Comparison of Methodologies for Calculating Quality Measures Based on Administrative Data versus Clinical Data from an Electronic Health Record System: Implications for Performance Measures
- Affiliations of the authors: Palo Alto Medical Foundation (PCT, LQ), Palo Alto, CA; Lumetra (MR, MFA, JG), San Francisco, CA
- Correspondence and reprints: Paul C. Tang, MD, Palo Alto Medical Foundation, 795 El Camino Real, Palo Alto, CA 94301; Tel: (650) 853-5775; Fax: (650) 853-6050; e-mail: <pctang{at}pacbell.net>
- Received 9 July 2006
- Accepted 11 October 2006
Abstract
New reimbursement policies and pay-for-performance programs to reward providers for producing better outcomes are proliferating. Although electronic health record (EHR) systems could provide essential clinical data upon which to base quality measures, most metrics in use were derived from administrative claims data. We compared commonly used quality measures calculated from administrative data to those derived from clinical data in an EHR based on a random sample of 125 charts of Medicare patients with diabetes. Using standard definitions based on administrative data (which require two visits with an encounter diagnosis of diabetes during the measurement period), only 75% of diabetics determined by manually reviewing the EHR (the gold standard) were identified. In contrast, 97% of diabetics were identified using coded information in the EHR.
The discrepancies in identified patients resulted in statistically significant differences in the quality measures for frequency of HbA1c testing, control of blood pressure, frequency of testing for urine protein, and frequency of eye exams for diabetic patients. New development of standardized quality measures should shift from claims-based measures to clinically based measures that can be derived from coded information in an EHR. Using data from EHRs will also leverage their clinical content without adding burden to the care process.
Footnotes
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Funding for the study was provided through Lumetra, under contract with CMS.
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The analyses upon which this publication is based were performed under contract number 500-02-CA02, funded by the Centers for Medicare & Medicaid Services, an agency of the U.S. Department of Health and Human Services. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. The authors assume full responsibility for the accuracy and completeness of the ideas presented.
