来源类型 | Publication
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| Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems |
| Genna R. Cohen; David J. Jones; Jessica Heeringa; Kirsten Barrett; Michael F. Furukawa; Dan Miller; Anne Mutti; James D. Reschovsky; Rachel Machta; Stephen M. Shortell; Taressa Fraze; and Eugene Rich
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发表日期 | 2017-12-30
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出版者 | eGEMs: The Journal of Electronic Health Data and Methods, vol. 5, issue 3
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出版年 | 2017
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语种 | 英语
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概述 | Researchers assess available data sources to identify and describe health care delivery systems, including system members and their relationships. They summarize strengths and limitations for identifying and describing systems due to varied content, linkages across data sources, and data collection.", |
摘要 |
Key Findings:
- No single national data source provides a complete picture of US health care delivery systems and their component hospitals, physician practices and physicians.
- Combining various sources can help compensate for each source’s limitations, and when information overlaps across sources, it can be used for validation
- Being able to examine linkages among system components gives researchers flexibility to tailor the definition of systems according to the objectives of their analysis
- The CHSP initiative recently released an inaugural Compendium of US Health Care Systems, which provides an early model of how such data can be used to identify systems in a way that can be updated or repeated over time and linked to other data sources to support analysis of how different types of organizations delivery health care.
Health care delivery systems are a growing presence in the U.S., yet research is hindered by the lack of universally agreed-upon criteria to denote formal systems. A clearer understanding of how to leverage real-world data sources to empirically identify systems is a necessary first step to such policy-relevant research. We draw from our experience in the Agency for Healthcare Research and Quality’s Comparative Health System Performance (CHSP) initiative to assess available data sources to identify and describe systems, including system members (for example, hospitals and physicians) and relationships among the members (for example, hospital ownership of physician groups). We highlight five national data sources that either explicitly track system membership or detail system relationships: (1) American Hospital Association annual survey of hospitals; (2) Healthcare Relational Services Databases; (3) SK&A Healthcare Databases; (4) Provider Enrollment, Chain, and Ownership System; and (5) Internal Revenue Service 990 forms. Each data source has strengths and limitations for identifying and describing systems due to their varied content, linkages across data sources, and data collection methods. In addition, although no single national data source provides a complete picture of U.S. systems and their members, the CHSP initiative will create an early model of how such data can be combined to compensate for their individual limitations. Identifying systems in a way that can be repeated over time and linked to a host of other data sources will support analysis of how different types of organizations deliver health care and, ultimately, comparison of their performance. |
URL | https://www.mathematica.org/our-publications-and-findings/publications/leveraging-diverse-data-sources-to-identify-and-describe-us-health-care-delivery-systems
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来源智库 | Mathematica Policy Research (United States)
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资源类型 | 智库出版物
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条目标识符 | http://119.78.100.153/handle/2XGU8XDN/489117
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推荐引用方式 GB/T 7714 |
Genna R. Cohen,David J. Jones,Jessica Heeringa,et al. Leveraging Diverse Data Sources to Identify and Describe U.S. Health Care Delivery Systems. 2017.
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