How Do Quality Improvement Interventions Succeed?
Archetypes of Success and Failure
The quality of heath care in the United States is suboptimal and needs to be improved as part of increasing the value of costly health care services. Achieving broad quality improvements will require reproducing local quality improvement intervention (QII) successes on a larger scale. Such replication has been difficult to come by, however, because we don't understand the "how" of quality improvement very well. The goal of this analysis was to ascertain the predominant themes and patterns likely to be associated with producing successful QIIs. Cases were compared according to each dimension of the framework. The general approach involved establishing the range (the maximally diverse exemplars), the central tendency (the modal example) and the distribution (the pattern of variation) within each dimension and subcategory. The author assessed cases first on a univariate basis and then on a multivariate basis by grouping them according to more and less successful cases, different domains of care, and different degrees of organizational integration. The strengths of this study include its comparative case study design as well as its unique investigator-based sampling strategy, which sought to maximize the observed variation across cases while achieving an equal balance of "more" and "less" successful cases. Future research endeavors should attempt to operationalize and validate the archetypes suggested by this study. Doing so will produce broadly generalizable and practical tools for explaining how quality improvement results are generated, and for strategizing for success when implementing interventions in different settings.
- Copyright: RAND Corporation
- Availability: Web-Only
- Pages: 222
- Document Number: RGSD-282
- Year: 2011
- Series: Dissertations
This document was submitted as a dissertation in May 2011 in partial fulfillment of the requirements of the doctoral degree in public policy analysis at the Pardee RAND Graduate School. The faculty committee that supervised and approved the dissertation consisted of Steven Asch (Chair), Gery Ryan, Lisa Rubenstein, and Peter Mendel.
This report is part of the RAND Corporation dissertation series. PRGS dissertations are produced by graduate fellows of the Pardee RAND Graduate School, the world's leading producer of Ph.D.'s in policy analysis. The dissertations are supervised, reviewed, and approved by a PRGS faculty committee overseeing each dissertation.
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