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Research at the Innovation Center
This Week's Topic is -
Defining, Delivering and Demonstrating Quality Care in AHC: Measurement
Connections Between Quality Measurement and Improvement
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Donald M. Berwick, MD, Brent James, MD, MSTAT, and Molly Joel Coye, MD
January 2003
Medical Care
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BACKGROUND: Measurement is necessary but not sufficient for quality improvement. Because the purpose of the national quality measurement and reporting system (NQMRS) is to improve quality, a discussion of the link between measurement and improvement is critical for ensuring an appropriate system design. CONCLUSIONS: Neither the dynamics of selection nor the dynamics of improvement work reliably today. The barriers are not just in the lack of uniform, simple, and reliable measurements, they also include a lack of capacity among the organizations and individuals acting on both pathways. |
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The Impact of Quality-Reporting Programs on Hospital Operations
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Hoangmai H. Pham, Jennifer Coughlan and Ann. S. O’Malley
2006
Health Affairs
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SUMMARY: We used data from the 2005–06 Community Tracking Study site visits to examine the impact of quality reporting on hospitals’ data collection and review processes, feedback and accountability mechanisms, quality improvement activities, and resource allocation. Individual hospitals participate in multiple, varied reporting programs with distinct effects on hospital operations. Reporting programs play complementary roles in encouraging quality improvement but are poorly coordinated and command sizable resources, in large part because of inadequate information technology. Policy should be directed at encouraging formal assessments of how individual and combinations of programs affect quality outcomes, and the development of adaptable information systems. |
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Using Routine Comparative Data to Assess the Quality of Health Care: Understanding and Avoiding Common Pitfalls
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A. Powell, H. Davies, and R. Thomson
April 2003
Quality and Safety in Health Care
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SUMMARY:Measuring the quality of health care has become a major concern for funders and providers of health services in recent decades. One of the ways in which quality of care is currently assessed is by taking routinely collected data and analysing them quantitatively. The use of routine data has many advantages but there are also some important pitfalls. Collating numerical data in this way means that comparisons can be made—whether over time, with benchmarks, or with other healthcare providers (at individual or institutional levels of aggregation). Inevitably, such comparisons reveal variations. The natural inclination is then to assume that such variations imply rankings: that the measures reflect quality and that variations in the measures reflect variations in quality. This paper identifies reasons why these assumptions need to be applied with care, and illustrates the pitfalls with examples from recent empirical work. It is intended to guide not only those who wish to interpret comparative quality data, but also those who wish to develop systems for such analyses themselves. |
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