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目的 用数据挖掘技术对患者病情危重度进行分类和评价。方法 用急性上呼吸道感染病例的病案首页数据和决策树分析法 ,确定分类标准、分类变量和决策树的生长及剪枝规则 ,建立病情危重度分类评价模型。结果 上呼吸道感染患者的病情划分为 4个等级 ,每个等级对应一个量化的危重度分值 ;医院收治患者的整体病情用危重度指数表示。经新样本考核 ,危重度等级和危重度指数对治疗结果、医疗资源消耗有一定预测能力 ,且随医院规模的增大而提高。结论 评价分析结果能够反映患者和医院收治病人的病情 ,可为医疗质量评价和医院费用补偿提供重要统计学依据。
Objective To classify and evaluate the severity of patients’ condition by data mining. Methods Acute upper respiratory tract infection cases by the case data and decision tree analysis method to determine the classification criteria, classification variables and decision tree growth and pruning rules, the establishment of critical illness classification and evaluation model. Results The patients with upper respiratory tract infection were divided into four grades, each grade corresponding to a quantified criticality score. The overall condition of the patients admitted to the hospital was indicated by the criticality index. The new sample assessment, the critical level and the severity index of the treatment outcome, medical resources consumption have a certain ability to predict, and with the size of the hospital increased. Conclusion The results of evaluation and analysis can reflect the patient’s and hospital’s treatment of patients’ condition, which can provide important statistical basis for medical quality evaluation and compensation of hospital expenses.