Inouye Sharon K, Zhang Ying, Jones Richard N, Shi Peilin, Cupples L Adrienne, Calderon Harold N, Marcantonio Edward R
Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Med Care. 2008 Jul;46(7):726-31. doi: 10.1097/MLR.0b013e3181649426.
Unplanned hospitalization often represents a costly and hazardous event for the older population.
To develop and validate a predictive model for unplanned medical hospitalization from administrative data.
Model development and validation.
A total of 3919 patients aged > or =70 years who were followed for at least 1 year in primary care clinics of an academic medical center.
Risk factor data and the primary outcome of unplanned medical hospitalization were obtained from administrative data.
Of 1932 patients in the development cohort, 299 (15%) were hospitalized during 1 year follow up. Five independent risk factors were identified in the preceding year: Deyo-Charlson comorbidity score > or =2 [adjusted relative risk (RR) = 1.8; 95% confidence interval (CI): 1.4-2.2], any prior hospitalization (RR = 1.8; 95% CI: 1.5-2.3), 6 or more primary care visits (RR = 1.6; 95% CI: 1.3-2.0), age > or =85 years (RR = 1.4; 95% CI: 1.1-1.7), and unmarried status (RR = 1.4; 95% CI: 1.1-1.7). A risk stratification system was created by adding 1 point for each factor present. Rates of hospitalization for the low- (0 factor), intermediate- (1-2 factors), and high-risk (> or =3 factors) groups were 5%, 15%, and 34% (P < 0.0001). The corresponding rates in the validation cohort, where 328/1987 (17%) were hospitalized, were 6%, 16%, and 36% (P < 0.0001).
A predictive model based on administrative data has been successfully validated for prediction of unplanned hospitalization. This model will identify patients at high risk for hospitalization who may be candidates for preventive interventions.
计划外住院对于老年人群而言往往是代价高昂且危险的事件。
利用管理数据开发并验证计划外医疗住院的预测模型。
模型开发与验证。
在一所学术医疗中心的初级保健诊所中，共有3919名年龄≥70岁且随访至少1年的患者。
危险因素数据以及计划外医疗住院的主要结局均从管理数据中获取。
在开发队列的患者中，有1932名，其中299名（1５％）在1年随访期间住院。在前一年中确定了五个独立危险因素：Deyo-Charlson合并症评分≥2[校正相对危险度（RR）=1.8；95％置信区间（CI）：1.4 - 2.2]，既往曾住院（RR = 1.8；95％CI: 1.5 - 2.3），6次及以上初级保健就诊（RR = 1.6；95％CI: 1.3 - 2.0），年龄≥85岁（RR = 1.4；95％CI: 1.1 - 1.7），以及未婚状态（RR = 1.4；95％CI: 1.1 - 1.7）。通过为每个存在的因素加1分来创建风险分层系统。低风险（0个因素）、中风险（1 - 2个因素）和高风险（≥3个因素）组的住院率分别为5％、15％和34％（P < 0.0001）。在验证队列中，相应的住院率分别为6％、16％和36％（P < 0.0001），其中328/1987（17％）的患者住院。
基于管理数据的预测模型已成功验证用于预测计划外住院。该模型将识别出可能适合进行预防性干预的高住院风险患者。
