Huang Donna, Slocum Chloe, Silver Julie K, Morgan James W, Goldstein Richard, Zafonte Ross, Schneider Jeffrey C
a Department of Physical Medicine and Rehabilitation , Spaulding Rehabilitation Hospital/Harvard Medical School , Massachusetts , USA.
b Commonwealth Fund Mongan Fellow, Harvard Medical School, Harvard T.H. Chan School of Public Health , Department of Health Policy and Management, Spaulding Rehabilitation Hospital, Department of Physical Medicine and Rehabilitation , Massachusetts , USA.
J Spinal Cord Med. 2019 Jan;42(1):20-31. doi: 10.1080/10790268.2018.1453436. Epub 2018 Mar 29.
CONTEXT/OBJECTIVE: Acute care readmission has been identified as an important marker of healthcare quality. Most previous models assessing risk prediction of readmission incorporate variables for medical comorbidity. We hypothesized that functional status is a more robust predictor of readmission in the spinal cord injury population than medical comorbidities.
Retrospective cross-sectional analysis.
Inpatient rehabilitation facilities, Uniform Data System for Medical Rehabilitation data from 2002 to 2012.
traumatic spinal cord injury patients.
A logistic regression model for predicting acute care readmission based on demographic variables and functional status (Functional Model) was compared with models incorporating demographics, functional status, and medical comorbidities (Functional-Plus) or models including demographics and medical comorbidities (Demographic-Comorbidity). The primary outcomes were 3- and 30-day readmission, and the primary measure of model performance was the c-statistic.
There were a total of 68,395 patients with 1,469 (2.15%) readmitted at 3 days and 7,081 (10.35%) readmitted at 30 days. The c-statistics for the Functional Model were 0.703 and 0.654 for 3 and 30 days. The Functional Model outperformed Demographic-Comorbidity models at 3 days (c-statistic difference: 0.066-0.096) and outperformed two of the three Demographic-Comorbidity models at 30 days (c-statistic difference: 0.029-0.056). The Functional-Plus models exhibited negligible improvements (0.002-0.010) in model performance compared to the Functional models.
Readmissions are used as a marker of hospital performance. Function-based readmission models in the spinal cord injury population outperform models incorporating medical comorbidities. Readmission risk models for this population would benefit from the inclusion of functional status.
背景/目的:急性病再入院已被视为医疗质量的一项重要指标。以往多数评估再入院风险预测的模型纳入了医疗合并症变量。我们假设,在脊髓损伤人群中,功能状态比医疗合并症更能有力地预测再入院情况。
回顾性横断面分析。
住院康复机构,2002年至2012年医疗康复统一数据系统。
创伤性脊髓损伤患者。
将基于人口统计学变量和功能状态预测急性病再入院的逻辑回归模型(功能模型)与纳入人口统计学、功能状态和医疗合并症的模型(功能增强模型)或包含人口统计学和医疗合并症的模型(人口统计学-合并症模型)进行比较。主要观察指标为3天和30天再入院情况,模型性能的主要衡量指标为c统计量。
共有68395例患者,其中1469例(2.15%)在3天内再入院,7081例(10.35%)在30天内再入院。功能模型在3天和30天的c统计量分别为0.703和0.654。功能模型在3天时优于人口统计学-合并症模型(c统计量差异:0.066 - 0.096),在30天时优于三个人口统计学-合并症模型中的两个(c统计量差异:0.029 - 0.056)。与功能模型相比,功能增强模型在模型性能方面的改善可忽略不计(0.002 - 0.010)。
再入院情况被用作医院绩效的一项指标。脊髓损伤人群中基于功能的再入院模型优于纳入医疗合并症的模型。该人群的再入院风险模型纳入功能状态将有所助益。