RTI International, Waltham, MA.
RTI International, Waltham, MA.
Arch Phys Med Rehabil. 2018 Jun;99(6):1049-1059. doi: 10.1016/j.apmr.2017.07.008. Epub 2017 Aug 9.
To examine facility-level rates of all-cause, unplanned hospital readmissions for 30 days after discharge from inpatient rehabilitation facilities (IRFs).
Observational design.
Inpatient rehabilitation facilities.
Medicare fee-for-service beneficiaries (N=567,850 patient-stays).
Not applicable.
The outcome is all-cause, unplanned hospital readmission rates for IRFs. We adapted previous risk-adjustment and statistical approaches used for acute care hospitals to develop a hierarchical logistic regression model that estimates a risk-standardized readmission rate for each IRF. The IRF risk-adjustment model takes into account patient demographic characteristics, hospital diagnoses and procedure codes, function at IRF admission, comorbidities, and prior hospital utilization. We presented national distributions of observed and risk-standardized readmission rates and estimated confidence intervals to make statistical comparisons relative to the national mean. We also analyzed the number of days from IRF discharge until hospital readmission.
The national observed hospital readmission rate by 30 days postdischarge from IRFs was 13.1%. The mean unadjusted readmission rate for IRFs was 12.4%±3.5%, and the mean risk-standardized readmission rate was 13.1%±0.8%. The C-statistic for our risk-adjustment model was .70. Nearly three-quarters of IRFs (73.4%) had readmission rates that were significantly different from the mean. The mean number of days to readmission was 13.0±8.6 days and varied by rehabilitation diagnosis.
Our results demonstrate the ability to assess 30-day, all-cause hospital readmission rates postdischarge from IRFs and the ability to discriminate between IRFs with higher- and lower-than-average hospital readmission rates.
调查出院后 30 天内所有原因、非计划性住院再入院率,以评估住院康复机构(IRF)的情况。
观察性设计。
住院康复机构。
医疗保险付费服务的受益人(N=567850 名患者住院)。
不适用。
所有原因、非计划性住院再入院率为 IRF 的结果。我们采用了先前用于急性护理医院的风险调整和统计方法,开发了一个层次逻辑回归模型,该模型估计每个 IRF 的风险标准化再入院率。IRF 风险调整模型考虑了患者的人口统计学特征、医院诊断和程序代码、IRF 入院时的功能、合并症和先前的医院使用情况。我们展示了观察到的和风险标准化再入院率的全国分布,并估计了置信区间,以便与全国平均值进行统计比较。我们还分析了从 IRF 出院到住院再入院的天数。
IRF 出院后 30 天内的全国观察到的住院再入院率为 13.1%。IRF 未调整的再入院率平均为 12.4%±3.5%,风险标准化的再入院率平均为 13.1%±0.8%。我们的风险调整模型的 C 统计量为 0.70。近四分之三(73.4%)的 IRF 的再入院率与平均值显著不同。再入院的平均天数为 13.0±8.6 天,且因康复诊断而异。
我们的研究结果表明,能够评估出院后 30 天内所有原因、非计划性住院再入院率,并能够区分再入院率高于或低于平均水平的 IRF。