Measuring Preventable Outcomes: Global Cardiovascular Risk (GCVR). Issue 2 (20th April 2017)

• Record Type: Journal Article
• Authors: Hamlin, Benjamin N.
• Is Part Of: EGEMS. Volume 5:Issue 2(2017)
• Publication Date: 2017-04-20
• Subjects: Performance Measurement -- Cardiovascular Disease -- Patient centered care; Medical records -- Data processing -- Periodicals; Medical care -- Data processing -- Periodicals; Medical Records; Automatic Data Processing; Medical care -- Data processing; Medical records -- Data processing; Periodicals; Periodicals; 651.504261
• DOI: 10.13063/2327-9214.1289
• Languages: English
• ISSNs: 2327-9214

Abstract

The National Committee for Quality Assurance (NCQA) piloted a new approach to quality measurement meant to reduce avoidable cardiac events and improve overall population health. In this pilot, we investigated whether a standardized technical specification could sufficiently define a process to reliably generate predicted outcome scores from heterogeneous electronic clinical data systems (ECDS) [1 ]. Patient data were electronically extracted from four health care organizations and processed by the Archimedes, Inc. Global Outcomes calculator, generating scores indicating future cardiovascular event probability for each provider's patient population. These Global Cardiovascular Risk (GCVR) scores represent the gap between current level of care achieved and optimal care for each clinician's patients, with a greater score indicating better performance. As GCVR requires more patient data than do traditional quality measures, we addressed feasibility and data completeness questions in order to understand the prospects of a wholly new quality concept. This pilot successfully produced GCVR scores for 2, 251 clinicians, representing approximately 60 percent of the total patient population under study. To our knowledge, this is the first time predictive models have been proposed for quality measurement, and our pilot successfully demonstrated that a predicted outcome measure is feasible using electronic patient data. However, new specification standards are required before this approach is fully scalable to a national quality reporting program.