Zheng Sarah, Hanchate Amresh, Shwartz Michael
University of Victoria Gustavson School of Business, 3800 Finnerty Rd, Victoria, BC, V8P 5C2, Canada.
Boston University School of Medicine, 801 Massachusetts Ave Crosstown Center, Boston, MA, 02118, USA.
BMC Health Serv Res. 2019 Mar 12;19(1):155. doi: 10.1186/s12913-019-3983-7.
To overcome the limitations of administrative data in adequately adjusting for differences in patients' risk of readmissions, recent studies have added supplemental data from patient surveys and other sources (e.g., electronic health records). However, judging the adequacy of enhanced risk adjustment for use in assessment of 30-day readmission as a hospital quality indicator is not straightforward. In this paper, we evaluate the adequacy of risk adjustment by comparing the one-year costs of those readmitted within 30 days to those not after excluding the costs of the readmission.
In this two-step study, we first used comprehensive administrative and survey data on a nationally representative Medicare cohort of hospitalized patients to compare patients with a medical admission who experienced a 30-day readmission to patients without a readmission in terms of their overall Medicare payments during 12 months following the index discharge. We then examined the extent to which a series of enhanced risk adjustment models incorporating code-based comorbidities, self-reported health status and prior healthcare utilization, reduced the payment differences between the admitted and not readmitted groups.
Our analytic cohort consisted 4684 index medical hospitalization of which 842 met the 30-day readmission criteria. Those readmitted were more likely to be older, White, sicker and with higher healthcare utilization in the previous year. The unadjusted subsequent one-year Medicare spending among those readmitted ($56,856) was 60% higher than that among the non-readmitted ($35,465). Even with enhanced risk adjustment, and across a variety of sensitivity analyses, one-year Medicare spending remained substantially higher (46.6%, p < 0.01) among readmitted patients.
Enhanced risk adjustment models combining health status indicators from administrative and survey data with previous healthcare utilization are unable to substantially reduce the cost differences between those medical admission patients readmitted within 30 days and those not. The unmeasured patient severity that these cost differences most likely reflect raises the question of the fairness of programs that place large penalties on hospitals with higher than expected readmission rates.
为克服行政数据在充分调整患者再入院风险差异方面的局限性,近期研究补充了来自患者调查及其他来源(如电子健康记录)的额外数据。然而,判断用于评估30天再入院作为医院质量指标的强化风险调整是否充分并非易事。在本文中,我们通过比较30天内再入院患者与未再入院患者在排除再入院费用后的一年成本,来评估风险调整的充分性。
在这项分两步进行的研究中,我们首先使用了关于全国代表性医疗保险住院患者队列的综合行政和调查数据,比较因医疗入院且经历30天再入院的患者与未再入院患者在首次出院后12个月内的总体医疗保险支付情况。然后,我们研究了一系列纳入基于编码的合并症、自我报告的健康状况和既往医疗利用情况的强化风险调整模型在多大程度上缩小了再入院组与未再入院组之间的支付差异。
我们的分析队列包括4684例首次医疗住院病例,其中842例符合30天再入院标准。再入院患者更可能年龄较大、为白人、病情较重且上一年的医疗利用率较高。再入院患者未调整的后续一年医疗保险支出(56,856美元)比未再入院患者(35,465美元)高出60%。即使进行了强化风险调整,且经过各种敏感性分析,再入院患者的一年医疗保险支出仍显著更高(46.6%,p < 0.01)。
将行政和调查数据中的健康状况指标与既往医疗利用情况相结合的强化风险调整模型,无法大幅缩小30天内再入院的医疗入院患者与未再入院患者之间的成本差异。这些成本差异很可能反映出的未测量的患者严重程度,引发了对那些对再入院率高于预期的医院施加高额处罚的项目公平性的质疑。