University of Ottawa, Ottawa, Ontario, Canada; Ottawa Hospital Research Institute, 1053 Carling Ave, Ottawa, Ontario K1Y 4E9, Canada; ICES@uOttawa, Ottawa, Ontario, Canada.
J Clin Epidemiol. 2014 Sep;67(9):1025-34. doi: 10.1016/j.jclinepi.2014.05.003. Epub 2014 Jun 25.
Prognostication is difficult in a diverse patient population or when outcomes depend on multiple factors. This study derived and internally validated a model to predict risk of death from any cause within 1 year of admission to hospital.
The study included all adult Ontarians admitted to nonpsychiatric hospital services in 2011 (n = 640,022) and deterministically linked administrative data to identify 20 patient and admission factors. A split-sample approach was used to derive and internally validate the model.
A total of 75,082 people (11.7%) died within 1 year of admission to hospital. The final model included one dozen patient factors (age, sex, living status, comorbidities, home oxygen status, and number of emergency room visits and hospital admissions by ambulance in previous year) and hospitalization factors (admission service and urgency, admission to intensive care unit, whether current hospitalization was a readmission, and admission diagnostic risk score). The model in the validation cohort was highly discriminative (c-statistic 92.3), well calibrated, and used to create the Hospital-patient One-year Mortality Risk score that accurately predicted 1-year risk of death.
Routinely collected administrative data can be used to accurately predict 1-year death risk in adults admitted to nonpsychiatric hospital services.
在患者群体多样化或结果取决于多个因素的情况下,预后评估较为困难。本研究旨在建立并内部验证一种模型,以预测患者住院后 1 年内任何原因导致的死亡风险。
本研究纳入了 2011 年所有在安大略省非精神科医院接受治疗的成年患者(n=640022),并通过确定性链接行政数据确定了 20 个患者和入院因素。采用拆分样本的方法来推导和内部验证模型。
共有 75082 人(11.7%)在住院后 1 年内死亡。最终模型纳入了 12 个患者因素(年龄、性别、居住状况、合并症、家庭氧气状况以及前一年的急诊就诊次数和救护车入院次数)和住院因素(入院科室和紧急程度、入住重症监护病房、当前住院是否为再次入院以及入院诊断风险评分)。验证队列中的模型具有较高的判别能力(c 统计量为 92.3)、良好的校准能力,并据此创建了医院-患者 1 年死亡率风险评分,能够准确预测 1 年的死亡风险。
常规收集的行政数据可用于准确预测非精神科医院收治的成年患者 1 年内的死亡风险。