Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care
Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care
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DOI：
10.1097/01.mlr.0000228002.43688.c2
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发表时间：
2006-11-01
期刊：
影响因子：
3
通讯作者：
Burnand, Bernard
中科院分区：
文献类型：
--
作者：
Halfon, Patricia;Eggli, Yves;Burnand, Bernard
背景：医院再入院率已被提出作为一项重要的结果指标，可由常规统计计算。然而，最常用的测量方法会引起概念上的问题。目的：我们试图评估计算机算法在最小偏差、标准效度和测量精度的基础上识别可避免再入院的有用性。研究设计与对象：采用49家医院的131809例活出院住院患者，比较风险调整方法的预测效果。对12家医院570对出院/再入院病历的随机样本子集进行了审查，以估计筛查潜在可避免再入院的预测价值。措施：通过计算机化算法确定潜在可避免的再入院，定义为与先前住院情况相关且不属于护理计划的一部分且在先前出院后30天内发生的再入院。不可避免的再入境被视为审查事件。结果：共有5.2%的住院患者在本可避免的情况下再次入院，其中17%在不同的医院。筛查的预测值为78%；经过筛选的再入院患者中有27%被认为是可以避免的。明确可避免再入院率与所有再入院率、潜在可避免再入院率、观察再入院率与预期再入院率的相关系数分别为0.42、0.56、0.66。使用临床信息的调整模型表现更好。结论：调整后的潜在可避免再入院率在科学上是合理的，足以保证将其纳入医院质量监测。
Background: The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues.Objectives: We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision.Research Design and Subjects: A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions.Measures: Potentially avoidable readmissions, defined as readmissions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events.Results: A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correlation between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information performed better.Conclusion: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.