Risk factors for hospitalization among community-dwelling primary care older patients - Development and validation of a predictive model
Risk factors for hospitalization among community-dwelling primary care older patients - Development and validation of a predictive model
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DOI：
10.1097/mlr.0b013e3181649426
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发表时间：
2008-07-01
期刊：
影响因子：
3
通讯作者：
Marcantonio, Edward R.
中科院分区：
文献类型：
--
作者：
Inouye, Sharon K.;Zhang, Ying;Marcantonio, Edward R.
研究设计：模型开发和验证。研究设计：模型开发和验证。研究对象：3919名年龄在70岁以上的患者，他们在学术医学中心的初级保健诊所进行了至少一年的跟踪调查。测量：非计划医疗住院的危险因素数据和主要结果来自管理数据。结果：在发展队列中，299例(15%)患者在1年随访中住院。前一年确定了五个独立的危险因素：Deyo-Charlson共病评分=2[调整后的相对风险(RR)=1.8；95%可信区间(0)：1.4-2.2]，既往住院(RR=1.8；95%CI：1.5-2.3)，6次或更多初级保健(RR=1.6；95%CI：1.3-2.0)，年龄=85岁(RR=1.4；未婚(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(0因素)、中(1-2因素)和高危(3因素)组的住院率分别为5%、15%和34%(P<；0.0001)。在验证队列中，328/1987年(17%)住院患者的相应比率分别为6%、16%和36%(P<；0.0001)。结论：基于管理数据的预测模型已被成功地验证用于预测计划外住院。该模型将确定可能需要采取预防干预措施的高危住院患者。
Background: Unplanned hospitalization often represents a costly and hazardous event for the older population.Objectives: To develop and validate a predictive model for unplanned medical hospitalization from administrative data.Research Design: Model development and validation.Subjects: A total of 3919 patients aged >= 70 years who were followed for at least 1 year in primary care clinics of an academic medical center.Measures: Risk factor data and the primary outcome of unplanned medical hospitalization were obtained from administrative data.Results: Of 1932 patients in the development cohort, 299 (15%) were hospitalized during I year follow up. Five independent risk factors were identified in the preceding year: Deyo-Charlson comorbidity score >= 2 [adjusted relative risk (RR) = 1.8; 95% confidence interval (0): 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 >= 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 (>= 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).Conclusions: 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.