Escobar Gabriel J, Baker Jennifer M, Turk Benjamin J, Draper David, Liu Vincent, Kipnis Patricia
Regional Director for Hospital Operations Research for The Permanente Medical Group, Inc, at the Division of Research in Oakland, CA.
Public Health Program Specialist for Contra Costa Public Health Clinic Services in Martinez, CA.
Perm J. 2017;21:16-084. doi: 10.7812/TPP/16-084.
This article is not a traditional research report. It describes how conducting a specific set of benchmarking analyses led us to broader reflections on hospital benchmarking. We reexamined an issue that has received far less attention from researchers than in the past: How variations in the hospital admission threshold might affect hospital rankings. Considering this threshold made us reconsider what benchmarking is and what future benchmarking studies might be like. Although we recognize that some of our assertions are speculative, they are based on our reading of the literature and previous and ongoing data analyses being conducted in our research unit. We describe the benchmarking analyses that led to these reflections.
The Centers for Medicare and Medicaid Services' Hospital Compare Web site includes data on fee-for-service Medicare beneficiaries but does not control for severity of illness, which requires physiologic data now available in most electronic medical records.To address this limitation, we compared hospital processes and outcomes among Kaiser Permanente Northern California's (KPNC) Medicare Advantage beneficiaries and non-KPNC California Medicare beneficiaries between 2009 and 2010.
We assigned a simulated severity of illness measure to each record and explored the effect of having the additional information on outcomes.
We found that if the admission severity of illness in non-KPNC hospitals increased, KPNC hospitals' mortality performance would appear worse; conversely, if admission severity at non-KPNC hospitals' decreased, KPNC hospitals' performance would appear better.
Future hospital benchmarking should consider the impact of variation in admission thresholds.
本文并非传统的研究报告。它描述了进行一组特定的基准分析如何引导我们对医院基准有了更广泛的思考。我们重新审视了一个相较于过去受到研究者关注少得多的问题：医院入院门槛的差异如何影响医院排名。考虑这个门槛促使我们重新思考基准是什么以及未来的基准研究可能会是什么样。尽管我们认识到我们的一些断言具有推测性，但它们是基于我们对文献的阅读以及我们研究单位正在进行的既往和当前数据分析得出的。我们描述了引发这些思考的基准分析。
医疗保险和医疗补助服务中心（Centers for Medicare and Medicaid Services）的医院比较网站（Hospital Compare Web site）包含了按服务收费的医疗保险受益人的数据，但未对疾病严重程度进行控制，而疾病严重程度的数据现在大多数电子病历中都可获取。为解决这一局限性，我们比较了2009年至2010年期间北加利福尼亚凯撒医疗集团（Kaiser Permanente Northern California，KPNC）的医疗保险优势计划受益人和非KPNC的加利福尼亚医疗保险受益人之间的医院流程和结果。
我们为每条记录分配了一个模拟的疾病严重程度测量值，并探讨了获取这些额外信息对结果的影响。
我们发现，如果非KPNC医院的入院疾病严重程度增加，KPNC医院的死亡率表现会显得更差；相反，如果非KPNC医院的入院严重程度降低，KPNC医院的表现会显得更好。
未来的医院基准研究应考虑入院门槛差异的影响。
