Steen P M, Brewster A C, Bradbury R C, Estabrook E, Young J A
Applied Research Division, MediQual Systems, Inc., Worcester, MA.
Inquiry. 1993 Summer;30(2):128-41.
This paper evaluates a new method for assessing hospital admission severity of illness based on disease-specific models (logistic regression) of the probability of in-hospital mortality. Results for the 26 disease groups in MDC 4--Diseases of the Respiratory System, MDC 5--Diseases of the Circulatory System, and MDC 6--Diseases of the Digestive System are presented using data on all 1991 admissions from 111 hospitals throughout the United States. These disease models are empirically derived using clinical findings from laboratory, radiology, pathology, diagnostic procedures, patient history and physical exam, as well as patient age and sex. Each predictive algorithm is presented, and the strong predictive performance of these models is indicated by the average C statistic of .870. A predicted probability of death is calculated for each hospital patient in the study sample, and these probabilities comprise a continuous variable that indicates admission severity of illness.
本文评估了一种基于特定疾病模型（逻辑回归）的住院死亡率概率来评估医院入院疾病严重程度的新方法。使用来自美国各地111家医院的1991例所有入院患者的数据，展示了医疗诊断相关组（MDC）4——呼吸系统疾病、MDC 5——循环系统疾病和MDC 6——消化系统疾病中26个疾病组的结果。这些疾病模型是根据实验室、放射学、病理学、诊断程序、患者病史和体格检查的临床发现以及患者年龄和性别通过经验得出的。文中给出了每种预测算法，这些模型的强大预测性能通过平均C统计量0.870得以体现。为研究样本中的每位住院患者计算了预测死亡概率，这些概率构成了一个表明入院疾病严重程度的连续变量。
