[Federal Register Volume 72, Number 114 (Thursday, June 14, 2007)]
[Notices]
[Page 32850]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 07-2938]



[[Page 32850]]

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DEPARTMENT OF HEALTH AND HUMAN SERVICES


Office of the National Coordinator for Health Information 
Technology; American Health Information Community Quality Workgroup 
Meeting

ACTION: Announcement of meeting.

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SUMMARY: This notice announces the 9th meeting of the American Health 
Information Community Quality Workgroup in accordance with the Federal 
Advisory Committee Act (Pub. L. 92-463, 5 U.S.C., App.)

DATES: June 22, 2007, from 1 p.m. to 4 p.m.

ADDRESSES: Mary C. Switzer Building (330 C Street, SW., Washington, DC 
20201), Conference Room 4090 (please bring photo ID for entry to a 
Federal building).

FOR FURTHER INFORMATION CONTACT: http://www.hhs.gov/healthit/ahic/quality/.

SUPPLEMENTARY INFORMATION: Over the next several months, the Quality 
Workgroup will begin to gather information from a wide variety of 
stakeholders on the data infrastructure strategies--data aggregation 
including merging of data from multiple sources and measuring across 
episodes of care--that have been developed and implemented across the 
healthcare community.
    The following questions are designed to draw out responses from 
industry members, regardless of size or implementation status, on real-
time experiences with creating and/or implementing a data 
infrastructure strategy for quality measurement and reporting. The 
responses will be analyzed and summarized to help Quality Workgroup 
members understand the current challenges, successes, and best 
practices within the industry.

Questions

    1. Please describe the process through which data is typically 
collected and aggregated, providing real-time examples and drawing from 
your experiences where possible. Please include the following key 
points:
    <bullet> What business functions (e.g., transparency, payment, 
network creation, internal quality improvement, public reporting, 
disease management) are supported through aggregation of patient-level 
data?
    <bullet> What financial models support the operational costs of 
aggregating patient-level data (e.g., internal costs, payers or 
employers paying a set fee, sale of data to third parties, grants, 
etc.)?
    <bullet> In your experience, what types of data can be collected 
and merged together? For instance, can electronic health record data be 
merged with other data (claims, lab results, pharmacy)? What are the 
common barriers to merging data from multiple sources?
    <bullet> What strategies can be used to help ensure that data that 
is generated by or stored in multiple systems within an organization 
can be collected and aggregated?
    <bullet> What strategies could be employed to ensure that data can 
be aggregated from multiple organizations? What types of agreements and 
system changes are needed for this to occur?
    <bullet> In your experience, when a single data element is accepted 
from multiple and distinct sources (e.g., claims data, electronic 
health records, lab results), from which sources is duplicate data 
typically accepted? What processes are needed to ensure that the data 
are comparable?
    <bullet> What data would you like to collect but do not currently 
have access to or the ability to collect?
    <bullet> Of the data that you can currently access, what data 
cannot be reasonably aggregated at a patient level with data from other 
systems due to technical, business or policy challenges: Please 
describe the challenges.
    <bullet> What are some best practices or lessons learned that could 
be shared about collecting and aggregating data from multiple sources?
    <bullet> Is your experience, is a centralized or distributed 
database (i.e., one with multiple storage sites) preferable? What are 
the pros and cons of using either approach?
    <bullet> What factors should be considered when determining what 
type of entity should serve as the database host? Can you provide 
examples of the database host arrangements with which you have 
experience?
    <bullet> What types of organizations need access to data form an 
aggregated database? Can you describe the types of data-sharing 
agreements that are needed to share data from an aggregated database?
    <bullet> What privacy/security challenges are common when 
considering the collection and aggregation of data from multiple 
sources as well as the sharing of that data? What strategies can be 
used to overcome these challenges?
    2. Can you please input on the strategies that should be used to 
develop a longitudinal view of patient data to evaluate clinical 
performance, providing real-time examples and drawing from your 
experiences where possible? Please focus on the following key points:
    <bullet> What strategies can be used to link patient-level data to 
define an episode of care (e.g., commercial software vs. custom 
algorithms)?
    <bullet> For what medical conditions is longitudinal measurement 
the most useful? Why?
    <bullet> What data sources are needed (e.g. pharmacy, lab results, 
claims data, electronic health records, data from multiple 
organizations) to collect longitudinal data for episodic measurement? 
Can you describe initiatives where this has been done successfully?
    <bullet> In your experience, how is an episode-of-care quality (and 
cost) measurement strategy influenced by data availability? Data 
reliability?
    <bullet> What factors should be considered when determining what 
type of entity should serve as the database host for longitudinal data? 
Can you provide examples of hosting arrangements with which you have 
experience?
    <bullet> What implementation barriers exist related to data 
collection and aggregation of longitudinal data? What strategies can be 
employed to overcome them?
    <bullet> What outcome and process measures are best supported by an 
episode-of-care methodology? Can you provide specific examples using a 
methodology with which you are familiar?
    <bullet> What feedback mechanisms are used or should be used to 
provide information back to providers or payers to help them better 
manage patient care? Are these methods retrospective, concurrent, or 
prospective? What are the barriers to providing concurrent or 
prospective feedback?
    <bullet> What are some best practices or lessons learned that could 
be shared on longitudinal data management strategies?
    The meeting will be available via internet access. For additional 
information, go to http://www.hhs.gov/healthit/ahic/quality_instruct.html.
    Persons wishing to submit written testimony, please contact 
Michelle Murray via e-mail at <a href="/cdn-cgi/l/email-protection#315c585259545d5d541f5c4443435048715959421f565e47"><span class="__cf_email__" data-cfemail="3c51555f54595050591251494e4e5d457c54544f125b534a">[email protected]</span></a>.

    Dated: June 7, 2007.
Judith Sparrow,
Director, American Health Information Community, Office of Programs and 
Coordination, Office of the National Coordinator for Health Information 
Technology.
[FR Doc. 07-2938 Filed 6-13-07; 8:45 am]
BILLING CODE 4150-24-M


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