Publications by authors named "Kyle Barr"

Goal: A lack of improvement in productivity in recent years may be the result of suboptimal measurement of productivity. Hospitals and clinics benefit from external benchmarks that allow assessment of clinical productivity. Work relative value units have long served as a common currency for this purpose.

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Objectives: To improve access, the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act of 2018 mandated a 2-year study of medical scribes in Veterans Health Administration specialty clinics and emergency departments. Medical scribes are employed in clinical settings with the goals of increasing provider productivity and satisfaction by minimizing physicians' documentation burden. Our objective is to quantify the economic outcomes of the MISSION Act scribes trial.

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Background: Although long-term opioid therapy (LTOT) has its own risks, opioid discontinuation could pose harm for high-risk Veterans Health Administration (VHA) patients receiving LTOT. There is limited information on the impact of a mandate requiring providers to perform case reviews on high-risk patients with an active opioid prescription (ie, mandated case review policy) on opioid discontinuation and mortality.

Methods: Our study is a secondary data analysis of a 23-month stepped-wedge cluster randomized controlled trial between April 2018 and March 2020.

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Aims: The Veterans Health Administration (VHA) implemented the Stratification Tool for Opioid Risk Mitigation (STORM) to reduce the risk of serious adverse events (SAE) among patients with opioid analgesic prescriptions. VHA facilities were mandated to case review patients identified as high risk by STORM. The aim of this study was to measure the effect of this mandate on all-cause mortality and SAEs among VHA patients newly diagnosed with opioid use disorder (OUD).

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Resource-constrained delivery systems often have access issues, causing patients to wait a long time to see a provider. We develop theoretical and empirical models of wait times and apply them to primary care delivery by the U.S.

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