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The Delivery Science Rapid Analysis Program: A Research and Operational Partnership at Kaiser Permanente Northern California

Health care researchers and delivery system leaders share a common mission to improve health care quality and outcomes. However, differing timelines, incentives, and priorities are often a barrier to research and operational partnerships. In addition, few funding mechanisms exist to generate and solicit analytic questions that are of interest to both research and to operations within health care settings, and provide rapid results that can be used to improve practice and outcomes. The Delivery Science Rapid Analysis Program (RAP) was formed in 2013 within the Kaiser Permanente Northern California Division of Research, sponsored by The Permanente Medical Group. A Steering Committee consisting of both researchers and clinical leaders solicits and reviews proposals for rapid analytic projects that will use existing data and are feasible within 6 months and with up to $30,000 (approximately 25-50% full-time equivalent) of programmer/analyst effort. Review criteria include the importance of the analytic question for both research and operations, and the potential for the project to have a significant impact on care delivery within 12 months of completion. The RAP funded 5 research and operational analytic projects between 2013 and 2017. These projects spanned a wide range of clinical areas, including lupus, pediatric obesity, diabetes, e-cigarette use, and hypertension. The hypertension RAP project, which focused on optimizing thiazide prescribing in Black/African-American patients with hypertension, led to new insights that inform an equitable care quality metric designed to reduce blood pressure control disparities throughout the KPNC region. Programs that actively encourage research and operational analytic partnerships have significant potential to improve care, enhance research collaborations, and contribute to the building and sustaining of learning health care systems.

Authors: Schmittdiel JA; Dlott R; Young JD; Rothmann MB; Dyer W; Adams AS

Learn Health Syst. 2017 Oct;1(4). Epub 2017-07-12.

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