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将入院时指标纳入医疗保险索赔中,以告知医院质量衡量风险调整模型。

Incorporating Present-on-Admission Indicators in Medicare Claims to Inform Hospital Quality Measure Risk Adjustment Models.

机构信息

Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut.

Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.

出版信息

JAMA Netw Open. 2021 May 3;4(5):e218512. doi: 10.1001/jamanetworkopen.2021.8512.

Abstract

IMPORTANCE

Present-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting.

OBJECTIVE

To assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS).

DESIGN, SETTING, AND PARTICIPANTS: This comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020.

MAIN OUTCOMES AND MEASURES

Changes in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment.

RESULTS

Data from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure).

CONCLUSIONS AND RELEVANCE

The findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.

摘要

重要性

在行政索赔数据中使用入院时已有(POA)指标可以帮助研究人员区分预先存在的疾病和在住院期间获得的疾病。在国际疾病分类和相关健康问题第十次修订版(ICD-10)中,尚未研究添加 POA 信息对基于索赔的医院质量衡量标准的影响,以便更好地了解患者的潜在风险因素。

目的

评估 Medicare 索赔中 POA 指标的使用情况,并评估在确定医疗保险和医疗补助服务中心(CMS)使用的公开报告结果衡量标准的风险因素时,将 POA 指标纳入风险调整模型所带来的医院和患者结果。

设计、地点和参与者:本比较效果研究使用了 2015 年 7 月 1 日至 2018 年 6 月 30 日期间的全国性 CMS 索赔数据。修改了 6 项评估再入院和死亡率结果的医院质量衡量标准,以在风险调整模型中纳入 POA 指标。然后,使用 POA 的模型与使用现有并发症护理算法的模型进行比较,以评估风险模型性能的变化。将 Medicare 按服务收费和退伍军人事务部的所有 65 岁及以上患者的住院患者索赔数据纳入分析,这些患者在测量期内患有急性心肌梗死、心力衰竭或肺炎的住院治疗。数据于 2019 年 9 月至 2020 年 3 月之间进行分析。

主要结果和措施

在风险调整中纳入 POA 指标后,患者水平(C 统计量)和医院水平(风险标准化结果率的五分位数变化)模型性能的变化。

结果

共有 6027988 例指数住院患者纳入分析,范围从急性心肌梗死死亡率衡量标准的 491366 例(269209 [54.8%]男性;平均[标准差]年龄,78.2[8.3]岁)到肺炎再入院衡量标准的 1395870 例(677158 [48.5%]男性;平均[标准差]年龄,80.3[8.7]岁)。使用 POA 指标与风险调整模型性能的改善相关,特别是对于死亡率衡量标准(例如,当将 POA 指标纳入急性心肌梗死死亡率衡量标准时,C 统计量从 0.728[95%CI,0.726-0.730]增加到 0.774[95%CI,0.773-0.776])。

结论和相关性

这项质量改进研究的结果表明,在医院质量结果衡量标准的风险调整方法中利用 POA 指标可能有助于更全面地捕获患者的风险因素并提高整体模型性能。纳入 POA 指标不需要医院额外的努力,并且易于在公开报告的质量结果衡量标准中实施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aadc/8116982/e2466a654c77/jamanetwopen-e218512-g001.jpg

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