Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems.

Area of Science:

• Health Services Research
• Health Policy
• Health Informatics

Background:

• Formal health care delivery systems are increasingly prevalent in the U.S.
• Research on these systems is limited by a lack of standardized criteria for defining them.
• Empirically identifying systems using real-world data is crucial for policy-relevant studies.

Purpose of the Study:

• To assess national data sources for identifying and describing health care delivery systems and their members.
• To inform policy-relevant research by establishing criteria for system identification.
• To leverage the Agency for Healthcare Research and Quality's Comparative Health System Performance (CHSP) initiative experience.

Main Methods:

• Evaluation of five national data sources: AHA annual survey, Healthcare Relational Services Databases, SK&A Databases, PECOS, and IRS 990 forms.
• Analysis of data source strengths and limitations regarding system membership and relationship tracking.
• Exploration of combining data sources to overcome individual limitations.

Main Results:

• No single national data source fully captures U.S. health care systems and their components.
• Each data source possesses unique strengths and weaknesses for system identification.
• The CHSP initiative aims to develop a model for integrating these data sources.

Conclusions:

• Combining multiple national data sources is necessary to accurately identify and describe health care delivery systems.
• Developing repeatable methods for system identification will facilitate performance comparisons.
• This approach supports research on how organizational structures impact health care delivery and performance.