.

**[\>\> John Lumpkin:]{.underline}**

Thank you.

[**\>\> Marion Kainer:**]{.underline}

You can see surveillance and laboratory information was rated very high.
Electronic health records were comparatively low and that probably
reflects the fact that clinical health information, whilst important, is
only a small component of the information required to manage outbreaks,
as Annie fine mentioned previously. Next slide, please.

Some final parting thoughts. Exposure investigations in healthcare
settings are often very complex, particularly because staff and patients
move locations so frequently. It would be incredibly helpful to be able
to easily capture and retrieve information on staff and patient
movement, including entry and exit times. You may be able to facilitate
that. In addition, you may be able to be in a position to advocate for
additional federal investments in tools for outbreak management such as
the CDC's OMS.

[**\>\> John Lumpkin:**]{.underline}

Thank you. And last, Tim Morris from CDC.

[**\>\> Tim Morris:**]{.underline}

I appreciate the opportunity to provide testimony today. Being from the
CDC, I\'m going to take a little more, a couple of levels up view of
some of this. My colleagues from the state and local level have
described much of the activities and the needs at the state and local
level very well. So I\'ll concentrate on a few different types of
things, the different types of response that CDC is involved in, some
particular areas where at the federal level we are involved and can
coordinate. So first slide, please, or next slide.

Again, this is just a depiction through some pictures of the different
areas that certainly CDC works in. Certainly we\'re talking about
outbreak management today. But in components of natural disasters and
recovery, preparedness and response to those, you can look at certainly
the laboratory capacity, coordinating laboratory response network and
other activities across the country for those types of responses.
Obviously the picture of the chickens that you can see on the picture
obviously referring to the avian influenza, and the types of, different
types of involvement we have. And as well as the state and local level,
but really across federal agency coordination with some of these
activities as well. A few things, the one picture in the middle
depicting the really, an international aspect of what CDC does certainly
with polio eradication, certainly historically the small pox
eradication, and certainly there\'s a global aspect to what CDC and
public health in general does. So I think this will point to ‑‑ I\'ll
touch on a little bit later some of the need for not just looking at
standards for information exchange just nationally, but public health
and certainly outbreak management and disease detection and such are
international issues. And certainly there are international standards
out there that are being used and certainly being recommended by HITSP,
but I think some of the consistency of use of those is important to look
into. Next slide, please.

Just to cover a few of the areas. This is really, you can view these
different areas and drill into these on the CDC site. I think it\'s at
bt.cdc.gov. And the different categories, at least the categorization
that we have on the site really around bioterrorism preparedness,
emergency response, and certainly the area of bioterrorism preparedness,
chemical emergencies, CDC, the Center for Environmental Health is really
a coordination point for really large volume testing for chemical
exposures and exposure studies. Radiologic emergencies, again the Center
for Environmental Health. Mass casualty events, natural disasters such
as Katrina, and of course disease outbreaks. In the areas to the right
that, certainly those, most on the phone or in the room know most of
CDC\'s mission, and certainly that of the state and local health
departments as well in disease and injury prevention, occupational
health, from the CDC perspective state and local support, disease
surveillance and control, at the CDC level with national coordination
and national surveillance, certainly lab testing, support for the state
and locals, as well as a large capacity for that, as a national lab, at
CDC. And obviously population health. Next slide, please.

Just to cover a little bit of the breadth of partners. Certainly we\'ve
talked about the interactions between the CDC and state and local health
departments. But as well all our federal partners in different
activities that cross different types of functional domains with the
FDA, the USDA, FEMA, EPA, and many other federal agencies as well as
their local counterparts at the state level. Department of Homeland
Security, certainly since 9/11 and the development of that agency, or
that area, excuse me, we have had increasingly more interaction with
Homeland Security and continue to do so. Obviously Health and Human
Services, which we are a part. Federal and local law enforcement,
certainly, and bioterrorism or any other type of terrorism event local
law enforcement is involved. Hospitals, clinics, and other local care
delivery facilities, certainly for the flow of clinical information, as
well as providing guidelines and information back to clinical care
during outbreaks or during just routine surveillance, as well as,
certainly in the systems area, commercial vendors and contractors. We
have those at CDC and the folks that create systems and work with the
standards that we use are an important part of developing the capacity
to respond. Next slide, please.

Just to go over a little bit, at a high level, the information types,
certainly they\'ve been covered well covered by the previous speakers,
cases, contacts, exposure cohorts. I use that term really to mean, say
in an environmental event, it\'s not person-to-person exposure,
certainly and I think it\'s been pointed out by the previous speakers
where we have exposure in locations or to a physical thing, and not
necessarily person-to-person. As well as we have exposure to animals and
other types of things, laboratory orders and results, this is certainly
an important one for routine surveillance or outbreaks, interventions,
environmental data, spatial data looking at this from a geographic and
temporal perspective. Health alerts. Obviously previous speakers talked
about the alerting and kind of form capacity to share information that
might not be in a transactable form, in a lab order or something else
but really ways to securely share information and recommendations and
other types of things in a more collaborative way, as well as the
recommendation and things that CDC would put out, and puts out
regularly. Next slide, please.

Can't talk about information management and sharing without talking a
little bit about interoperability. I won\'t dwell too much on this. Just
to talk about the two different areas, one is kind of the semantic piece
of this, which is the terminology systems, LOINC, SNOMED, that we use
for looking at data, what a given attribute in a information system
means, or some coded element, or a drop-down box in a system you might
see. And they also populate the messages that we move back and forth.
Formatting, obviously, as has been mentioned previously, some of the
state of the art now for outbreak management tends to be spreadsheets,
Access database, and many ad hoc tools. As such, some of the data
exchange that is currently available in public health is also text files
and spreadsheets and other types of things. And there is quite a bit of
success at the state and local level and national level in using
national standards like, or international standards like HL7.

The key to this is certainly using and thinking about information around
a given semantic model, I think this is an important thing to realize,
with Dr. Kainer's presentation, when you looked at the social network
diagram that was provided, there\'s no way that can happen without a
model that that\'s based on to encode relationships. So it\'s an
important thing to look at and it\'s important with interoperability,
too, how are you going to share information at that level of complexity?

The other piece of this is the physical interoperability, the data
transport, the security and encryption, directory services, and another
one that identifier name spaces, that\'s just the last one, is reakkt an
important issue I think for as we looked at the Public Health
Information Network and certainly for the Nationwide Health Information
Network in identifying systems, organizations, other well-known entities
or objects. So if I have two different lab systems I need to know the
difference between specimen one from system A and specimen one from
system B. That\'s what this is for. There needs to be an infrastructure
to provide that. With the transport and directory services the analogy
would be close to e‑mail, where you can go into your e‑mail box, look in
the directory, and address an e‑mail to anyone. And the reason that
works is because there\'s a common transport protocol, called Simple
Mail Transport Protocol, that allows that, and everyone uses it
consistently. So there\'s a ways to go with some of these things, and
the use of them consistently, or protocols for doing these types of
things securely, which e‑mail is not. Next slide.

This is my Rubik's Cube of semantic information. It has an animation
with it. I\'m not sure that it will work, but this is just meant to
show, and it\'s hard to read on the screen here, but you can see it a
little better if you have the slides in front of you, the cross-cutting
nature of what public health has to deal with. I think this is true for
clinical care as well. But this depicts certainly the domains, some of
the domains in public health where you have early event detection really
crosses the laboratory domain, clinical observations, demographics,
public health investigations, and other types of information. And if the
animation worked you could see any one of these boxes at the
cross‑section, you could see, say with outbreak management, you could
pull out the clinical observation piece and you would see the
intersection there and how it\'s used. And I think the important thing
to remember here is that there\'s a usage context in each one of these
domains that makes it a little different. However, you are using the
same information and hopefully the same information semantic, otherwise
this can\'t happen. Next slide, please.

[**\>\> John Lumpkin:**]{.underline}

Tim, you\'re at 12 minutes.

**[\>\> Tim Morris:]{.underline}**

I will skim through the next slide because it\'s heavily animated. So
you can move on. That one is, I\'m quite sure that one won\'t work.

I was going to step through a couple of scenarios. We\'ll go through
these pretty quick and I\'ll get to the wrap‑up. The first one was
anthrax, which was the animation to show the different partners that are
involved in some of the different information flows. But I put a couple
of interesting ones in here, one the monkey pox investigation we did, it
was a multi‑state zoonotic disease transmission. The normal types of
activity and information, case investigations, exposures, source
identification here traced back to animals from the distributors to the
different pets, and these were exotic pets so it was kind of, in some
cases it was an underground trade so it was some of these were sold out
of a home, specific types of locations. And then the follow‑on to
individuals releasing those pets that may have been exposed. So
surveillance of the wild animal population, which really shows the
cross-cutting nature of an event like this and how in some cases
clinical information can lead us to some things but sometimes these
become the proverbial needle in the haystack for detection in the
beginning. Information challenges, multi‑state, so the animals and
distributors were multi‑state as well as the cases. Data collected, in
this case, in ad hoc spreadsheets and databases. A new type of thing
that certainly in public health we may come across but tracking animal
shipment manifests and then the other thing was these multiple venues
for possible animal human exposure, again looking at locations where
individuals might be exposed for these exotic pet swap meets and
different things that were going on. Next slide.

We\'re all pretty familiar with SARS. Again a lot of the same types of
activities. Again, this one CDC is heavily involved with tracking
migration of population at ports of entry as well as disseminating
information about potentially exposed individuals that might be on
airplanes or whatever types of international modes of transportation,
down to the state and local level for some cross-jurisdictional contact
tracing and follow‑up of individuals that might be on those transports.
Isolation and quarantine management. And then some of the challenges,
again, these start to repeat because there are many things that are in
common with different types of outbreaks, but there are also about as
many things that are different with each one. But distribution of
contact information across jurisdiction. Obviously this was a difficult
one with SARS. An evolving case definition. Certainly many surveillance
systems now work off of pretty static case definitions. When you throw
in the mix of an outbreak investigation where you can use that
definition but also look at different things particular to the
difference between a, say a TB outbreak in a prison versus in a day care
setting or something else, there\'s differences there that you need to
track. But SARS was particularly difficult because there was no case
definition in the beginning and it evolved very quickly and very often.
So your systems need to be capable of managing that. The other thing is
for the clinical data feeds that we might get from clinical care to do
syndromic surveillance or situational awareness in this case, the
systems need to be very dynamic and configurable to go to syndrome and
subsyndrome level, to be able to detect these types of things and tune
to those types of detections. Next slide.

I know I\'m over. Just to touch on Katrina a bit. Certainly with natural
disasters there\'s many things that go on. Certainly there was outbreak
management or certainly surveillance there. But certainly injury
prevention for displaced people and rescue workers, environmental health
and safety, rebuilding public health infrastructure. It was gone in the
region, and so several federal agencies, certainly CDC, played a part in
that and other state and locals lended aid to the region for rebuilding
public health infrastructure in different areas. Big challenges here,
the poor or nonexistent infrastructure, population migration makes it
difficult to do surveillance because you really have difficulty getting
denominators. Inadequate system redundancy. Obviously I think the
electronic health record and availability of some of that will help us
with some of this with the displaced populations. However, I think we
need much more redundancy and capacity in the local public health
systems as well. Distributed ad hoc data analysis. Again, we had about
20, 30 versions of a shelter surveillance form and across those there
was about a 10 percent difference in the content. But if you looked at
the data behind it, it was all 100 percent different if you were going
to try to aggregate it. So again Janet I think touched on the use of
standard questions and reuse of those across different types of
situations and certainly across jurisdictions. Next slide.

Current challenges. We still face some of the things that we've faced
for a while. Certainly the multi‑state, local, federal entities,
cross-jurisdictional data sharing both from a policy level as well as a
system level. Distributed systems, it\'s a fact that we have them and we
need to learn to integrate them better than they are now. Complexity of
information. Again, going back to the, some of the use of clinical data
is just the pure size that that pipeline may represent for some
infrastructures that are not, possibly not ready to receive that. So
again the algorithms for taking that and whittling it down to the
information that is important for a specific event or some type of
outbreak is an important thing to do. Current state of the art for
outbreak management is too often a spreadsheet. The communications
infrastructure, while improving, I think there\'s things that can be
done there. And really the human and physical resources at the state and
local health departments is a concern with the level of IT resources,
system redundancy, and other types of things.

And the last slide, just quickly through some future work to do.
Obviously we need a flexible and secure nationwide network, both for
clinical information but also to help flow the information about the
other types of data that we may overlay for population health, like
environmental data or some of the animal health, some of these other
types of things. Implementation of standards consistently across
different domains. There\'s a lot of, there are a lot of successes at
the local levels, at the national levels with doing this. However I
think there\'s some ways to go in implementing some of the standards
more consistently to get closer to real interoperability, in the
real-time that we\'ll need for outbreaks, and the international aspects
are there with the standards. Common terminology usage and definitions
really gets to the consistent application of standards. Infrastructure
supporting discovery of exchange of information partners and services.
Many state, regional areas have regular trading partners with labs and
other folks. But in outbreaks and large events, and with the NHIN, your
trading partners just became everyone. So we need the infrastructure to
support that. Shared infrastructure for user and system authentication,
and these things need to be available at the local, regional, and
national levels and be compatible. And I'll throw the one plug in at the
end, field deployable situations, because in situations like Katrina,
where we have offline use, a Web system does not always fit the need
where you don\'t have a Web. Thank you.

[**\>\> John Lumpkin:**]{.underline}

Thank you. We're going to now go to questions. And I'm going to kick it
off. I\'m going to start off by sort of bridging off the comments I made
earlier on to introduce the session, and that, the goal of this
Workgroup or the job of this Workgroup is to make recommendations to the
American Health Information Community, not to the CDC or even to HHS,
but to look at those broader kinds of recommendations that can have an
impact. What I heard a number of comments on sort of implied but not
directly stated is that there\'s a need for interoperability. And this
interoperability needs to go in a number of directions. Clearly up and
down in the public health system between local health departments, state
health departments, and the CDC. Also horizontally across, between
states, between local jurisdictions. And then in sort of a fourth
dimension, or maybe a third dimension, between the clinical settings.
And you talked a little bit about more of the afferent kind of receiving
the data and less about the efferent.

So let me ask a very specific question. There are 19 of the 42 ‑‑
actually, 103 local health departments were surveyed by NACCHO. Of those
42 had some involvement with a RHIO or a health information exchange.
And 19 were already actively engaging. So given that environment, where
are the standards gaps? Is LOINC adequate for this kind of
communication, is SNOMED adequate for this communication? Are there an
adequate number of messaging standards? You talked a little bit about
communicating with immunizations, trying to get immunization records,
but there have been immunization records in an HL7 standard for exchange
of that data for eight or nine years. To what extent is that being used?
So is the gap the ability to use the current standards or is the gap the
fact that there are missing standards that need to be addressed?

[**\>\>**]{.underline}

I\'ll go first.

[**\>\> John Lumpkin:**]{.underline}

Sorry, long‑winded question.

[**\>\>**]{.underline}

Maybe I\'ll speak to the immunization one first, because it's probably
the one that we\'ve had the most experience with and the one that I know
the best personally. I guess a Katrina example of how immunization
registries were used, we did find that especially within Louisiana
immunization registry, that there was the capability to use HL7
messaging to exchange across state boundaries, with other state and
local immunization registries.

To the best of my knowledge, the HL7 exchange was not used with the
clinical setting, however. And I\'m not sure if that, it\'s probably a
matter of time to set up those exchanges. From personal experience with
immunization registries, we\'ve had the standard in place. The
difficulty has always been convincing HMOs and managed care, convincing
hospitals, providers\' offices that there is a value-add for them to
having electronic exchange of this data and then in turn it\'s been very
difficult to get the software manufacturers for practice management
software to actually implement these standards in these systems and the
ones that have or were interested in it, it was because their client
base of providers were pushing this. So just simply public health coming
to the software manufacturers and saying immunization registries are
great, we have this standard, we want you to implement it was not
sufficient. It was when the providers, their clients actually said we
need this. This is something we\'re demanding. We want you to implement
this. So I\'m going to say in the example of the immunization registry,
it\'s not a gap in the standards. It\'s a gap in implementation of the
standards in the practice management software and that is because
there\'s no consumer demand from the providers.

[**\>\> John Lumpkin:**]{.underline}

Responses as to gaps related to standards and messaging formats?

**[\>\> Theresa Cullen:]{.underline}**

This is Terry Cullen with Indian Health. I just wanted to comment on
this because we do run a huge immunization exchange with many states. I
would agree with you, I think the consumer, in quotes, the consumer
demand isn\'t there but it\'s also that it\'s not enabled in a way that
is passive. I don\'t think there\'s any practitioner out there who
doesn\'t think sharing immunization data is important. It\'s because of
the barriers that have been put in place. So even though there\'s
standard HL7 messaging I\'m sure you\'re aware that not every state but
many states have many interface engines going in. Even though CDC has
published standards I think there\'s at this point about 25 different
interfaces that you need to interact with. So one of the problems is
that when we look at standards there\'s standard messaging that I think
everybody is comfortable with HL7 for immunization, but at the interface
level of how that data goes from my system and populates the state
system, there\'s some inconsistencies. And that\'s a standard that has
not been addressed to some extent.

[**\>\> John Lumpkin:**]{.underline}

So let me just sort of branch off from what I'm hearing, is that there
needs to be some sort of reference implementation, that if you can speak
to that reference implementation then you should be able to speak to
others who can also speak to that. John?

[**\>\>**]{.underline}

You should only have to do it once.

[**\>\> John Lumpkin:**]{.underline}

Right.

[**\>\>** **John Loonsk: **]{.underline}

Some of the classic problem here has been that HL7 messages have
optionality and that optionality leads to various implementations. A
couple of points. When I last looked at state immunization registries I
think the majority of them and maybe it\'s getting closer to 50, still
did not process HL7 messages, though I think Louisiana is probably the
exception, Texas, yes. And the number was increasing, and that was
really encouraging and I don\'t know if anyone has looked at that more
recently.

Relative to ‑‑ so two related points. One is having a message that has
adequate implementation guidance, that is agreed upon, that specifies
the terminologies and constrains the message is part of the solution to
the optionality issue and the multiple interface issue. And that is
something that is, for example, part of the thrust of the Health
Information Technology Standards Panel work is not just to say it\'s an
HL7 message that needs to be used, it\'s to say here\'s the
implementation guide, here are the terms that need to be used in these
different places, so that, and that\'s exactly why, is to minimize the
optionality and try to reduce the number of variances in implementation
so it gets closer to plug-and-play.

Regarding the electronic health records and compelling people, I will
point out, to be able to transmit immunization messages, I will point
out that there is a certification criteria that\'s on the roadmap. It\'s
not yet into the ambulatory EHR, a certification criteria that suggests
that EHRs will need to be able to send that standard message and so you
can see a path here. It\'s not there yet but when that becomes a
criterion that certified EHRs will have to meet to achieve
certification, I think there\'s a very powerful tool there relative to
the private market and getting electronic health records to participate
in that end of that spectrum. I don\'t know, John, if you wanted to have
more discussion on that. I had a question I would like to follow up
with.

[**\>\>**]{.underline}

Let me respond quickly to something you just said and the issue of the
interface engine. While the immunization registry community did come
together to work on a common implementation guide, CDC did do work
around a common interface engine. But the proprietary software
developers didn\'t necessarily use it. So while many used the
implementation guide, it only got us so far. And I\'m not really, I
should know, as I was both a registry manager and a vendor who developed
the software, but I\'m not really sure where the gap was.

[**\>\> John Loonsk:**]{.underline}

This is one of the reasons that conformance testing as part of the
certification process is so important. That it\'s not enough to just say
I\'m using the message or I\'m using HL7. You really have to show it and
test it and prove it as a method of showing that that interface will
work when stressed against multiple other systems that may need to
connect.

[**\>\>**]{.underline}

And the greatest success seen with Katrina, with exchanging the data,
was using with other states using the same application.

[**\>\> John Lumpkin:**]{.underline}

Let me just suggest, not for an answer today, but we just went through a
very detailed discussion in relationship to HL7 messaging for
immunizations which obviously is a key component. But there are other
aspects of managing an outbreak for which there would be benefit. And I
think the opportunity that is being presented to the organizations who
we\'ve asked to present here that you represent is to put together an
agenda. And that subsequent agenda can be recommended to AHIC and
subsequently that can be put on the agenda for the CCHIT and other
processes. But if public health can\'t think to that point and merely
start putting those things on the agenda, we could be back here in
another five or ten years having the same conversation. So I\'m
encouraging you, not at this meeting, but if you can go back to your
organizations and put together a set of recommendations of what you
would like to see the America\'s health insurance community put on the
agenda for work down the road.

[**\>\>**]{.underline}

We actually are a little bit ahead of you. We\'re having in San Diego in
two weeks we\'re having a joint meeting with all of the major national
organizations, our federal partners, and some large, actually eHI, will
be, Janet Marchibroda will be in attendance to discuss just that, what
needs to be on the agenda.

[**\>\> John Loonsk:**]{.underline}

It is deja vu all over again for some of us. But I\'d like to just
follow up on some of the key points here. Because we\'ve heard some very
compelling testimony about some capabilities that I think can be very
clearly pointed to as important.

One of them is being able to exchange or work with possible cases. We
don\'t always know what those cases are going to be. But I'd like to
build to a question here to ask all of our panelists to talk about,
relative to the ability in public health systems to exchange possible
cases.

And another capability is contact tracing, we heard compelling testimony
about the importance of that and how valuable that can be in outbreaks
or how important in these outbreaks, and I\'d also like to ask our
panelists to give us an assessment of the degree to which contact
tracing, as a computer supportable function, is actually in place
nationally, just grossly, because it\'s hard to get a sense for this. We
tend to hear the examples of the ones that have, the early adopters that
have this capability, but I\'d like to have a broad picture, since we
know it was critical in SARS, we know it's critical in other outbreaks,
what percentage of jurisdictions at the state, local, and federal level
can actually perform contact tracing with a computer supportable
methodology? So that\'s question one. Contact tracing.

The other question was how many can exchange a possible case message in
a way that another system can use it? And clearly this is, we have
compelling testimony that says that you don\'t want to be building
technology at the time you\'re in the middle of an emergency. So what
percent of jurisdictions, and to use John\'s four dimensions perhaps, or
just his first two, the horizontal and the vertical? And how many
jurisdictions can actually exchange a possible case message, a simple,
that token of outbreak management, can exchange it in such a way that
another jurisdiction can actually work with it without having to
reprogram it or reprocess it, et cetera. Are those questions clear?

[**\>\>** **Annie Fine: **]{.underline}

Can I \-- this is Annie Fine in New York City. Could you just clarify
when you\'re talking about case data, possible case data, are you
talking about between the clinical setting and the local or state health
department, or are you talking about between the health department and
perhaps CDC?

[**\>\> John Loonsk:**]{.underline}

You\'re welcome to talk about the clinical too, but I was focusing more
on public health and both between local jurisdictions or between locals
and states and between local states and CDC. So horizontal and vertical.
The first two Lumpkin axes.

[**\>\> John Lumpkin:**]{.underline}

Someone lives in Newark and lives in New York City, how do those two
health departments exchange information that enables them to coordinate
their investigation of an outbreak?

[**\>\>** **Annie Fine: **]{.underline}

Currently we do not exchange data electronically across state lines. We
exchange data with the state health department and with the CDC. We do
not exchange electronic data across, but we\'re working on a regional
kind of outbreak system that would allow multi‑jurisdictional sharing of
data. But we\'re not there yet.

[**\>\> John Loonsk:**]{.underline}

I\'m sorry, Annie, I\'m not sure I\'m being completely clear. It\'s not
so much that I\'m trying to seek the information flows. I know the flows
are, there are traditional flows, there are flows that occur in a
routine endeavor. What we sort of heard was that in an emergency
sometimes those flows change. What I\'m seeking is the capacity. How
many jurisdictions can actually exchange a possible case with another
jurisdiction if the need arises in such a way that the other
jurisdiction can use it?

[**\>\>**]{.underline}

I think the simple answer is we don\'t know. But gut, Angela correct me
if you have a different gut, but my gut tells me that within states
probably when a statewide system is in place, when a statewide system is
in place very, very unlikely that it\'s being done electronically. It\'s
probably more likely, within states and across state lines, being done
with Epi-X, so no standards-based messaging. That is my gut.

[**\>\> Tim Morris:**]{.underline}

Certainly from the CDC perspective we have developed certainly in the
initial development of the HL‑7 version 3 case notification message and
as a follow-on to that around activities of the PHIN, for preparedness
and outbreak management and other things, we\'ve been working on an
outbreak message. Now an outbreak message is much more difficult to do
than a standard pretty static case notification because those don\'t
change much. In an outbreak, depending on what data you want to move, if
you want to move all of the different types of things that could go
between this TB outbreak and this one and this one, it\'s not your
standard surveillance. So it becomes a more complex message, but we do
have specifications to do that. Now in version 3, with the
infrastructure that\'s available, is there capacity to do that? I don\'t
think so right now. That message is not implemented anywhere.

We are working also with the Canadian Health Service and Infoway
project, through HL7, to develop a message to exchange exposure data.
Again, a very complex message, depending on what you put in it, because
it's relationship-rich, where you might have multiple people to list to
a contact or multiple things there.

So I think we\'re looking at trying to do those things and developing
the standards but I think back to the standards implementation question,
it\'s not that there\'s a lack of standards, I think it\'s application
of them consistently. Certainly especially in something like laboratory
microbiology results you can code the same result three or four
different ways and be right. Certainly I think that the standards are
there and I think, as John Loonsk said, it\'s getting to the level of
specificity and the implementations to where it\'s constrained enough so
that we can test against interfaces.

**[\>\> John Loonsk:]{.underline}**

Thanks. I don\'t know if anyone else wanted to comment on the possible
case exchange or not. But maybe we could turn to some assessment in your
professional opinions, and I know it\'s a gross estimate, of contact
tracing as a functionality and the degree of penetration of that
capability.

[**\>\> Marion Kainer:**]{.underline}

This is Marion Kainer. As part of the CSTE survey which was just
conducted in February, so this is very recent information, there were 10
jurisdictions which had developed an in‑house solution for outbreak
management, of which contact tracing would be a part of it. Out of those
10 jurisdictions which had completed that, only 5 stated that it met
their needs. So one would say that there are five jurisdictions who have
developed in‑house solutions where we assume that contact tracing is
part of that. There are two jurisdictions which have actually used OMS.
And I don\'t know about the rest.

We didn\'t specifically ask a question on the contact tracing itself.
However, we asked as to were they, how prepared you feel to manage a
large complex outbreak such as SARS in Toronto. And the self-assessment
of these states were such that there was only six jurisdictions who
stated that they were highly prepared from a data management
perspective. Which is 11 percent of the jurisdictions. Seventy-one
percent were somewhat prepared. And 18 percent unprepared. So it
doesn\'t get drilled down to just the contact tracing part of it, but I
think it gives you somewhat of an idea.

[**\>\>** **Annie Fine: **]{.underline}

This is Annie Fine in New York City. I cannot speak to the proportion of
jurisdictions that can do this, but again I have a question for you, I
believe it was John who asked the question, as to whether you\'re
talking about the entire activity of contact tracing being
computer‑based. Because I don\'t know that any jurisdiction in the
country can do contact tracing without calling and interviewing the
patient and following up and calling and interviewing the contacts. I
can\'t really envision how that could be computer‑based at this point.

[**\>\> John Loonsk:**]{.underline}

Annie, I was intending to refer to computer support of contact tracing,
and obviously there are a number of activities that are carried out by
people in that regard. But it is seemingly one of the compelling pieces
of outbreak management that the computer, computer systems seem to be
able to help with the linkages between contacts. But clearly it\'s
still, even when a computer is supporting it, it still involves a lot of
shoe leather.

[**\>\> Annie Fine:**]{.underline}

Right. I do think that\'s one of the strengths of CDC's OMS, is that
it's got very robust contact tracing support for those activities,
compared to other systems that we\'ve seen.

[**\>\>** **Janet Hamilton: **]{.underline}

This is Janet Hamilton. And just to speak on the sort of exchange piece
that you asked first. I think where states have systems in place, that
the exchange is good within the state. That\'s one reason why with our
outbreak management system in Florida, that was so important. Because we
wanted to be able to not do duplicative data entry, so that once we had
cases in outbreak we essentially just wanted to link them to the
surveillance reporting piece and it was essentially done, so that we
could manage that piece efficiently and so that\'s really the only way
that we can exchange data right now is through our reporting module. We
cannot exchange the outbreak piece. We have talked about how we would
add that messaging component in and I don\'t think that we really feel
like we have enough information to tackle that at this point. We\'ve
heard that there are standards that are coming out, but we really don\'t
know have what we feel we need to even begin that job. So if we had to
exchange our outbreak data with New York or another state, you know,
we\'d be faxing things and compiling things. It wouldn\'t be an
electronic exchange.

And in terms of the contact piece, our outbreak system does a good job
in linking the contacts but it doesn\'t really do a good job in
following those people over time. So we can link them but then, and we
can prioritize them, but after that, what we\'ve found is that our
management piece is stagnant. So that once we had essentially designated
a case in a certain way, they\'re designated and then we change it but
we lose where we change the designation to follow up on them. Nor does
it necessarily alert us, like hey here are all your to-dos for today and
so you can see who the contacts are and which ones are high and low
priority but you can\'t necessarily do a lot of follow‑up over time on
those individuals. And I think that\'s a real limitation.

**[\>\> Tim Morris:]{.underline}**

Just wanted to follow up on, John Lumpkin asked about standards gaps and
wanted to speak on that in terms of a terminology or vocabulary
perspective with outbreak, if you were going to message outbreak
information or exposure information, and I think there\'s really a gap
when we look at the types of things that public health looks at.
Different types of risk factors or risk factor questions that might be
on a surveillance or an outbreak investigation form. There would
certainly be a gap in a foodborne investigation when they asked them
about every food known to man that they may have eaten in the last few
weeks. There is no standard coding for that. So how are we going to
exchange that information? Most of that, or all of that is
post-coordinated. Some of the other areas where we have difficulties is
in post-coordination of specific strains of diseases. There are
methodologies to do this in SNOMED in the terminology space, but the
ability and knowledge to do it and for systems to implement it is
difficult right now and certainly how you code that into the messages
may not be done consistently across many systems. An example of that
would be the different strains for influenza that are reported and
influenza reporting routinely now and certainly would be important
during a pandemic, We're currently trying to go through that exercise
now in a specific area. You look at all the foodborne diseases, that\'s
a specific problem.

I think that the types of information that are inherent in outbreaks, if
you look, there are basic questions that might relate to a clinical
observation but they\'re basically multi‑component things when you look
at them from a coding perspective. So if you say fever greater than 100
degrees, you can build that expression in SNOMED, but do most systems
have the capability to implement that in that way so the data can be
mined? I think the other thing is being able to relay the clinic flows
to those types of questions that might be asked, to be able to map that
information into the outbreak systems, but also return that information
back to the clinical care setting so they can have an idea of what\'s
going on. I talked to Marion Kainer about this on some of the specific
things with, say, a hospital. And Marion, you may want to follow up on
this. On a contact investigation in a hospital setting, there was not
much information from clinical care on actually movement of an
individual there so you could actually know where they were, the
locations, and track through the hospital. Some of that type of data
would be important for some of those types of settings. And I don\'t
know if Marion wants to follow up on that.

**[\>\> Marion Kainer:]{.underline}**

Yes, this is Marion Kainer. I also have a very strong interest in health
care epidemiology. I\'ve been involved in a lot of contact
investigations within hospital settings. And this is one of the most
difficult problems, where we just don\'t know whether a certain patient
has exposed other patients or staff members to a particular disease. And
very few hospital information systems keep any kind of track of where
the patient location has been in terms of bed number. And it is not
necessarily in the time that they actually move but when the clerk
actually entered that kind of information. It makes those investigations
incredibly difficult. I\'m not even asking for a message of this
information but just being able to get a timeline of where a patient was
and who else was in that room or at that particular location would make
these contact and exposure investigations in hospitals so much easier.
This is not information which is usually kept in electronic health
records.

**[\>\> John Lumpkin:]{.underline}**

We could put RFID devices in all the staff and patients and record the
movements.

\[laughter\]

**[\>\> Marion Kainer:]{.underline}**

Maybe. It would certainly make life much, much simpler. Following up on
the messaging, currently the oubreak management system from CDC does not
have messaging, although that was slated for a future version. But
development has currently ceased while this evaluation is taking place.
In follow‑up from what Janet had said, one of the real strengths of the
outbreak management system is the follow up capabilities. One could
easily create triggers for what needs to happen, when. One can also get
a historical record of when case status has changed, when investigation
priority has, and have a historical record of what isolation or
quarantine records had taken place. So it really greatly assists in the
management of the patient, not only after you have identified the fact
that they are a contact, but also throughout the time of the
investigation.

**[\>\> John Lumpkin:]{.underline}**

Other questions. Scott.

[**\>\> Scott Becker**:]{.underline}

Thank you, everybody, for the presentation. This was excellent
testimony. And I wanted to sort of go down just a couple of thousand
miles here, and ask, we heard testimony in support of the OMS system,
and I\'m wondering what the timetable is for this evaluation that\'s
taking place.

**[\>\> Marion Kainer:]{.underline}**

I\'m not sure if I\'m the best person to speak to this, because I\'m not
in charge of this evaluation. I believe CDC is. My understanding is that
the outbreak management system funding source is (inaudible) at CDC, and
I believe that is being re‑evaluated in April for funding for financial
year 2008.

**[\>\> John Lumpkin:]{.underline}**

And, Marion, if you had been here, you would have seen Tim leaning
towards the microphone.

**[\>\> Marion Kainer:]{.underline}**

Oh, I\'m sorry, I\'m not there. I apologize.

**[\>\> John Lumpkin:]{.underline}**

And you saved him, but not for long.

**[\>\> Marion Kainer:]{.underline}**

Tim, you may want to add information.

**[\>\> Tim Morris:]{.underline}**

Well, I have a little bit to add. I was the previous lead for the
system, and it no longer resides in my division. However, I think in the
next few months, what I\'m hearing from Scott McNabb, who is the
director of the Division of Integrated Surveillance there, that there
will be some new information. Certainly there is more evaluation going
on at CDC in reference to a pandemic influenza exercise and use of it in
our operation center. Certainly in the first exercise, in February I
guess it was, there was support for doing it. So they are going to
continue to do it, and there is some things going on there. But I don\'t
have specific information about that timetable, but Scott McNabb would
be the best to talk to about that.

**[\>\> Scott Becker:]{.underline}**

It sounds like a temporary pause, not a permanent situation.

**[\>\> John Lumpkin:]{.underline}**

A pause. Not a hard stop.

**[\>\> Scott Becker:]{.underline}**

A pause, right. Okay, thanks. We can come back up to 40,000.

**[\>\> John Lumpkin:]{.underline}**

All right. Brian?

**[\>\> Brian Keaton:]{.underline}**

Actually, Scott took my question. But as I hear it, and it\'s almost
scary. I\'m an emergency doctor. I\'m starting to think like a public
health person, and that\'s really ‑‑

\[laughter\]

**[\>\> John Lumpkin:]{.underline}**

It happens to some of the best of us.

**[\>\> Brian Keaton:]{.underline}**

It\'s really alarming. I hear people, you know, you are talking about
the Florida system that you have developed internally. And I assume that
you are here because you are one of the examples of people that are
doing a lot of work and doing it the right way. I also hear the OMS
system talked about. Do those two systems talk to each other?

**[\>\> Janet Hamilton:]{.underline}**

They don\'t right now, and that\'s been part of our ‑‑ we have one
county that\'s evaluating OMS, and we would be more than happy to look
more carefully at OMS with the messaging component. Because we have
counties that ‑‑ OMS has some really wonderful features. And it does
things better than our system in some ways. But the thing that it does
not do is the surveillance and reporting piece, and sort of the setup
portion is much more difficult than ours. So for counties to initiate
outbreaks that are not necessarily highly technically skilled with
setting up databases and computers and the relationships, our system is
just so much easier for it, for them to use. And they are already
trained on the system. So we have discussed our ability to integrate
with the outbreak management system that CDC is developing, and would we
offer that as a second option, and we are definitely willing to consider
it. But without the messaging piece, it is a real limitation for us. And
right now it is not ‑‑ I mean, we are kind of waiting on that piece.

**[\>\> Brian Keaton:]{.underline}**

Back to John\'s question, is that messaging piece dependent on a lack of
standards or is it dependent on the horsepower and the time and energy
to actually do the work, using standards that exist?

**[\>\> Tim Morris:]{.underline}**

It is dependent on horsepower, resources to do it. It was planned in the
next release. It had always been a plan because we realize that need.
OMS really, I think, shines at the local level where the contact tracing
and other things are going on. As you described in your presentation,
where you are supporting at the state level this activity. Because it
does have a lot of the follow‑up pieces in it. But the need is to, and
there is a two‑way flow there. There is possibly from a detection
system, from clinical care data where you would notify, identify a
cluster of cases or, through a surveillance system, push that data into
the outbreak system and then do your cluster investigation and look at
that. And then you need to report those cases back to the surveillance
system for the routine longitudinal surveillance. Most outbreak systems,
I think, certainly OMS\'s is built instant-space. You create something
for this outbreak and then you create anew the next time in a kind of
generic system. So the message is there. We were certainly working
towards that. But the specification for the outbreak, we call it the
outbreak general message, is there, but has not been implemented
anywhere thus far.

**[\>\> Annie Fine:]{.underline}**

Also I just would add ‑‑ Annie Fine from New York City ‑‑ that, yes, we
were also waiting with bated breath for the messaging capability of OMS,
and needing that in order to send cases to our surveillance system and
our lab to send requests and also to receive data from the lab. But in
addition, I just wanted to mention that OMS has the capability to create
prepackaged sets of questions, including supplemental questions, that
can be shared with other jurisdictions. So that would facilitate
standardization of data collection across jurisdictional lines and then
messaging, if needed, of cases that were crossing jurisdictional lines,
or contacts as well.

**[\>\> Tim Morris:]{.underline}**

It gets us to one other standards gap, which is really, you can look at
questions like you would look at the SNOMED hierarchy. When you look at
things, these are questions that are about respiratory syndrome or these
are about a SARS investigation. And you could have an environment where
someone designs forms from a reusable question repository that is a
controlled vocabulary. So I think to do this, and what Annie suggests,
to share these. HL7 has been working on a common terminology services
specification for some time, really attached mostly to the version 3 HL7
messaging. But I think that the national, extending that, it doesn\'t
meet all the needs now. But that distribution to local levels from maybe
a master somewhere. But managing those types of terminology as well. And
it's a more dynamic piece that requires governance as well. But I think
that need is certainly there, both for distributing LOINC in the usage
context of public health, or SNOMED, because that hierarchy is not
necessarily how public health has the context of using it. So we do have
things to do that. And vocabulary and distribution system is there. Not
everything it needs to be, but we need those local instances of those
things and standards to distribute terminology.

**[\>\> John Loonsk:]{.underline}**

One more, one follow‑up question before we lose our epi panel. And in
anticipation of the afternoon testimony, clearly one of the other
capabilities that\'s important in managing an outbreak is for an epi
system to be able to take and accept an electronic lab result. Could
you, similar to the question asked earlier, give an assessment of where
we are nationally in terms of having epi outbreak systems that can
indeed accept electronic lab results and then use them to help support
an outbreak?

**[\>\> Janet Hamilton:]{.underline}**

This is Janet Hamilton. I don\'t think that I\'m probably the best
person to speak on all systems. But it is, I think electronic lab
reporting, in and of itself, is a challenge. We are challenged right now
with bringing electronic lab reporting in appropriate standards formats
into just our surveillance module. In terms of our outbreak module, when
it was initially built it did not accept lab reports. Lab reports were
essentially added as questions. So was this sent to the state lab, did
it have a positive result for X, Y, and Z? And that was definitely
recognized as a limitation. Currently our system does not allow you to
attach a true lab report to an outbreak case, but we expect to have that
in place by the end of the summer. The development is currently there
for it, and that was recognized as a real limitation, too, in the
surveillance piece. Because maybe you have the lab attached on the
surveillance side, but it is not available to you on the outbreak side.
And I would imagine that since there are so few outbreak management
systems available in states, that there are, that\'s probably a
limitation of many of the systems.

**[\>\> John Lumpkin:]{.underline}**

Steve, did you want to ‑‑

**[\>\> Steve Solomon:]{.underline}**

No, go ahead.

**[\>\> Tim Morris:]{.underline}**

I just wanted to answer that question really quick, too. I don\'t have
the specific numbers. Don\'t quote me on these. But certainly, again in
the Division of Integrated Surveillance at CDC, would have good numbers
about the, at least from our national ELR pieces, that CDC works with
commercial labs to provide, the number of connections we have there, and
there are a number of those. But when you talk about a system, sometimes
there is multiple. There is not full integration of systems at the state
level, as you know. And so the key piece there is that brokering
technology or integration technology to not only take that source, and
as many data sources, maybe the national feed that we might be helping
to broker, but also all the local private labs and other labs that they
have, and their public health labs, that is a smorgasbord of formats.
Maybe all HL7, but it\'s 2.3.1, 2.3, 2.4.Z, 2.5. And normalize that into
a given, you know, a standard. Maybe they standardize on 2.5. And then
feed that off to these different systems. So that, and I think we are
making some inroads there as well through some activities that are going
on, again in the Division of Integrated Surveillance, and working with
commercial partners for providing some wrappers around their integration
solutions that allow for that mapping. The State of Texas took about two
months to map in all of their ELR sources in the state, plus the
national ones with this tooling and is able to provide these off, say
for TB, and they can do routing based on content. Some real capacity
development I think is happening there, and it\'s spreading to maybe 20
states or so now.

**[\>\> Annie Fine:]{.underline}**

This is Annie Fine in New York City. I would like to address that
question briefly. We have definitely ELR reporting now to our
surveillance system, although we are working out the kinks in that. But
in terms of outbreak ELR reporting, I just want to make the point that
here at the Bureau of Communicable Disease and elsewhere in the health
department, we have hundreds of outbreak databases. We don\'t have one
outbreak database because there is none in existence, as I think Janet
was saying. We tried for SARS, anticipating it, to set up messaging from
our public health laboratory in anticipation to an Access database with
a SQL back end. And we tested it, and it worked. That\'s the only
instance I\'m aware of in which we actually set up, even from our public
health laboratory, electronic reporting into an outbreak database. So
currently we don\'t have it. And I would suspect that for some state, at
the state level maybe the states have it. But at the local level, I
would suspect almost none, or maybe none.

**[\>\> Marion Kainer:]{.underline}**

This is Marion Kainer inTennessee. I don't know the full number, but
I\'m not aware of any outbreak management system which currently
receives ELR messages.

**[\>\> Janet Hamilton:]{.underline}**

Well, this is Janet Hamilton. Just to add on that, we also deal with
outbreaks of non‑reportable diseases. So that again makes it a challenge
in terms of receiving that kind of electronic lab data. Because that\'s
not, we have in Florida statutes essentially a caveat that says any
outbreak is reportable. But if we are not already receiving that kind of
electronic message from labs, we obviously won\'t ever get that. Now,
for the state lab, we will be implementing a procedure where you can go
and search for things that are essentially non‑reportable. So if you
knew what you were looking for, you can search for it, but that\'s
really the only lab that we'll have the opportunity to do that with.

**[\>\> John Lumpkin:]{.underline}**

We are ‑‑

**[\>\>]{.underline}**

Thank you.

**[\>\> John Lumpkin:]{.underline}**

‑‑ past our time. Are there any last‑minute ‑‑

**[\>\> Annie Fine:]{.underline}**

Okay. One last‑minute point from New York City. I just wanted to add
that in an outbreak the laboratory data that one would ideally want also
would include pertinent negatives, as well as positives for alternative,
perhaps non‑reportable, perhaps non‑etiologic agents for the outbreak.
So for example, in a respiratory outbreak, you would like to know if a
patient was RSV positive, even though that\'s not the cause of the
outbreak. We like to know if the flu test was negative. So those are
not traditionally reported through electronic laboratory reporting and,
you know, I don\'t know how much of a challenge it would be to turn on
in an outbreak.

**[\>\> John Lumpkin:]{.underline}**

Okay.

**[\>\> Theresa Cullen:]{.underline}**

This is Terry. I had one question for Dr. Kainer, and it was related to
your slide about the priority of what people thought was important
information. This is really from the AHIC perspective. Given that
electronic health records is pretty low on the priority, but yet above
it are things that are contained in the electronic health record, at
least good electronic health records, things like (inaudible) lab
and immunization data. Was it because people interpreted the EHR as ‑‑
that that other data could be maintained in separate datasets so you
didn\'t need to have an electronic health record?

**[\>\> Marion Kainer:]{.underline}**

I think it was the data which was not captured by the other systems, how
important was it to capture that data, is the way I would interpret
that.

**[\>\> Theresa Cullen:]{.underline}**

Okay. So the assumption was there was a separate way to capture lab and
immunization data.

**[\>\> Marion Kainer:]{.underline}**

The first priorities would integrate with surveillance systems that
people don\'t have to do double data entry. The second one was really
the exchange of laboratory information and also the immunization
registry for vaccination data.

**[\>\> Theresa Cullen:]{.underline}**

And let me just interrupt, I\'m sorry. So that would be not exchanged
with an EHR but exchanged for instance with lab to lab or lab to public
health department?

**[\>\> Marion Kainer:]{.underline}**

That is correct.

**[\>\> Theresa Cullen:]{.underline}**

Okay.

**[\>\> Marion Kainer:]{.underline}**

Does that answer your question?

**[\>\> Theresa Cullen:]{.underline}**

Well, it does answer my question. I think there may be an opportunity
however from an AHIC perspective at some point to discuss whether that,
the way people are interpreting EHR in this setting may be limiting the
possibility for what EHR at the local level can bring to the table in
the future.

**[\>\> Marion Kainer:]{.underline}**

I think this was more a case of how important is it right now in giving,
trying to give a sense of prioritization.

**[\>\> Theresa Cullen:]{.underline}**

Right.

**[\>\> Marion Kainer:]{.underline}**

The real need right now is really the lab, getting lab information and
surveillance information exchanged. Not that EHR would not be helpful.
Not denying that at all. It is just the primary priority right now is
not to have to do lots of double data entry into the surveillance
outbreak management systems and to get the electronic lab records.

**[\>\> Theresa Cullen:]{.underline}**

So one of the proposed responses however may be that if there is an
integrated EHR and that is already collecting its own lab data and
bidirectionally interfacing with reference labs, it could clearly act as
a source of information for the public health in this case, health
departments.

**[\>\> Marion Kainer:]{.underline}**

Absolutely. I think there is huge opportunities there. I guess what is
the ‑‑ I think this is a reflection of what their primary priorities
were. Because people are frustrated that they cannot at the present time
exchange information with those other systems.

**[\>\> Theresa Cullen:]{.underline}**

Thanks.

**[\>\> John Lumpkin:]{.underline}**

Thank you. And at this point we are scheduled to take a break, which
some people may use to go up and get lunch. But regardless of how you
use this break, we are going to start back at 1:00.

**[\>\> Janet Hamilton:]{.underline}**

I just wanted to provide one last comment. This is Janet Hamilton. I
think this is a really useful opportunity and experience, and I think it
is a really wonderful start. And I can only encourage that, that this is
something that\'s continued on. I mean, I\'m just one state representing
here, but I think that there are a lot of other state and local county
health departments that would have some really valuable input into this
process. Thank you.

**[\>\> John Lumpkin:]{.underline}**

I would like to thank you and all the panel. It was a very excellent
presentation for those of you here and those on the telephone. Thank you
so much.

**[\>\>]{.underline}**

The lunch room, for those of you who don\'t know, is on the eighth floor
of this building. You should have enough time to get lunch and eat there
or either bring it back. Whichever you'd like.

**[\>\> John Lumpkin:]{.underline}**

Thank you.\
\
\[lunch break\]

**[\>\> Judy Sparrow:]{.underline}**

Dr. Lumpkin?

[**\>\> John Lumpkin:**]{.underline}

Thank you. Good afternoon. And today we\'re going to continue on with
our discussion and we're going to move into the laboratory arena. And
why don\'t we start off with Norman?

[**\>\> Norman Crouch:**]{.underline}

Thank you very much. I appreciate the opportunity to talk about the
laboratory and the data management aspects there. What I want to do is
just start off with giving an overview of the state public health
laboratory. And really the message that I want to bring to you is the
importance of networks within laboratories, between public and private
entities. First slide, please.

I\'m going to give a rather broad overview and then my state laboratory
colleague, Steve Hinrichs is going to give more detail regarding the
detail matters. When we talk about essential lab connectivity or
networks, we really, for the purpose of this Workgroup we\'re focusing
on the population health labs which would include the state public
health laboratories and also local public health laboratories, and then
their connectivity with the clinical care labs. For the most part we\'re
talking about clinical-based hospital laboratories but we're also
talking about the large commercial laboratories. And I think my last
slide will talk about some of the challenges with that.

But when we think in terms of the state public health laboratories'
perspective, not only do we need to have a connectivity, central
connectivity with the clinical care laboratories, but there are other
laboratories that we also have to have a connectivity to. Those are the
state veterinary laboratories as well as state agriculture for
food, state veterinary for animals, for zoonotic diseases that might
impact public health, and of course state environmental laboratories for
environmental factors that might be important in an incident. Next
slide, please.

I want to point out the unique characteristics of the public health
laboratory. There are unique functions as well as the diagnostic work
that we\'re all familiar with. Really from a public health standpoint
some of their unique functions are their role in detecting outbreaks and
also investigating outbreaks in collaboration with the epidemiologist.
But we also, in the public health laboratory, are highly involved in
monitoring trends like antibiotic sensitivity and resistance to
antibiotic use, as well as assuring quality practice as we interact with
our other laboratories and networks. As we talk about laboratory
networks, there are a few states that really have developed fine-tuned
laboratory networks I\'m going to be describing. Other states are really
moving forward in that direction, rather robustly, as we talk about the
LRN and some things I\'ll be mentioning later.

But it really is a direction that the laboratories are going. Now the
health impact of these connectivity, or the special public health
laboratory function, is that the public health laboratory, the data that
we generate, inform interventions by the epidemiologists and the medical
community as well as supporting policy that might have public health
impact. Really, if you stop to think about it, the laboratories and
these laboratory networks are really in the business of providing data
for decision-making regarding intervention and policy. Next
slide, please.

Now, it\'s important I think to just quickly compare the lab missions of
the clinical care laboratories and the public health laboratories.
Clinical care, of course, focuses primarily on diagnostic testing, they
do some reference testing depending on the size of the clinical
laboratory. But their focus is really medical management and they\'re
focusing on individuals. In contrast, the public health laboratory does
some diagnostic testing, particularly sexually transmitted
diseases, things of that nature. But they do a lot of reference
testing, esoteric kinds of organisms that might be detected in the
state. But also, their primary function is surveillance and monitoring
which is related to the previous slide. Their focus then is on
population. On the one hand you have individuals and on the other hand
you have population. But really, when you start thinking about
networks, it\'s very important that those two are linked, because
there's an interdependency. Both provide data for decision-making. In
one case, patient management by the physician and the other case by
intervention and public policy. And they both act to identify public
health threats. Next slide, please.

Now, there are already existing networks that I\'m sure you\'re all
familiar with. There are actually three of them, the Laboratory Response
Network that was originally set up in 1999 to deal with, begin to deal
with terrorism preparedness. It started out biological and now it\'s
also been expanded to some aspects of chemical terrorism. In
addition, there\'s the National Laboratory System, which is being
developed. It is fairly developed in about six states, including
Minnesota, Nebraska, Michigan, Wisconsin and Massachusetts. And one of
the functions of the National Laboratory System is to improve laboratory
practice through this interaction or the network that the clinical care
laboratories and public health laboratories. And the public health
laboratories are taking a leadership role. And then finally the third
network, I just want to the mention, is the National Molecular Subtyping
Network, and this is known as PulseNet. This has really been a
remarkable network in detecting, early detection and response to
food-borne infectious diseases. This is not just a national network but
now it\'s becoming an international network, which I suspect in the
future all of these laboratory networks will have a national component.
Next slide, please.

So basically, this is the structure of networks we\'re talking about. On
the bottom of this pyramid, have you all these sentinel laboratories.
We\'ll be talking here today about the clinical care laboratories. If I
recall, there\'s something between 25 and 30,000 of these sentinel
laboratories. They interact with the public state labs in the networks
that we\'re talking about and the state public health laboratories
interact with, primarily with the CDC laboratories. And the CDC provides
definitive characterization of agents that are identified at the state
level. They provide training. They provide materials, and technology
transfer. Next slide, please.

Now, if you tilt that pyramid over on its side, you see there on the
bottom, you have all these laboratories that are the sentinel
laboratories. There are a very large number of these in my state, which
is Minnesota. We have 125 of these, which is rather a small number
compared to a state like California or Texas. These then include not
only the clinical care as I mentioned in the first slide, but also local
public health, veterinary laboratories, as well as agriculture
laboratories that can serve in a sentinel function. And these
laboratories then provide microbial isolates, or in some cases
specimens, to the state public health laboratories that serves as a
reference laboratory and then we of course interact with the CDC. Next
slide, please.

On the next slide, you\'ll see, on the left you see these are healthcare
institutions, hospitals, for example, clinical care. And you have the
patient, you have the clinician for the patient, and then you have the
laboratory that may be providing diagnostic work-ups for that
patient, for that doctor. And the isolates that are obtained from the
patients, or specimen in some cases, are then sent to the public health
laboratory where we do identification, confirmation, and subtyping. Very
often, the initial identification is done in the clinical care
laboratory. But, sometimes, the, because the state laboratory has a lot
of reference capability, the identification is actually done in the
state laboratory. And so this is a system that really is tuned for very
early detection. Because if it works well, you have these networks
really functioning, you get all of these isolates and specimens coming
over from all over the state jurisdiction so that we can identify them
through confirmation and subtyping for the possibility of outbreaks
occurring. Next slide, please.

These are some applications that we have in Minnesota using these kinds
of networks. We do this networking for anti-microbial resistance, for
emerging infectious disease, for invasive infection outbreaks, for
food-borne outbreaks, and also for bioterrorism. And we put together in
our state and other states have similar systems. We call this the
Minnesota Laboratory System, and this is the public/private network.
It\'s an integrated network, voluntary network, but all of our clinical
laboratories are very, very, engaged in being involved in this. Next
slide, please.

Now, examples of the network application, I have two examples. One would
be the anthrax incident, and of course the laboratory network was
fortunately in place in September 11th in 2001. But as far as the data
exchange capability at that point, it was very, very limited. It\'s much
better now. We have results messenger, which enables laboratories in the
Laboratory Response Network, if there would be something like an anthrax
incident or another kind of biological agent, we have the capability now
to enter things directly and go directly into the CDC. I would just like
to make one comment with that, though, that while that really is a very
important step in the right direction, it\'s very time-consuming at the
state level. And so, we, together, need to work with the CDC to improve
that. And, of course, the Minnesota Laboratory System, I just want to
use that as an example.

In the anthrax incident we already had our MLS in place. And when 9/11
occurred, we were, within a few hours we had contact with all 125 of our
clinical laboratories and put them on alert. Of course, this was before
anthrax. We didn\'t know what biological terrorism agents might be
coming down the pipe. We were able, through this network, this
system, able to identify or notify them very quickly. In addition, when
we had the anthrax we were able to do active surveillance. Every
morning, by noon, we had ten of the major clinical laboratories reported
whether over the night or during the previous day they had seen anything
that looked like a gram-positive rod, and so that was active
surveillance.

We've used it for other purposes as well. We had a situation in our
state, in Minnesota, a few years ago were there was three cases of
deaths in young, healthy individuals that had knee surgery. And we
isolated a very unusual organism in our reference lab, a Clostridium,
and we were able to get that out to all the clinical laboratories so
they were on alert to see if they were finding this organism in any of
their patients. So it works not just nor emergency events but in
general. And pandemic influenza preparedness, the systems are also very
important in our state. We have a sentinel set up, we have 27 sites that
report into the laboratory by sending isolates or specimens and with
this kind of network we know what laboratories out there are actually
detecting influenza using direct assays, and which ones are capable of
sending isolates, which ones are capable of actually isolating the
virus. And so that interaction is very important. And, of course, as we
look at pandemic influenza preparedness the LRN is a very important part
of that. Next slide, please.

Now, looking at this lab connectivity, again, I just want to point out
where some of the most important parts of data exchange are. And, of
course, there are two. One is the data exchange between the CDC and the
public health laboratory, the state laboratory. And the interchange
between, the data interchange between the state public health laboratory
and all those sentinel laboratories in the network. Next slide, please.

And this is a slide that lists some of the data exchange partners that
we have to be very interested in and concerned about and hopefully we
have connectivity with in the future. And this would include of course
all our sentinel laboratories, the CDC, the agency epidemiology
program, public safety officials when we have outbreaks or if we have an
emergency event of some kind, public safety gets involved and we need to
have connectivity there, as well as other state laboratories. Next
slide, please.

And these are some of the data elements that need to be considered.
Accessioning samples and specimens, that\'s an obvious one. Reporting
analytical results back to the submitters that give us isolates and
specimens. And the third one is integrating lab data/epidemiology case
data. Dr. Layton in New York City referred to that this morning, how
important it is. In our state we\'re trying to integrate the database of
the laboratory with the database of the epidemiology group. Because that
way we can make much more robust case input and so this is very, would
be very helpful to us. And, of course, we have to be able to report
analytical results to the lab network and collecting the sentinel lab
capacity and capability data. As you set up these networks you need to
know what capacities and capabilities are out in those network
laboratories. And so we need to have a data system to keep track of that
so it\'s updated on a regular basis, et cetera. Next slide, please.

Some of the barriers to an integrated network: rapidly changing
information technology, and of course we heard a lot about that this
morning. It\'s hard to \-- there are many systems out there and
information technology is rapidly changing. There\'s a lack of public
health laboratory standards that these requirements need to be
identified. I think we\'re making some great progress along those lines.
It\'s high cost to develop and maintain the systems. Some laboratories,
both on the clinical side and public health side, don\'t have LIMS
systems and certainly that is going to be required. And of course
there\'s limited state public health laboratory input. And I mentioned
the LRN results messenger, the fact that this is really a very important
step in the right direction, but it\'s very difficult to use that, it\'s
very time-consuming, it's not difficult, so there has to be a way to get
public health laboratory input as we design these systems.

And finally, next slide, the last slide, I mentioned the large
commercial laboratories, which are part of that sentinel capability.
And, of course, a lot of the diagnostic testing that is done is done in
the large commercial laboratories. And it\'s a real challenge because
there\'s an absence of reporting standards for them. They need to be
involved in multi-state reporting, and also with isolates and such.
That\'s a real challenge because states differ so much. There\'s
state-specific recording requirements that they need to know about, so
it would be helpful to have standards. And there\'s no acceptable place
to send the reports because they\'re out there doing all this reference
work for a lot of different states and a lot of different clinical
laboratories within those states. And so it\'s very complicated for
them. That\'s an area that we have to improve. Thank you.

**[\>\> John Lumpkin:]{.underline}**

Thank you. And next, Dr. Hinrichs.

**[\>\> Steve Hinrichs:]{.underline}**

Thank you for the opportunity to provide this testimony on behalf of the
APHL. I\'m a board member of APHL and also the immediate past chair of
the informatics committee of APHL and I\'ll be making remarks in regards
to the contribution of public health laboratories to event detection,
response, and management. Next slide.

We think it\'s very important that we keep our eye on what we want. We
have a long-term vision of where we're going with this whole activity.
In addition to detection I think it\'s important that we recognize that
it\'s also situational awareness that we want out of this electronic
system. And that\'s a term actually outside the military arena that I
first heard from John Loonsk when he said to us how are we going to be
able to give data back to our systems to know how well are we managing
an outbreak? How well are we, how well are our response efforts dealing
with the problem? And if we can\'t decide situational awareness, we
really have not captured the entire scope of what we\'re trying to do.
So laboratories, as you might suspect, say that, outside of the realm of
pharmaceuticals, laboratory data is the low-hanging fruit. It\'s the one
area where we think we can actually contribute a great deal in the least
amount of time to our ability to provide not only early detection, but
also situational awareness. Next slide, please.

We\'ve gone to great lengths to go about mapping the public health
laboratory information pathway, to not only manage or look at the issue
of event detection, but also response. Laboratories are involved in
events in a number of ways. Particularly, we may be called by the
epidemiologist to investigate a situation and provide an answer
regarding a patient specimen. But it\'s also important to know that our
involvement in incidental events, meaning they are initially detected in
the laboratory. I\'ll provide examples of this shortly. But the point
is, each of them results in data that must be transmitted back to
someone. In the present situation that information is transported back
either by phone or paper or electronically. But that only tells half the
story. Meaning that is getting the data out. What I think is the other
half of the story is that our partners are telling us that if we want
them to send electronic data to us, the government and state
laboratories must be in a position to send electronic data back to them.

That is a very important issue that we cannot ignore. Next slide.

APHL has been working on this problem for a number of years. Shortly
after 2001, we began a very detailed advanced planning strategy that
looked at both short-term and long-term goals. We recognize the
challenges are enormous. But we have to take a systematic approach to
this problem, otherwise we\'ll never make any progress. So within the
APHL informatics program we focus on a number of issues, including
shared resources and collaborative activities. We will have these as
appendices or additional information should the group or the committee
ask for them. Particularly we wanted to emphasize such things as the
collaborative requirements document, whereby we went through every
public health laboratory and said, what are the core functions of the
laboratory, which elements of those functions can be captured
electronically, and how do you write those requirements down on a piece
of paper. Very significant event in the life of public health
laboratories. In addition, we conducted and continued to conduct
surveillance activities about what is the capability of public health
laboratories across the country to pull in electronic information and to
ship it out. So in a sense, we have the ability to define the state of
the states relative to laboratory function. We also engaged in a number
of collaborative activities, including what we call the LIMS
collaborative user group whereby every public health laboratory that has
a commercial LIMS is able to share with its partners in the business
what is it that they need and how are they going to make improvements in
the future, as well as such other activities as open source LIMS
development project. Happy to take more questions about that in the
future. Next slide, please.

So if someone were to ask, what has this advanced planning led to, for
example, what are you going to do tomorrow, should we have a national
emergency. We can answer that we actually have a short-term strategy
whereby we can transmit through the web a spreadsheet-type format
response or summary of information. Now, we want to immediately say
that\'s not the optimal solution. But that\'s one that we could put out
there if we needed to do it. On the other hand, we\'re very much focused
on the long-term solution. And the long-term solution is one which is an
automated multi-directional electronic transmission of laboratory data.
But therein lies many of the complex issues that I know this group has
been dealing with and talking about. Because it also involves something
else beyond that large-scale ability to ship data, and that is for the
laboratory purposes and our customers, that is our partners who order
lab test from us and want results, they want to be able to place those
orders electronically and receive those results electronically. And to
that degree, we have been involved on a number of specific activities
and I\'ll be detailing those now. Next slide.

So, for example, a public health laboratory is, realizes on a daily
basis that we are dealing with local events that have national
implication. For example, a patient death that we were asked to
investigate on behalf of an epidemiologist: the patient presented with
diarrhea. We collected a food sample and identified and recovered an
organism. We were able to use a profile that we generated from it and
compare that molecular fingerprint to one which was available through
PulseNet and determine that three months after the original event in
California, we had a patient who had died from E coli, having eaten
spinach. In addition, we were able to use a similar technique but back
to the incidental way it occurred we began to notice we had an usual
number of salmonella Tennessee and the pulse field pattern matched and
as we began to submit that data and began to see that data grow
nationally it became obvious that there was a national outbreak,
associated with a single type, or single strain, of salmonella. Now that
data is transmitted, as Norm said, in a number of ways such as through
the LRN messenger, or through PulseNet, et cetera, but there are other
ways in which that data can be transmitted, ad we move that data around.

Now, with that in the background, I\'d like to say or draw attention to
a couple other key capabilities and essential functions that a
laboratory has that ELR must be able to handle. One of those is surge
capacity. Perhaps for you this is not as visible as those other
activities, such as detection of food-borne illnesses. But for us, surge
capacity is critical when a state such as mine was challenged by West
Nile virus. We were virtually filled with capacity or our capacity was
virtually filled and we were beginning to say, what of our neighboring
states can help us? The problem became, we were not going to get any
advantage by using our neighboring states because they could not accept
our electronic orders or receive results back from us. So we began to
work on that issue in a great more detail. Next slide.

Another major function of laboratories that we have to deal with
nowadays is the issue of continuity of operations. So should any of our
laboratories, such as those destroyed by Katrina in Louisiana, be
destroyed by, say in Nebraska, a tornado, we again need to be able to
turn to the neighboring states and say, can you help us, can you perform
those key functions for us until we get our feet back under us. But in
order to do that, we need to be able to standardize not only the data
but also the methods. As part of the surveillance activities we surveyed
14 public health laboratories and found only two had the same
terminology and the same electronic terms for the information and the
technologies that we were looking at. We obviously have to do a much
better job at coordinating not only the ELR but also the methods and the
ways in which we describe those methods.

So really this leads to the national planning coordination efforts that
we\'ve all been talking about. But it\'s important to realize that
laboratories do much more than testing. They \-- testing human samples,
they do testing of all kind of samples, including the air, the
water, the soil and animal material. That\'s where the issue of the
integrated consortium of laboratory networks comes in. For that matter
I\'m going to let our next speaker detail more of those issues. But
it\'s a very important one that the community needs to be aware of and
focused on. Next slide

So what we really have been focused on within APHL and with our partners
in CDC and elsewhere is the public health interoperability project. In a
nutshell what it is trying do is take a community solution to ELR., by
using not just standard public health strategies but also bringing in
corporate strategies to problem solving. So these might involve such
things as the iterative process, as well as utilizing a team approach
with Six Sigma-type strategies to arrive at consensus and identification
of problems and solutions. One of the biggest problems we\'ve identified
as a task force solving is this issue unifying, or putting a uniform
format to, de-identified surveillance results. It\'s going to be
essential that we be able to identify whether or not we are seeing
duplication of specimens and/or results.

We've also had to struggle with the issue of how do we get results into
multiple systems simultaneously so our state or local epidemiologists
are satisfied that they\'re receiving results when and as soon as they
become available? So we focused on harmonizing data elements,
particularly as it relates to influenza. Influenza is the driver of all
our efforts at the present time, and we've made great success by
focusing on a single topic. What we've basically accomplished now is the
prototype message structure, acceptable to six laboratories and the CDC,
for dealing with pandemic influenza and influenza, seasonal influenza.
Next slide.

So some of the major outcomes that we've already encountered are we now
have a uniform or a standard message structure. And it\'s not just
applicable to influenza, but t\'s applicable to virtually all of the
notifiable or reportable diseases. We\'re able to incorporate high-level
as well as granular descriptions of laboratory tests including standards
such as LOINC and SNOMED. But we have also identified a number of
additional challenges that we can discuss at a future time. We have a
collaborative resource portal, and the essential reason for that is that
what\'s the purpose of us going to all this trouble of describing these
lab tests and these lab types if we cannot share them with our partners.
Basically our public partners have said we would be happy to use LOINC
and SNOMED in our reports, but we don't want to have to determine what
that is. If you would tell us what LOINC and SNOMED you want us to use,
we will put it in, and you have to give it to us in a place we can find
easily. In the long run, all these activities we believe, will be able
to be incorporated and used in connection with regional health
information organizations. Thank you.

[**\>\> John Lumpkin:**]{.underline}

Thank you. We\'ll move on to Dr. Miller.

[**\>\> Mike Miller:**]{.underline}

Thank you very much, and for the opportunity to be here this afternoon.
It\'s very fitting that the CDC laboratory component followed my public
health colleagues, because the public health labs remain, indeed, our
primary clients. When I would like to do is take you on a brief
laboratory tour, if you will, of the Coordinating Center for Infectious
Diseases. So walk with me through some of CDCs laboratories and
laboratory activities, beginning with the next slide, you\'ll begin to
see how some of this will take shape.

The Coordinating Center for Infectious Diseases actually became official
just last week with the Secretary\'s signature. And as you can
see, there are four national centers within the coordinating center.
Now, within those four centers, there are 21 separate divisions, each
with their own missions. And, as indeed, each center has its own
mission. And in regards to our topics this afternoon, it\'s important to
note that each national center is responsible for essentially a
different set of organisms. They are organism-specific even within the
divisions. There is no central, core site or facility to receive a
telephone call from a state or an epidemiologist requesting help. That
call might go to any one of a number of people within the divisions that
are listed there. However, there is a central specimen receiving site
that is located within one of those divisions for all four of the
centers. And at that receiving site, the specimens are logged in and
then delivered to the appropriate laboratory. The response to an
outbreak from such a call may be very focused by one of the divisions or
it may be distributed throughout a number of centers that share the
responsibility for different organisms. And it\'s the relationships that
are both collegial and formal between the scientists of those divisions
that are critical to the success of completing an outbreak. Next
slide, please.

Within the Coordinating Center for Infectious Diseases, as I mentioned,
there are 21 divisions, and 15 of those have something to do with the
laboratory activities. Now there are over 1,000 laboratory sites within
CCID. Now, don\'t take that as a strict number, because the definition
of a laboratory is very varied. We have laboratory suites. We have
laboratories where the doors open and becomes one laboratory, or
three, or what have you. But there are over 1,000 sites where organisms
can be manipulated within CICD and then there's an additional 43 labs
within the National Center for Environmental Health. The surge capacity
of these divisions and within the centers are robust such that a very
large outbreak can be handled for quite some time before external help
would be requested. Of the 4,500 employees within the CCID, I estimate
that about 40 percent of those employees and contractors are actually
laboratorians. So that gives you an idea of how many people would be
available and are available for public health emergencies should they
arise. There are between 80 and 85 laboratories that are registered for
select agent work just at the Atlanta campus alone, and this does not
incorporate the campuses at Fort Collins, Colorado; Alaska; or Puerto
Rico. Next slide, please.

For laboratory response activities within CDC, we can look at a number
of activities that occur continuously. Surveillance and response is
certainly critical to all of CDC's activities. We have reference
identification capability. We certainly conduct public health research,
and application of that research. We\'re involved directly in pathogen
discovery as we are in vaccine discovery and adverse event tracking. Our
laboratories are responsible for incredible repositories of organisms
that are unmatched anywhere in the world. Preparedness and response to
all public health emergencies are a hallmark of CDC\'s mission. In
addition we provide laboratory support to our internal and external
partners through training, through providing new and novel laboratory
methods, providing products of test development and deployment, and
certainly laboratory service on a long-term schedule. Now, with that
said, you can see that there is a huge knowledge ecosystem that is in
place and that is required throughout all of CDC, reaching out
particularly from our public health partners and our external partners.

There are a number of other partners, as you can see on the next slide.
The primary clients remain our state public health agencies. But we also
work very closely with world health agencies, virtually every agency
within the federal government, with private sectors, academia, the
medical community, and virtually any other groups with a public health
mission. Next slide.

The interesting part of our work in the laboratory is that we, in
fact, do get these calls on outbreaks or diseases, many of which are of
unknown etiology. And the tracking information that is required is even
more complex, very often, when it cannot be attributed to a specific
organism. For instance, in 1976, we\'re all familiar with the
respiratory disease in attendees of an American Legion convention in
Philadelphia which we now know is, the organism is Legionella. In the
early 1980s, acquired immune deficiency syndrome initially emerged in
men who had sex with men. In 2002 and 2003, severe acute respiratory
syndrome became known as SARS, through that viral illness. Severe
pulmonary disease in the Four Corners region of the United States became
known because of the introduction and the recognition of hantavirus. And
then there\'s a number of illnesses which we don\'t have an etiologic
agent at this point, we just have descriptive symptoms such as febrile
illness, rash illness. Nothing else to attribute it to.
Encephalitis, jaundice, infectious diseases from transplant, and very
interestingly, just unexplained death. Now many of these have been
caused by novel etiologic agents that are now fully characterized
because of the work that is done by CDC and our partners in public
health and in the medical community. Next slide.

Now, this challenge of unknown etiology does not stop with the ones that
I just mentioned. For instance, it\'s very clear that 25 to 50 percent
of the cases of acute respiratory illness is still, has no etiologic
logic agent attached to it. When we get cases of encephalitis, 50 to 75
percent come with no known etiologic agent. The same with acute
gastroenteritis. We still do not know the agent of (inaudible)
diarrhea, Crohn\'s Disease, non-cultivable pathogens, patients with
jaundice, isolates that resist identification or characterization by
standard methods, all of these are usually addressed initially at the
state public health level and find their way to CDC where we work
together to try to resolve the outbreak that resulted.

The next slide will show you a list of the tools these laboratories use
on a daily basis. The tools are varied from phenotypic analysis, for
instance the old test tube method of defining organism to the more
(inaudible) that are used extensively, including the fingerprinting
through PulseNet that was mentioned just a few moments ago, but these
laboratory tools all require a reporting mechanism. Many of those are
instrumented methods that need to be able to provide the results to a
standard type of report that goes back to the initiator of the specimen.

The next slide will simply reinforce the unique roles of CDC. Clearly
public health in the states have a unique role, as was just
discussed, in terms of support of the clinical laboratories. In our
support of public health, CDC also has some unique roles, that being we
have the ability to assess national and international events with a
broad base of expertise throughout the Coordinating Center. We can
deploy investigative teams on very short notice and we can employee
multiple large teams on relatively short notice, also. We can mobilize
resources as needed to accommodate surge capacity demands of larger
outbreaks. We can apply pathogen discovery tools, temporal data analysis
with sometimes redirection of that data and the results. Because
when, many times, an outbreak may begin in one division, it may, in the
middle of the investigation, be determined that it\'s a totally
different organism than was suspected and we then move to another
division to complete the complex work. The next slide

In addition, extensive specimen inventories and data banks are
available, and especially useful are reference laboratories that can
identify the most difficult organisms that we see today. Now, the
average outbreak, the title of this next slide is how the average
outbreak is handled within CCID. I think you heard several examples of
how outbreaks are initiated and how they're followed. I won\'t go into
detail on this except for our standpoint, a call is received by one of
the groups at CDC. That call is going to be accepted. We cannot go into
a state without being invited. And after that call is accepted, it\'s
determined who should handle it, a team can be developed, deployed, if
necessary, the cause of that outbreak would be determined and then
future work for research may be determined based on the resolution of
that outbreak. Now the interesting part about this, even at CDC, this is
still a manual process of resolving these outbreaks. Even though some of
our reporting is certainly electronic, the process of getting to the end
is often manual. There is human interaction, which is critical. And the
work is often conducted in parallel with a number of laboratories where
the data exchange between those laboratories, internally as well as
externally, needs to be published.

The next slide will show you just in the food-borne area the number of
surveillance tools that are available and currently being used. FoodNet
is a food-borne disease active surveillance network. The National
Antimicrobial Resistance Monitoring System is used for human, food, and
animal isolates. PulseNet was discussed earlier, as a DNA fingerprinting
tool. There\'s an OutbreakNet. There was an initial effort to create a
National Electronic Disease Surveillance System, which was NEDSS. That
is struggling and is not yet successful. And then there are others that
have been discussed here today. So all of these require complex
information technology interactions, but they are not necessarily
interconnected among themselves. The data entry, the tracking, the
reporting, and the access are really not interconnected at this point.

The next slide will illustrate before we talk about the laboratory data
exchange, some of the challenges that we face in the laboratory.
Now, you\'ve heard the politically correct word of challenge. We don\'t
say problems anymore. But some of these are what would I term
insurmountable opportunities, if you want to use a little more creative
term for the problems we have. But one of those might be resolving
outbreaks of unknown etiology. It is clearly a challenge that requires
unique skills and unique data exchange.

Another problem that CDC is facing is GMP development of Assays in a
non-manufacture arena and getting FDA approval of those public health
assays in a timely manner, especially for emergency need such as
bioterrorism, or very large, novel outbreaks. Competing resources, as
with everyone else, could result in a reduction of laboratory capacity
and our ability to respond.

One of the problems we face in the laboratory, is recruitment and
retention of top laboratory scientists. And I think all of our
laboratories, from the sentinel labs through CDC, is facing that same
problem. Developing the next generation of public health leaders is
something that we see as a critical issue and those public health
leaders needing to understand, in a very detailed manner, the critical
nature of this data exchange, a necessity. The complexity of our
electronic communication needs, I think we\'re seeing more of that
discussed today. And certainly, integrating the critical public health
information and tracking in a secure efficient and accessible format is
one of the primary challenges we face in the laboratory. Thank you.

**[\>\> John Lumpkin:]{.underline}**

Thank you. Emory Meeks?

**[\>\> Emory Meeks:]{.underline}**

I would also like to take this opportunity to express my appreciation
for being able, for being allowed to participate in the discussion, this
important discussion on laboratory response informatics and take the
time allotted to me to give you a brief overview of our work in this
arena. Next slide, please.

Clearly the pressures of public health preparedness require that public
health labs be able to electronically share test results in real-time.
Laboratory data are key to the decision-making processes of counter
measure and intervention, outbreak management, and other public health
response activities. In order to enable this, public health labs must be
able to share sample information, test orders, and test results in
real-time or at least near real-time. The ability to collect data in a
timely and standard manner to support early detection. Timely difference
of laboratory results to decision-makers ensures earlier detection and
identification of potential public health emergencies. Because of the
many organizations involved and the many groups that require results
from labs, industry standards for results reporting are a critical
component of ensuring that all parties can access results when and where
they need them. Next slide, please.

As an example, I\'ll use the CDC\'s response to the anthrax incidents of
2001, during which over 125,000 samples, representing greater than 1
million laboratory tests, were reported to the CDC. At that point in
time, there was no support for electronic exchange of data between the
involved organizations. In addition, because of the number of
organizations involved in the response, and the fact that there were no
standards implemented at the time, management of the data was very
complex and resulted in many man-hours to consolidate and reconcile the
data. The net result was a significant reporting burden on participating
labs both at the CDC and with our state and local partners. Next
slide, please.

The anthrax events were somewhat unique in that they leveraged the
capabilities of the LRN. Dr. Crouch gave a good explanation of the LRN,
and so I won't belabor the point, but it's a coordinated network of
laboratories that do testing for both biological and chemical agents of
terrorism, the strength of which is the standardized reagents and
protocols used in the Network. It includes state and local public health
laboratories and a variety of other partners including FDA, DoD, and
USDA labs. Our informatics goals for the LRN are to strengthen
preparedness by enabling standardized, two-way standard electronic
exchange of specimen information, lab test orders, and test results,
both lab to lab within the network and between lab and the other
partners, such as CDC. Next slide, please.

Our strategy to accomplish this goal is based upon incremental
advancement toward increasingly robust IT solutions. In order to
accomplish this we've had two ongoing efforts, the first is the
development of the LRN Results Messenger. It\'s a standards-based
interim, or transition, application. The drawback is that it is separate
from a lab\'s own systems. It\'s somewhat of a siloed system. We
recognize that, but the application does provide immediate reporting
capacity within the LRN. The other effort is work towards guidance to
allow a lab to utilize their own systems to report in a standardized and
integrated way. Next slide, please.

The Results Messenger is currently deployed in approximately 94 percent
of the LRN. And of that 94 percent, that represents 100 percent of state
and public, state and local public health labs. The application provides
lab to CDC results reporting, lab to lab test requests and test
results, which support the routing of samples to other labs within the
network during surge situations and for testing that might be
unavailable at the originating lab. It also provides support for PT.
Results Messenger as a matter of fact was just used in the most recent
proficiency testing performed by the LRN. It has the ability to
automatically update the application and it provides routing within the
Biowatch program to BioSense and the Biological Warning and Incident
Characterization, or BWIC program. Next slide, please.

The parallel, well, the parallel efforts underway are LIMS integration
team. We view this as preferable to the CDC provided Results Messenger.
We really designed Results Messenger with somewhat planned obsolescence
in mind. We understand that it requires duplicate data entry. It was a
preparedness solution, and we would prefer that a state be able to
utilize their own LIMS. So we\'re trying to lay the ground work to
enable that. To do so, we\'re collaborating with subject matter experts
from the CDC and from nine public health laboratories. We\'re currently
providing to the labs system requirements to configure their LIMS for
LRN assays and we're providing a constrained version of the PHIN
laboratory generic message guide with mapping for LRN assays. All this
is based on the LRN protocols, so this is a specific effort towards LRN.
Next slide.

This is just a graphic that shows very quickly the message flows between
LRN labs, test order and test results between various LRN labs, and test
results to the CDC. We also share, like I'd mentioned before, we share
some of the BioWatch results with BWIC, which is the Department of
Homeland Security-sponsored program. Currently, we are not capable of
sharing results with other agencies, and that\'s something that needs to
be addressed. Next slide, please.

Our future plans for LRN data messaging are that Results Messenger will
handle data exchange for the chemical side of the LRN. Currently it\'s
only capable of handling biological assays, but within the next few
months we\'ll be rolling out chemical capability. We would like to
enable LRN laboratories to set up their own recipients such as local
health departments, so that they can share results with the locals. We
would encourage and assist labs implementing their own solutions via the
LIMS integration project. We would like to enable better integration
with other PHIN applications and services and then ensure
interoperability other agencies, via ICLN. And I\'ll discuss ICLN in \--
I\'m sorry. The Integrated Consortium of Laboratory Networks.

Um, I feel like I\'m on T.V. I\'m getting whispered to and I have a
headset.

**[\>\>]{.underline}**

Everybody may not know what PHIN is, that acronym in your last slide.

**[\>\> Emory Meeks:]{.underline}**

Oh. The Public Health Information Network.

Dr. Hinrichs described PHLIP, and so I won\'t go into detail here,
either, other than to say it\'s a collaborative effort between states,
APHL, and CDC, and the focus is to enable lab to lab data exchange of
nationally notifiable disease results, as well as between labs and the
CDC. One of the primary components, from our perspective, is vocabulary
harmonization. In the discussions this morning there was a lot of talk
about the standards, the current state of the standards, and Tim
mentioned that a lab, for any LOINC code there may be four possible
LOINC codes for a different assay that might be correct and might each
be used by four different labs. There has been to be some harmonization
in place so that everyone knows which codes to use. And then HL7 data
exchange. Next slide, please.

The laboratory data exchange needs basically are the need to refine and
consistently implement the standards for laboratory results and orders
exchanged. The need to harmonize requirements across agencies to reduce
the reporting burden on labs. This approach should be incremental and
should progress from basic capabilities to more complex. We have a
tendency sometimes to focus on the low-hanging fruit and overlook the
more difficult questions that need to be answered first. And, of
course, laboratories need funding for informatics. Not just the CDC, but
state and local labs as well need funding. We oftentimes run into kind
of the roadblock with the labs simply don\'t have the funding to do the
work that needs to be done in this area. Next slide, please.

Agency to agency collaboration that needs to take place, we\'re
currently working with the Integrated Consortium of Laboratory Networks,
or ICLN. This particular project was organized by the Department of
Homeland Security, it\'s goal is to promote harmonization and
coordination across multiple laboratory networks affiliated with federal
agencies that would include the LRN; NAHLN, which is the National Animal
Health Laboratory Network; FERN, which is the Food Emergency Response
Network; ELRN, which is the Environmental LRN; so on and so forth. And
the CDC\'s Division of Bioterrorism Preparedness and Response and the
National Center for Environmental Health, which handle both the
biological and chemical aspects of LRN are both involved in the ICLN
effort.

The next slide is a table that shows the task that we\'re up against.
When you look at, down the vertical axis is the various networks and
across the top are things such as transport protocol, data format, and
et cetera, and it shows the variability between the labs that currently
exist. So there\'s a lot of work to be done to harmonize these networks.
Next slide, please.

So the agency to agency issues that we see are that laboratory data
exchange may be enabled within a given network, such as the LRN, but
interagency data exchange has not been accomplished. And that public
health laboratories that belong to multiple networks are required to
report differently to each of these networks and that\'s adds a
significant load for those labs. And that prioritization and funding are
lacking to support interoperability between these networks. And with
that, I\'ll close.

[**\>\> John Lumpkin:**]{.underline}

Thank you, very much. Fascinating panel and presentation. To get the
questions started, kind of basing off of the slide before your last
slide, it seems like there\'s a lot of things going on around
standardization, harmonization, what can AHIC add of value to that
process? In other words, what can we recommend to AHIC that would add
value to the process?

**[\>\> Emory Meeks:]{.underline}**

I think that from my perspective, from where I sit, there needs to be,
and the recommendations made on how to implement some of the standards
that are already in place. We provide guidance, we utilize the
standards, we provide the guidance, but there\'s no overarching body, at
the moment, that is helping provide direction for implementation.

**[\>\>]{.underline}**

I\'m not going to answer for the panel. But I want to point out, just as
a, since we\'re on that particular slide, that it occurs to me, in
looking at all five of these networks, and there\'s one that sort of
nascent, the EPA, but that will come on, a single lab in the state, the
state public health lab, is the lab that is the member of the other four
here. And when you look across and down in the matrix and see all of the
various \-- this is the first time I\'ve actually seen this. And it\'s
stunning. And you wonder why we\'re pulling our hair out at the state
and local level? This just says it all.

**[\>\> John Lumpkin:]{.underline}**

When you run out of hair you leave government, right?

**[\>\>]{.underline}**

Well, getting to your point about what \-- \[laughter\] \-- so you\'re
saying there\'s a future in the foundation for me?

**[\>\>]{.underline}**

So if I could add to the recommendation that we would recommend that
this activity consider the full range of public health activities and
particularly as it relates to the laboratory and not just human
specimens. But every type of specimen, every type of sample that a
public health laboratory might encounter and it is all what is on
Emory's slide, it\'s animals, it's humans, it's water, it's the air.

**[\>\> John Loonsk:]{.underline}**

If I was understanding the thrust of the comments that Scott was making,
it would be very important to have a consolidated ask in terms of how
\--

**[\>\>]{.underline}**

Across government.

**[\>\> John Loonsk:]{.underline}**

Exactly. And what would that ask be?

**[\>\>]{.underline}**

I think just in terms of the standardization piece alone, just looking
at the harmonization, just look at HL7. Granted we\'re not part of
NAHLN, but you can see that that sort of thing play across. And this
doesn\'t bring in the complexity of clinical lab data. This is just
within government networks. We\'re not even talking about the connection
to clinical. So that\'s how complex it is.

**[\>\> John Lumpkin:]{.underline}**

I think that we would certainly appreciate some assistance, of
course, with Scott helping us on the committee, of language we can then
pass on to AHIC in regards to this aspect.

I actually have a very specific question which came up as I was
listening to this conversation and that has to do with vocabularies. We
have an outbreak of a respiratory illness with a high rate of mortality
in four contingent states in the southwest. And you come across a virus
that you had no experience. Is there a LOINC code for that?

**[\>\>]{.underline}**

Yes, there is. The way it would come out, as the order, would be for
viral culture. And it could be for general virus culture, it could be
for any number of tests related to viruses. And then the answer could be
virus detected, not further identified. It could come out as CPE
detected, submitted for further confirmation. So that entire outbreak
could all have fallen under that category or fall under that LOINC code.

**[\>\>]{.underline}**

What about the family of viruses?

**[\>\> John Lumpkin:]{.underline}**

But let me take that a little further, which is that one of the things
that the CDC lab does that I didn\'t hear discussed is the development
of reagents. So when I was in Illinois and we were doing West Nile, we
got all of our reagents basically from the CDC. So now we have this
agent that is identified, there are tests that can be done, there are
reagents which are not generally available in the commercial market. So
how do you capture the ability of a vocabulary that with was really
designed for clinical, in the area where you have an overlap, and to
take West Nile one step further, talking about the veterinarian
labs, looking very carefully, you monitor the outbreak by looking at
what is going on with horses and birds, which are all done by the vet
labs. So do you have some recommendations or thoughts or areas where
additional standards need to be developed in order to aid the exchange
of information that's very crucial in managing outbreaks that cross the
human and the rest of the animal or even other living organisms, that
cross that barrier where obviously you have to coordinate with other
agencies?

**[\>\>]{.underline}**

So, absolutely. First of all, in terms of SNOMED codes, as you might
expect, are largely related to human characteristics and specimens. So
the uniformity in that regard is not broad and needs additional work and
recommendation. So if you want to follow-up on our suggestion that this
activity be broadened beyond human diseases, that definitely has to take
place.

**[\>\> John Lumpkin:]{.underline}**

And let me just follow-up on that, give an example. Public health
laboratories are the ones that do rabies tests?

**[\>\>]{.underline}**

Correct.

**[\>\> John Lumpkin:]{.underline}**

So that\'s a test generally that is going to be done on a animal?

**[\>\>]{.underline}**

Correct, again.

**[\>\> John Lumpkin:]{.underline}**

Okay. So that is another example where the boundaries are blurred.

**[\>\>]{.underline}**

And water. And air. Soil. It just goes on and on.

**[\>\> John Loonsk:]{.underline}**

Now, do I think there has been an effort to do the LRN reagents in
LOINC, to get the LOINC codes for LRN reagents, is that correct?

**[\>\>]{.underline}**

Yes.

**[\>\>]{.underline}**

Yes.

**[\>\> John Loonsk:]{.underline}**

And that effort, in that scope, is ongoing, is that correct?

**[\>\>]{.underline}**

Right. I think there are ongoing efforts. There\'s some lag there, as we
request new LOINC codes. So there\'s work being done in that area, but
there definitely could be more.

**[\>\>]{.underline}**

That discussion could go on further. We could get into the issue
of, should we talk about or would we want a system like LOINC to be
hierarchical as opposed to just a random number generated. I know it\'s
not totally random, but it\'s not hierarchal. But that might be another
suggestion to look at in terms of terminology or uniform terminology.

**[\>\> John Loonsk:]{.underline}**

Yeah, it\'s \-- I\'m sorry. I was going to say it\'s a little striking
to have the first panel this morning and talk about the number of
outbreak management systems that can handle a lab test at all and think
about some of the esoteria. And I know it's a complicated issue, but we
seem to have some really basic infrastructural capacities we have to
broach. And what I\'m hearing is that the labs can, in
fact, substantially create standard, or communicate standard result
messages, although it might not always come from the LIMS system that\'s
in most common use in the lab. Is that fair to say?

**[\>\>]{.underline}**

I would say we\'re not there completely yet, but we\'re very close. So
all of those processes are within months of coming together, I would
say.

And one other point in that is the PHLIP project is also giving us the
ability to create an example of how we would share the accepted LOINC or
SNOMED in format as well, meaning the community portal will have it
posted as to which LOINC and SNOMED we would like to have the community
use. All they would have to do then is visit the site and see the number
and incorporate it into their database.

**[\>\> John Loonsk:]{.underline}**

I\'m sorry.

**[\>\>]{.underline}**

I think we need to say that we\'re there for the LRN assays. We\'re
close to being there for influenza. But there\'s still a bulk of the
work that, is it fair to say, Steve, that there\'s (inaudible) work that
needs to be done for the other nationally notifiable diseases.

**[\>\>]{.underline}**

And there are other issues to look at such as this one on our page of
second opinions and recommendations, this issue of a national database
for identification of the laboratory with a number, call it an OID.
It\'s an essential national function. Fortunately now that\'s being
looked at and taken on by the CDC. But that not only needs to extend for
laboratories, but it also needs to be extended to providers. There has
to be a site or a place where we can go and pick a number, pull a
number, and that is going to be now, and as changes occur, up-to-date
for where that specimen originated, where the specimen was collected,
and where the test was performed.

**[\>\> John Loonsk:]{.underline}**

This may be a question that is better asked of the epi panel, but
you\'re here. So in talking about \--

**[\>\> John Lumpkin:]{.underline}**

We have one panel member who made the mistake of not leaving.

**[\>\>]{.underline}**

They\'re all here.

**[\>\> John Loonsk:]{.underline}**

Obviously, public health labs play a critical role in so many public
health emergencies and outbreaks. But clinical labs play an important
role to. That was eluded to. Could you talk a little more about some of
the more significant outbreaks that have occurred and the role that
clinical labs played and where we stand in terms of working with
clinical labs so that the results can be leveraged for public health
purposes? It was touched on earlier.

**[\>\>]{.underline}**

I\'ll start. And I would say it falls under the category of perceptions
and realities as well. First of all, there\'s a big conception or
misconception that it\'s very difficult to send electronic laboratory
data across state lines. And the fact is that, many of our very large
commercial laboratories process up to 10 million laboratory tests a day,
and report those results across state lines every day. So those are also
identified. They have a patient name on them. So this is really not the
issue. It is happening all the time. And I don\'t know who else would
like to follow-up on that point. So the issue then becomes how can we
integrate with those laboratories when, as Norm pointed out, there is no
one place for them to send the data, they\'re reportables, so the public
health labs and state epidemiologist can go get it. We\'re asking them
to funnel and separate that data out and send it to disparate sites
across the country.

**[\>\>]{.underline}**

So, Steve, what you\'re saying is that if there was a central place, it
wouldn\'t matter where it came from, as long as it was coded the same
way and knew where it had to go. So, for example, using multi-state, not
an outbreak, just every day as you\'re saying, it could actually, the
message could be routed to where it was reportable? I\'m thinking of the
situation, John, you may have a patient who resides in Indiana but gets
treatment in Chicago. Where is that test result reported? Or if the test
is actually, if the specimen is taken in Indiana but is shipped to
Missouri, because that\'s where the clinical lab is, where does that
report go?

**[\>\> John Lumpkin:]{.underline}**

But it sounds like you\'re describing a clearinghouse function, which is
done in billing all the time.

**[\>\>]{.underline}**

That\'s right. That\'s exactly right.

**[\>\>]{.underline}**

But there\'s a, there needs to be a great deal of additional
growth, understanding, and acceptance of that concept as relates to
public health in the country.

**[\>\>]{.underline}**

I think, I just want to add, there are many examples of large food-borne
outbreaks and national outbreaks that have been detected with PulseNet.
But that\'s not because the clinical labs reported that they had
something, brather, because the way the system is set up that I tried to
describe, those isolates that they get of E. Coli or shigella or
whatever, and that\'s all they know and that's all they need to know,
from the patient standpoint. But it\'s the state laboratory then doing
additional testing using pulse field or something of that nature. So
that despite the fact we don\'t have all those connections yet
electronically, it can happen. I think it would be improved. For
example, in our state, we have a state rule that requires all our
clinical laboratories to send these isolates to the state laboratory. It
would be helpful to have that interconnection, that data connection, so
that we would know, on the reportable disease side, are all of the
isolates they report actually being sent, and you know, there would be
that audit function as well. It would improve the system. But we can
detect outbreaks now without having that connection. But, and that\'s
because the data is really coming from the state lab in terms of whether
an outbreak or whether a cluster has been detected. That doesn\'t mean
we shouldn't go and improve that by having data connections as well.
I\'m not trying to imply that.

**[\>\>]{.underline}**

Can I ask a question either for this panel, or anyone who wants to
comment? We talked about the need, one of the recommendations is the
implementation of standards that exist, certainly gaps in the
standards, but implementing standards that exist. What are some of the
barriers implementing standards that exist? Or the challenges, as Mike
would say?

**[\>\>]{.underline}**

As I mentioned, certainly many of the laboratories don\'t have LIMS
systems and that's a big challenge. They don\'t have the resources to
put that in place. When you\'re looking at the public health laboratory
requirements they\'re different in many respects from the clinical
laboratory requirements. That\'s also a challenge. There are many. I\'ll
defer to other colleagues.

**[\>\>]{.underline}**

I believe one of the subgroups working on this issue has identified the
minimum data set as one of the key objectives or current
challenges, meaning what is the minimum data sent that we want collected
on every hospital admission or on every laboratory? And one of the
challenges we\'re facing is exactly that as it relates to the individual
and their address. Sometimes it\'s required. Sometimes it\'s not
required. So the ability to go back and get the patient address is a
significant issue, because requirements are not uniform for that
particular activity, for that particular element of the information set.
And in addition, the actual process in which the requirements are
described across the country also vary. And another issue that needs to
be looked at, I think, again, there\'s progress being made. But
again, there\'s significant variability across the country. I\'ll leave
it at that for now.

**[\>\>]{.underline}**

I think the one thing I would add is probably more of a follow-on to
Norman\'s comments, is that resources really seem to be an issue. It\'s
not just whether or not a state or local lab has their own LIMS in place
already, or not, if they do, oftentimes there\'s enough variability in
the standards, enough, even just using HL7 as an example, there\'s
enough versions of HL7 being used, and they don\'t have the resources to
move towards a common standard. If a common standard were
identified, they don\'t necessarily have the resources to move towards
it.

**[\>\>]{.underline}**

So let me push that point a little bit. Going back to the chart that you
showed at the end with the multiple systems, to get to the point where
we have identified, even if we had the resources, who should determine
who has to change? Assuming that there is a mutually agreed upon
standard, who determines which one that is?

**[\>\>]{.underline}**

Right. I think that for several of those networks HHS is the over
arching body for, and so I feel like HHS should play a role there.

**[\>\> Tim Morris:]{.underline}**

This is Tim Morris. I don\'t know if this one is working, but my
background is laboratory. Certainly I\'ve been involved in outbreak.
That\'s why was on the other panel. But I've worked with Steve Hinrichs
on the steering committee for the PHLIP group, and I\'m also the IT, the
chair for the IT group of the ICLN or Integrated Consortium of
Laboratory Networks. And speaking specifically to that point in the
chart that you were holding up, that\'s a set of data that we collected
through that ICLN subgroup. We have members from each one of the federal
agency networks on that group, and that little bit of data you see there
took quite a long time to gather. And when you get to the reasons why
we\'re not integrated, I think one is like the LRN, like the ELRN that
is coming from the EPA, they do have a transport mechanism called the
CDX that they are very invested in. The FDA is very invested in the
eLEXNEXT for the FERN. The NAHLN has capacity that's similar to what the
LRN is doing. The key is that they all have existing capacity to some
degree and they have investment in it. And it will require change. I
think, Steve, your point is right on target, because as we\'ve analyzed
this on the ICLN, and we\'re doing an exercise in the middle of
April, because a lot of the people didn\'t want to recognize some of
these lab to lab interactions and other things that those are the state
labs know exist that, as Emory said and I think Steve said and maybe
Norm, that you have multiple of these interfaces for these separate
networks. That same public health lab is doing all of that work. And
so, I asked DHS, this is sponsored by DHS as a, in the capacity of the
national coordination for a national event. However, it\'s unclear where
the authority would lie across all of these to, if a recommendation was
made for integration amongst these groups, which we\'re going to try to
get the output from that, from my group in the next couple of months, as
a recommendation paper on what needs to be done. Now, I told DHS I would
turn that over. But nothing will happen unless there\'s some authority
vested through those two to make something happen. And I don\'t know
where that\'s going to come from.

**[\>\> John Loonsk:]{.underline}**

So \-- I\'m sorry. Maybe you can answer this question for me. The Health
Information Technology Standards Panel has identified an HL7 version 2.5
lab result message, which is going to be used for clinical care systems,
it's going to be certified that EHRs can accept it. It is, I
believe, was done in conjunction with the biosurveillance work of the
Health Information Technology Standards Panel. That standard is going to
be, was accepted by Secretary Leavitt, and he has indicated that he is
going to recognize it in December of 2007. At which point, it would be
essentially required for federal systems and federal contracts to use
that. So I mean, perhaps there\'s leverage in that. Can you talk to us
about the applicability of that message as it exists now in this
context?

**[\>\>]{.underline}**

Um, certainly. That message, although for some of the environmental work
using a OUL message instead of and ORU, if you get to specific HL7
language, but it\'s to the particular points that were made before, when
you're testing air and animals and things that aren't patients. It\'s a
separate structure. So I think companion-wise, most of it is the same.
But I think there\'s some additional that we would need to do to cover
all our bases there. Certainly CDC, the message that we have for use in
the LRN is an OUL message because we know we have that need, it can do
human or, the patient information is optional. So you can do things like
test air or chairs or what have you, or animals. So I think that
there\'s a little bit more that we might want to do there with an
additional specification or look to that, because the ORU is generally
the one that's been used in clinical care.

**[\>\> John Lumpkin:]{.underline}**

That was a qualified maybe.

**[\>\>]{.underline}**

I think that certainly for the clinical testing we do on humans, you
can, we shoehorned in animals and other things into that before. The
recommended way to do environmental samples, animals, other things that
aren\'t patients is with the OUL result.

**[\>\>]{.underline}**

I want to jump in and add a point to that. And that is, as Norm pointed
out, we have a number of clinical partners in our state and they use in
many cases more sophisticated LIMS systems than public health
laboratories have. In most cases that\'s a commercial vendor which has
had LIMS and HL7 exchange technology for sometime. Unfortunately
they\'re not ready and will not be able to implement 2.5, and therefore
we, at the state level, if we say you must go to 2.5 we will lose our
ability to get data from them. Now, there's alternatives around and that
and we\'re working towards interpreters, translators, et cetera, but
nonetheless we want to make sure that by implementing a higher standard,
we don\'t cut off the data sources we already have.

**[\>\>]{.underline}**

Is there, sort of playing off on the earlier part of your, not the,
whatever the specific language was, but in terms of what we heard from
Mike Miller is that there's a great complexity of laboratories across
the CDC, what I didn't hear in particular was is there a common system
for transporting data? So in other words, is there a common LIMS system
at CDC, and does it have the ability \-- I know the answer is that
currently we don\'t have the ability to transmit the data back to the
requester, being the state. So we can focus in I think at some level on
the triad of state to state and state to CDC and CDC to state.

**[\>\> Mike Miller:]{.underline}**

You\'re familiar with the STARLIMS approach and it\'s not there yet. It
should be one of those systems that would allow that communication
throughout CDC and then to our partners also. I want to say one other
thing if I may, you mentioned animal, I\'m fortunate to be the associate
director for science for the newest of the centers, The National Center
for Zoonotic, Vector-borne and Enteric Diseases, where we are really
looking at the ecologies of infectious disease, where infectious disease
in humans actually interfaces with many of nature's communities. And
over 75 percent of new emerging infectious diseases are zoonotic in
nature. And we\'re going to find these organisms in animals and in
nature and in people and may in fact be found first by our veterinary
colleagues. So whatever we set up needs to be set so that we can
accommodate this approach to a different look at infectious disease and
the interventions of those infectious diseases.

**[\>\> John Lumpkin:]{.underline}**

So that means integrating with the Department of Veterans Affairs.

**[\>\>]{.underline}**

Veterans?

**[\>\> John Lumpkin:]{.underline}**

Yeah I apologize.

**[\>\>]{.underline}**

Being one.

**[\>\> John Lumpkin:]{.underline}**

Scott, you had a follow-up?

**[\>\> Scott Becker:]{.underline}**

So what is the plan really in terms of time frame then for the LIMS
solution at CDC. I actually think that the AHIC, we could actually make
a recommendation about better utilization of existing systems.

**[\>\>]{.underline}**

Yeah, I\'m not the one to answer that. I really don\'t think that the
folks that could answer this specific question I think about the
STARLIMS implementation at CCID are here. However, I think the main
thing is, there\'s 85, you can see from Mike\'s slides that there are
many laboratories, all differing levels of complexity, and I think we
all know the difficulties in implementing a LIMS over a large number of
labs. Some of the issues you talk about are, the main one is the ability
to accept an electronic order. And I think that is the bidirectional
communication that we\'re going to work through. Now I\'ve heard that it
would be this year. But I think they\'re scoping that effort now. Some
of it is related to funding. So that capacity at CDC will be there
hopefully in the next year or so to, you know, respond to an order with
an electronic result.

**[\>\>]{.underline}**

And I think it\'s important to point out that STARLIMS is only going
into CCID labs and so that only encompasses, a significant portion, but
only a portion of the labs at the CDC. NCEH has their own, has a variety
of LIMS in place and has a system in place to tie all of those LIMS
together. And so we\'re doing some work at CDC with a product called
STARS that would tie together all of those LIMS and allow them to share
results and track specimens across the enterprise.

**[\>\>]{.underline}**

And then report back?

**[\>\>]{.underline}**

And then report back.

**[\>\> John Lumpkin:]{.underline}**

A very technical question, but how many states participate in LRN and
how many participate in PulseNet?

**[\>\>]{.underline}**

All.

**[\>\>]{.underline}**

All.

**[\>\> John Lumpkin:]{.underline}**

They all participate. Okay. And then the other question I had, which is
looking at the linkage and the bi-directional, one of the major
political fallouts that we had in Illinois from West Nile was after we
announced the first couple of cases, and patients and physicians found
out that they had West Nile through the newspapers rather than through
other channels. The system, as you described, goes from clinical care
setting to the laboratory, partner laboratory. It comes back, you
know, the treatment of West Nile is primarily symptomatic, so there was
no impact upon patient care. Nor would there be impact on patient care
related to subspecies of salmonella. So the question becomes at what
point do we develop more interaction between the clinical care system
and the public health laboratories so that there aren\'t those kind of
nasty surprises?

**[\>\>]{.underline}**

I would like to start on that one. Because it raises a very important
issues and it\'s also included in our recommendations. We would like
everybody to recognize, number one, that the best laboratory test when
utilized in a situation where the prevalence of disease is very low, the
positive predictive value of that test result is very, very low. So in
the situation of West Nile, where there never was a case, and the test
is positive, the predictive value is very low, in fact it\'s probably a
false positive. So what we need, in addition to better tests, is we need
better data analyses systems and research into how to integrate and
determine when are rare event statistically significant. And we would
argue when, for example, in Nebraska, if we found only one salmonella
Tennessee it may well have been a false positive or a false
characterization with no clinical significance. But somehow, this
integrated system has to be able to determine when have we broken
through a threshold when it must have an investigation?

Now to get back to your specific question, we don\'t want to leave the
epidemiologist out of this process, because as I said, if you are
detecting events with low prevalence, the likelihood is, it is false
positive. So if you only follow-up in investigation or say that a lab
test is truth without testing it. you may well have created a problem.
So the data in some way has to be seen and/or screened by
epidemiologists who are very knowledgeable in the whole process before
it gets disseminated broadly and widely, to determine it\'s overall
significance. I\'m not saying I know how to do that. What we\'re saying
is it\'s a very important issue and needs to be examined.

**[\>\>]{.underline}**

I think there's another aspect to that too. As we set up these networks
that involve sentinel laboratories and reference laboratories, if the
data only goes one way, that they send things to us and we send things
on to the CDC, in terms of a clinical laboratory, that's okay. But I
think really to make the networks work, they have to get something back,
and I think in order to prevent that problem that you had, where they
find out, they read it in the newspaper or something, they ought to be
engaged in these networks, in this data exchange, to the extent that
they always know what is happening as well. And they make their
contribution to that, as a sentinel laboratory, but they need to look,
be able to see, at least their administrators and such, need to see the
big picture as well, because they have to be engaged. You can't just say
you have a network, and you sign up the laboratories. Unless they really
are engaged in an active way, it's not going to work very well.

There's a, right now I think we're headed in the right direction,
getting standardization and such, but we're still very fragmented. And I
think part of that, maybe a lot of that fragmentation is driven by the
fact that every one of us, where it's state, local, federal, private,
public, whatever, we all have needs and we have to get those needs fixed
now, and so we take whatever serves our purpose, and they're not
interconnected. So how do we set that, and that has to go on, because
people have to address their current needs as soon as they can with the
resources that are available to them, but somehow we have to be able to
sit back, look at the big picture, and make sure that all those pieces
start being put together in a way that at some point in the future it
will all work together. I just don't know how to do that, but if we
continue to just put together fragments, that's what it's gonna be.

**[\>\>]{.underline}**

The second part of that is defining an iterative process of getting from
where we are with successful systems, in some ways, to the overall more
global interoperability that we need through incremental change in our
systems, because certainly with the funding streams available to public
health, you know, overnight change in the systems is not going to happen
unless there's a big infusion of money. So, to John's question, to me, I
just, clarity on that one with the domain of those directives from HHS
relative to the EPA and others that work in this arena. Certainly I
would welcome and would like to take to these committees some of these
mandates that we could drive through, and certainly those that are under
the HHS umbrella, but how does that affect some of the other agencies
that would not be, federal agencies.

**[\>\> John Loonsk:]{.underline}**

It is a federal government-wide executive order, so it\'s not specific
to HSS. Historically, the context for it is in healthcare. And so this
is where it gets complicated. Because they may not see that as part of
the domain, and how closely is that tied to clinical care per se, and
the provision thereof is the challenge.

**[\>\>]{.underline}**

And I think for our purposes, and certainly my own purposes on the ICLN
committee, is, you know, for the committee, maybe some investigation or
some guidance for me or maybe we can provide some back to you relative
to these efforts so that we can broaden that and have language that
might help reinforce that with the other agencies somehow. I think that
would be very welcomed.

**[\>\> John Lumpkin:]{.underline}**

I think that all of the testifiers, the likelihood that we\'ll get it
right increases when you provide us with language. So that would be
appreciated.

**[\>\>]{.underline}**

Okay.

**[\>\> John Lumpkin:]{.underline}**

At this point, we\'ve sort of gone over our timeframe. We\'ve actually
gone right through our break. I personal little feel like we ought to
take a break right now. So we're going to take a five minute break and
before we do, I would like to thank the panelists both this morning and
this afternoon. It\'s very excellent insight into the arena that we\'re
trying to develop recommendations for. So thank you very much.

\[break\]

**[\>\> John Lumpkin:]{.underline}**

Okay, we\'re ready to get started. Is there something we need to do to
get started?

**[\>\> Judy Sparrow:]{.underline}**

I think we\'re just ready to go. Dr. Lumpkin.

**[\>\> John Lumpkin:]{.underline}**

Thank you. We have scheduled some time for us, different that the last
time where we were done and then everybody jumped on an airplane, to
have an opportunity to discuss what we've heard and identify what we
might want to hear in our next set of hearings, which will be a
follow-up. Right now, we\'re looking for, at April. The next scheduled
time we have was April \--

**[\>\>]{.underline}**

I think they cancelled that meeting, and your next meeting is May 11th

**[\>\> John Lumpkin:]{.underline}**

That\'s what I meant. May 11th

**[\>\>]{.underline}**

Did we not fix that here?

**[\>\> John Lumpkin:]{.underline}**

No, I didn\'t look at it. I was going on memory. This is the end of
March, isn\'t it?

**[\>\>]{.underline}**

Yes.

**[\>\> John Lumpkin:]{.underline}**

We\'ll be going for May 11th for another hearing, for a number of
reasons

**[\>\>]{.underline}**

The next hearing, we decided to push the rest of the response management
testimony to June, because May 11th \--

**[\>\> John Lumpkin:]{.underline}**

Too soon. I knew that \--

**[\>\>]{.underline}**

It wasn't too soon, but we had other obstacles in the way. That\'s the
Brussel\'s conference? That was the obstacle. So in the interim, we had
talked about doing the ad hoc workgroups and moving adverse event
forward in parallel with digesting and moving this testimony forward
towards recommendations.

**[\>\> John Lumpkin:]{.underline}**

That\'s exactly what I meant to say. Okay. So if I can clarify, we\'re
going to meet on the 11th of May to move our recommendations forward.
And then we\'re going to have some extended meeting on June, in June.

**[\>\>]{.underline}**

June 15th.

**[\>\> John Lumpkin:]{.underline}**

June 15th. Okay. So I think that right now what we would like to do
is, you know, if there\'s any feedback or thoughts based upon the
hearing, if there are areas where we would like to make sure that we
touch base on in June, when we do that hearing, areas that we would like
to, or you think that there are promising areas for recommendations, I
think that\'s all open for discussion.

**[\>\>]{.underline}**

I thought that the survey that we heard about this morning was, well, it
was useful at giving a sense about where in fact health IT is with
respect to the health departments. Although I must say that I didn\'t
understand, as I said to you offline, I was actually down in the parking
garage when the data was actually being presented, but from the
slides, I think it\'s useful in giving us a sense of the state of
things. And I think for the AHIC it would be useful to have that kind of
base, you know, to build recommendations on that. And I think the same
kind of thing would be good for the public health labs as well, sort of
knowing what the state of health IT readiness is of the ability to
interconnect to the degree to which they\'re getting information
electronically from hospitals or whatever, because I certainly come away
with a sense of, number one, the tremendous importance of both
testimonies, this morning and this afternoon. But secondly, that we\'re
very far from where we need to be. And I think, you
know, recommendations to push that forward. But I think it needs to be
based on something that, quantitatively if you will, gives you the state
of thing. Tim may have that at his fingertips or someone else, but I
don\'t.

**[\>\> John Lumpkin:]{.underline}**

Now the data we saw this morning was 05 data, wasn\'t it?

**[\>\>]{.underline}**

Most was \'05 data. The data at the very end was a survey that is
actually still in the field that is closing tomorrow.

**[\>\> Scott Becker:]{.underline}**

\-- data was from a few months ago, last month\'s right? And we have it
on our schedule to do a health IT survey. And I can go back and see how
quickly we can move that up.

**[\>\>]{.underline}**

Actually, Scott, that\'s good to hear, because Angela and I were just
talking in our cooperative agreements next year to have that proposed.

**[\>\> Scott Becker:]{.underline}**

We would be happy to have your support.

**[\>\>]{.underline}**

We would be happy to collaborate.

**[\>\> John Lumpkin:]{.underline}**

What I heard is that by the time we make recommendations we should have
data from CSTE and the labs, maybe. And that we\'re very likely, by this
time next year, hopefully, to have data from both NACCHO and ASTHO and
the labs working in coordination.

**[\>\>]{.underline}**

And then even probably by our May meeting Angela and I can present some
preliminary results from the survey about public health involvement with
RHIOs.

**[\>\> John Lumpkin:]{.underline}**

Great.

**[\>\> John Loonsk:]{.underline}**

Having that data would be helpful. One of the aspects of, it was
pronounced to me here and was pronounced previously, is that a lot of
this, and a lot of these issues are not just about capacity, but
they\'re also about providing capabilities to others. If you think about
labs, it\'s partly about how the labs can provide data so that the epis
can use them, how the epis can provide data so that another health
department can use them, how another organization can take advantage of
them. And when we hear that the obstacles are not having the
standards, certainly there are details there that are complex and
obstacles. But the issues are not that the standards don\'t exist
principally. The issue is that it\'s a question of implementing those
capabilities when that\'s on a priority list that is, where those
priorities are sometimes, for doing those things to others, for
others, are sometimes lower on the list than the immediate activities
inside the lab, we have a basic conflict.

I heard a call for help in that regard. I heard the fact
that, indeed, there was uncertainty as to how to move forward in terms
of trying to assure that some of those needs are met across
organizations, certainly there\'s plenty of infrastructure issues
internally that need to be addressed in many public health agencies as
well. But I think we should, as a working group, think about what we can
do that\'s most constructive that could help advance it. And we, the
scope of the AHIC is principally oriented to clinical care, but we do
have a number of different agencies that are at the table. And I think
that we should be careful to try to craft some recommendations that can
actually show the importance of this and try to put into place a way of
the classic issues are getting people, get on people\'s priorities list
and then having a process that can demonstrate that they\'ve
accomplished it.

**[\>\>]{.underline}**

I guess the point I was making was what John is saying, but adding to
that, something a little different than saying these are the
recommendations, but making clear where we currently stand. And the fact
that, well, this has been discussed for some time, but the progress has
been slow. And I think knowing that, in a sense, the group, the
enterprise to use that word we\'re dealing with, is actually a
relatively finite one. It\'s big, but it\'s finite. It\'s not like
we\'re dealing with electronic health records for the United States.
We\'re dealing with something I think we can draw a circle around and
say, this is what we\'re after. This is the current state. And then
recommendations that perhaps state in terms of standards, I\'m not sure
the best way to state these, but something that emphasizes as somebody
said the really critical importance of this to health. I mean these are
the kind of things we\'re dealing with here that directly relate to
health.

**[\>\> John Loonsk:]{.underline}**

I agree. We have to try to boil it down to some very basic indicators.
It gets complicated very fast. Lab results, being able to share
electronic lab results, being able to share and accept. Possible cases
for me, it\'s a gross one, but there\'s a lot of complexity under there.
Being able to share possible cases between jurisdictions, contract
tracing is a fundamental capability that is demonstrated to be useful in
managing outbreaks in public health settings. These as, as kind of
surrogates for the general capacity, I agree with you
completely, Ed, looking at those things, seeing the degree of
penetration of them right now, which I think is disturbing, just from
the standpoint of supporting the public's health, and then carrying
forth from there. And then so, recognizing that status, what are the
concrete things that we can do and what can we, how do we do them?

**[\>\> Theresa Cullen:]{.underline}**

This is Terry. The one thing I would warn, even though we don\'t want to
take on the state of electronic health records around the United States,
is that we also don\'t want to miss the opportunity to ensure that there
aren\'t some appropriate recommendations, as AHIC and ONC move ahead
with recommendations and certifying criteria in electronic health
records that ultimately may benefit this public health process.

**[\>\> John Lumpkin:]{.underline}**

But I did want to go back to those three items that John listed, because
all three of those have significant preparedness implications.

**[\>\>]{.underline}**

There\'s a model for this that can be tested, and it can be tested on an
annual basis. And that\'s something that is variably at the forefront of
our consciousness which is pandemic flu. There is a model for that
annually, which is seasonal flu. We were fortunate last year to not have
a bad flu season. We all hope we\'re fortunate again this year.
Nonetheless, all of the systems we talked about, both epidemiological
and laboratory systems, can in fact be tested with regard to all of
those issues, using that as a specific measure, not just in a tabletop
exercise, but literally in the event, whether we have a heavy or a light
flu season, the ability to transfer those records, whether it\'s 1 case
or 100,000 cases from New York to New Jersey, or from Missouri to
Kansas, with a standardized message can literately be tested in the
event, and it's something that can be measured annually, if we set it up
the right way in terms of how well we\'re proceeding including contact
tracing and including \-- it is something that at least for discussion's
sake, actually making that a model of how we measure our progress by
doing something that we all think is necessary and establishing the
criteria for success.

[**\>\> John Lumpkin:**]{.underline}

I think we have to be careful about that. Unless things have changed
since, you know, the couple years I left the state health
department, influenza is not a reportable disease. There\'s sentinel
practices that report. Second of all, we don\'t do contact tracing on
influenza. The resources, we do contact tracing, or states do contact
tracing, on a number of diseases on a regular basis. So I would be very
careful. The third reason I have concerns about influenza is that the
public health system has, and begins to get a representation of crying
wolf. We can only ride the pandemic flu issue so long. And at some point
there will be a numbing response from both the public and other sectors.
I think that there\'s enough here, tuberculosis, the case we saw this
morning is a classic example. Every state is engaged in that. There are
50 cases, 50, 60 cases in Illinois a year. Those are increases. That
involves all the things we want to test. I urge that we think about
something that might be a little but more enduring if we use that as a
sentinel monitor.

**[\>\>]{.underline}**

I would tend to agree with that. We can use something, there\'s TB,
there's vaccine preventable diseases like pertussis, which unfortunately
we have seen a resurgence of. I tend to think that we would be able \--
I think we\'re getting flu-fatigued. I agree with that. I think that for
the long-term, we probably are better off going with something where we
know that local and state health departments do this all the time every
day. And unfortunately, TB is not going away and reemerging and becoming
resistant. So I think that would be a very important example to try to
ascertain what is going on.

**[\>\> John Loonsk:]{.underline}**

Clearly another way of slicing it would be by the LRN category A agents,
or category A and category B. There are different ways to do it.

**[\>\> John Lumpkin:]{.underline}**

Another \-- Scott?

[**\>\> Scott Becker**:]{.underline}

Another point, something that Tim said towards the end really I thought
about, he said, you know, even if there was, we could fix part of this
if there was a lot of money. Well, that\'s true and not true. Because I
think we haven\'t heard enough about the workforce issues for public
health informatics. I think that is something that would be good to get
a little but more on and \--

**[\>\>]{.underline}**

Yeah, I didn\'t present that data but we do have some of that data. And
we are actually ASTHO and NACCHO are working with the Public Health Data
Standards Consortium to develop workforce training and try to do some
sort of an assessment of workforce needs.

**[\>\>]{.underline}**

That would be useful to see at some point.

**[\>\>]{.underline}**

We\'re a little busy.

**[\>\>]{.underline}**

Your point gets back to Ed Sondik's point, or at least potentially back
to Ed's point, which is how much money is in the system right now that
is not being optimally spent because of duplication, because of
redundancy, because of non-intersecting systems. What\'s the return on
investment, even short term, in fixing some of those redundancy and
non-intersecting problems by harmonization that ends up saving us a lot
of money that can then be reinvested? I mean, do we need to invest the
whole amount up front or can there be a cascading effect by a relatively
modest investment saves enough money that then \--

**[\>\>]{.underline}**

A principal example of that is frankly the work that we did on the
development of the requirements for a LIMS system, because every state
was trying to figure this out on their own, and we sort of collected all
and said this is what it is, here is the recipe book. They're then not
having to spend their own or federal dollars to do that, and that short
circuited I think a lot of wasted effort, what would have been wasted
effort. I think there are examples, yeah, like that.

**[\>\> John Lumpkin:]{.underline}**

And we could compare that to the immunization registry system, which is,
was not developed that way.

**[\>\>]{.underline}**

Right.

**[\>\>]{.underline}**

One of the things I heard a lot of people asking for, especially in the
morning session, was that the progress continue and be accelerated with
the OMS system that's being developed, including the links to the
surveillance system. And I also heard the message that that process had
been slowed down for a variety of reasons. It would seem reasonable,
from our standpoint advising to AHIC, as part of HHS that indeed that
system is important and that either through the current process or a
different process we need to get to a workable product.

**[\>\>]{.underline}**

I would also follow up that I was not completely satisfied with the
response that I got about the enterprise-wide LIMS system. I think it
would be a good as a follow-up or an action item to really learn about
what the plan really is. I think if we had asked the question
differently, or to this last panel, we probably would have heard from,
at least from the state side, continuing need for that.

**[\>\> John Lumpkin:]{.underline}**

Well, should we just pick on CDC now? Because you know, what we heard is
that there is networks related to environmental measurements. There\'s
overlap there between what EPA does and then there\'s ag issues. So I
think that we could broaden that out and not pick on our good friends at
the CDC.

**[\>\>]{.underline}**

Not exclusively.

**[\>\> John Lumpkin:]{.underline}**

Exclusively.

**[\>\>]{.underline}**

I agree.

**[\>\> John Lumpkin:]{.underline}**

So I\'m hearing kind of three buckets of recommendations, I think. Kind
of like my four dimensions. Anyway, there are those recommendations that
will be specifically related to standards and harmonization. There are
those buckets that will relate to \--

**[\>\> John Loonsk:]{.underline}**

Can I offer an amendment to that?

**[\>\> John Lumpkin:]{.underline}**

Yes.

**[\>\> John Loonsk:]{.underline}**

I think it\'s more a question of implementation of standards than it is
of standards and harmonization. They\'re not totally separable, but what
I heard was that the standards are not the major obstacle, that the
implementation of them is.

**[\>\>]{.underline}**

Is there a harmonization aspect to that, though?

**[\>\> John Loonsk:]{.underline}**

There can be. I\'m not dismissing it completely, out of hand. I think
that was one of the points that I heard this morning, pretty loudly, was
that, you know, some of the standards do exist, or a lot of the
standards do exist, but it\'s a question of getting them implemented
into systems and assuring that they are there.

**[\>\> John Lumpkin:]{.underline}**

So we have the melody right, we need to make sure the harmony is all the
way there.

**[\>\>]{.underline}**

You\'re on a roll today.

**[\>\> John Lumpkin:]{.underline}**

The second bucket has to do with capacity. And I don\'t know exactly how
to describe it. But I think what I\'ll start off, put on the label for
that bucket is laboratory reporting, contact tracing, and what was the
third one?

**[\>\> John Loonsk:]{.underline}**

I said possible, the exchange of possible \--

**[\>\>]{.underline}**

Exchange of possible cases as sort of sentinel kind of capacity that we
believe the system ought to have. And it may be due to things in the
other buckets, but that is something that we could look at. And the
third is we may want to place in that bucket the things like the cross
LIMS systems, sort of interagency coordination, which also had some
capacities of implications for intra-agency coordination. Those are sort
of three areas. Are there other areas that we may want to look at?

**[\>\> John Loonsk:]{.underline}**

Well I think this is, this underlines your last point, but I didn\'t
quite explicitly hear it said. But it was alluded to that the
information flows in an emergency are different. And at times, what we
have to target is the broad capacity for sharing those data, and
recognize that we may need, it may, you may not use it on a routine
basis, all the time. Clearly the thrust is to have the systems be
useable on a routine basis, and you\'re frequently using them. But I
heard a lot of need for data at many different levels and the needs to
be able to share those data pretty readily. I think the concept of
building an infrastructure that can sustain an emergency event, having
it in place, needs to be stated.

**[\>\>]{.underline}**

So four categories?

**[\>\> John Loonsk:]{.underline}**

I don\'t think it\'s a fourth category, but it goes to some of the
subtleties about information exchange wherein, you know, flu is not a
reportable disease. But indeed, in an emergency, there are needs for
situational awareness on influenza that are prominent at all levels of
public health. You can almost take any single disease, whether it's
reportable or not, and conceive of a situation in which you would need
to be able to share information about that, to carry out an emergency
response.

**[\>\>]{.underline}**

Where would the workforce information go? Would that be under the
capacity bucket?

**[\>\> John Lumpkin:]{.underline}**

We could. You know, we can try it there. I\'m just sort of getting some
broad areas and we can try to flush those out. But then, so the next
question, sort of roughly, those three buckets, and there could be four
or five and we may decide to split out workforce. Where do we need more
testimony?

**[\>\> Chip Kahn:]{.underline}**

Can I ask a question about workforce for a second?

**[\>\> John Lumpkin:]{.underline}**

Sure.

**[\>\> Chip Kahn:]{.underline}**

I don\'t \-- is that in our scope? I\'m not \-- I think it\'s an
important issue in terms of operationalizing the things we\'re talking
about. But I guess I\'m just wondering, other than a sentence that says
somebody needs to do something about this, which I think we could put
in, I\'m just a little concerned that that is outside of the scope of
the AHIC\'s activity, because it actually is only a piece of a larger
set of manpower issues, and I, and I just don\'t, other than commenting
on it, I don\'t know what else we can do, really.

**[\>\> John Loonsk:]{.underline}**

John, you asked about other areas for potential testimony. I think one
of the things that we haven\'t quite delved into completely is the
possible role, what the roles of health information exchange are in
supporting public health in this context? So a lot of the information
exchanges that we heard about were classic public health information
exchanges. And as the nation builds this tier of health exchange
networks that are connected to provider organizations, connected to
consumers, and connected to public health labs, and connected to public
health departments, what is, what are the possible roles there and is
there something we can leverage in regard to this? I think that would
bring it home even more directly to the AHIC\'s purview, indeed as well.
And so that\'s an area we may want to have at least more discussion.

**[\>\>]{.underline}**

I would just add on to that I thought it was interesting that folks
brought up the clearinghouse function and I think in the commercial lab
world, that\'s been thought about over the last couple years but nothing
has really been acted on. And the pharmacy community has come together
over the last five years and they do have a functional network
now, actually, more than one, but it\'s national in scope. And there
could be both from a commercial and public health side for labs a reason
to have some kind of clearinghouse function. And I think trying to
understand a little more about what that might look like and the
incentives for it to come together would be helpful.

**[\>\> Chip Kahn:]{.underline}**

What would be \-- there\'s a business case for \-- on the pharmacy side.

**[\>\>]{.underline}**

Right.

**[\>\> Chip Kahn:]{.underline}**

And I don\'t \--

**[\>\>]{.underline}**

Right.

**[\>\> Chip Kahn:]{.underline}**

And there\'s a policy case. But what is the business case on the lab
side?

**[\>\>]{.underline}**

That\'s a really good point.

**[\>\> John Lumpkin:]{.underline}**

Well, and I think there\'s any number, there\'s one thing, do we need
it? Then the second is, where would a business case exist? And my guess
is, I'm going to be where Chip is, is that there probably isn\'t an
extragovernmental business case. But that doesn\'t mean that it\'s not
doable.

**[\>\> Chip Kahn:]{.underline}**

Right. Then the question is who is going to pay for it?

**[\>\> John Lumpkin:]{.underline}**

That would then be the role of government.

**[\>\>]{.underline}**

Right.

**[\>\> John Lumpkin:]{.underline}**

That\'s why we\'re all so happy to pay our taxes.

**[\>\>]{.underline}**

I think if this is one of those issues where there is an inherent
governmental role, then I think it would be helpful for to us point that
out.

**[\>\> John Lumpkin:]{.underline}**

Uh-huh. Okay. Um, any other areas that we want to think about for our
June focus? I think we have a couple already on \--

**[\>\> Sunanda McGarvey:]{.underline}**

Countermeasures, countermeasure allocation, distribution, and
administration and, John, I think you had some additional ideas as well?

**[\>\> John Loonsk:]{.underline}**

Thank you, Shu, and when you remind me what those were \--

\[laughter\]

**[\>\> John Loonsk:]{.underline}**

\-- I\'ll be happy to share them.

**[\>\> John Lumpkin:]{.underline}**

I think we didn\'t get into \--

**[\>\> Sunanda McGarvey:]{.underline}**

We also had communications, I think. We need to determine what the
overlap is between the communications, that aspect of communications,
and what we've already covered in bidirectional communications in
previous testimony. Actually, we put recommendations together for
bidirectional communication, but we never really had testimony in that
area. And I think we heard some things today that furthered the need for
testimony in that area on unique identifiers being needed for
providers, for labs, and that sort of points to directory-types of
functions as well as data routing-types of functions and so on and so
forth. Is that what you had in mind, John?

**[\>\> John Lumpkin:]{.underline}**

I was with you all the way until we got to you used that one word that
no longer is in my vocabulary, unique identifier. And one of these days
I'll tell you about the time when I was heading up a hearing from the
NCVHS on the unique personal identifier. But we won\'t go back there.

**[\>\> John Loonsk:]{.underline}**

And just to be clear, what was being discussed was a unique provider
identifier.

**[\>\>]{.underline}**

Other than INCI, yes.

**[\>\> John Loonsk:]{.underline}**

But there needs, and the allusion to an OID is an area we don\'t want to
go \-- but \-- in terms of the depth and complexity. But
organizations, if you\'re going to share data electronically you need to
be able to identify those organizations so you can address it
appropriately. And that was the issue here. It was not about patients
and unique identifiers. It was being able to address data on a network
to organizations and know where the data came from.

**[\>\> John Lumpkin:]{.underline}**

Right.

**[\>\>]{.underline}**

The other comments I was going to make, this has been a pet of mine
since the beginning, is when we talk about bi-directional
communication, we have to kind of put off to the side the final link of
that communication back to the clinician. We\'re pouring data into a
black hole. We need to get the information back. And there\'s a number
of things that I know from my domain within emergency medicine that
we\'re working with that to be able to have not only communication with,
between providers, but with the public health, and also, ultimately, to
some kind of an incident command structure to be able to participate and
to work effectively in the truly public health emergency situation.

**[\>\> John Lumpkin:]{.underline}**

So we should put on the potential of revisiting bi-directional within
the context of what we've heard in this hearing and maybe getting some
testimony on that.

**[\>\> Kelly Cronin:]{.underline}**

Just a related point to give folks an update. Since we have four
Workgroups that are very interested in clinical decision support and
various aspects of it, two of them have explicit charges that deal with
CDS. We are trying to do sort of a planning framework that all these
Workgroups, including this Workgroup, would use and try to sort of
separate out the issues that are unique to public health or tha are
unique to personalized medicine or that are unique to quality
measurement and have a complementary effort going on within each
Workgroup. To the extent, Brian, that you would be involved in that
planning on a conceptual level or John, or John, we\'re going to try to
get something started in the next three weeks. I\'ll follow up.

**[\>\> John Lumpkin:]{.underline}**

And will we get support for that decision making? Okay.

**[\>\>]{.underline}**

A plan.

**[\>\> John Lumpkin:]{.underline}**

We have a plan. So that being the case, and we\'re approaching 3:30 and
it\'s like one of my promises to always finish the meeting early. Or
I\'m sorry, on time because what we have to do now is we have the
opportunity for public input. Judy thought I was going to forget.

**[\>\> Judy Sparrow:]{.underline}**

I did think you were going to forget. Jennifer, you can just see if
anybody out there want to make a comment?

**[\>\> Jennifer Macellaro:]{.underline}**

I just put the slide up. The number if you\'re just listening over the
Web and haven\'t called yet, just dial in, there\'s instructions to
press star 1, and if you're already dialed in you need to press star 1
to alert the operator. There\'s also an e-mail address if anyone wants
to write in comments after the meeting. I\'ll check back with you in
about a minute.

**[\>\> John Lumpkin:]{.underline}**

Where is that Jeopardy clock music?

**[\>\>]{.underline}**

On the business case side, Kelly mentioned government, you know, it\'s
all levels of government. It\'s not only the national, the federal
government, but because you know, clearly, there\'s a benefit to the
local and state public health from having faster, better, more accurate
reporting, being able to share information.

**[\>\> John Lumpkin:]{.underline}**

But doesn\'t that always mean that the feds should pay for that then?

\[laughter\]

**[\>\>]{.underline}**

That\'s just with your old hat on. You\'re supposed to be thinking more
innovatively than that. But it also gets at the Secretary\'s goal of
value-based health or value-based healthcare. So in the meeting in CDC a
couple days ago the idea of value-based public health came up. And in a
sense, this relates to that, because we want to think not just of what
we need put in place, but what is the benefit that we actually get from
that? In a sense, what is the marginal benefit, the gain in benefit,
that we get by having this kind of facility? We don\'t think in those
kinds of terms as much. You know, they\'re sort of there, but we don\'t
quantify it. Was that a minute?

**[\>\> Judy Sparrow:]{.underline}**

Yes, that was a minute. Jennifer, do we have anybody?

**[\>\> Jennifer Macellaro:]{.underline}**

There is no one dialing in today, no.

**[\>\> Judy Sparrow:]{.underline}**

Thank you. Okay. Thank you everybody.

**[\>\> John Lumpkin:]{.underline}**

Thank you and, with minutes to spare, we are adjourned.