32850 Federal Register / Vol. 72, No. 114 / Thursday, June 14, 2007 / Notices 

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. 

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: 

• What business functions (e.g., 

transparency, payment, network 

creation, internal quality improvement, 

public reporting, disease management) 

are supported through aggregation of 

patient-level data? 

• What financial models support the 

operational costs of aggregating patientlevel data (e.g., internal costs, payers or 

employers paying a set fee, sale of data 

to third parties, grants, etc.)? 

• 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? 

• 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? 

• 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? 

• 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? 

• What data would you like to collect 

but do not currently have access to or 

the ability to collect? 

• 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. 

• What are some best practices or 

lessons learned that could be shared 

about collecting and aggregating data 

from multiple sources? 

• 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? 

• 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? 

• 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? 

• 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: 

• What strategies can be used to link 

patient-level data to define an episode 

of care (e.g., commercial software vs. 

custom algorithms)? 

• For what medical conditions is 

longitudinal measurement the most 

useful? Why? 

• 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? 

• In your experience, how is an 

episode-of-care quality (and cost) 

measurement strategy influenced by 

data availability? Data reliability? 

• 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? 

• What implementation barriers exist 

related to data collection and 

aggregation of longitudinal data? What 

strategies can be employed to overcome 

them? 

• 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? 

• 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? 

• 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 

michelle.murray@hhs.gov. 

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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