住院病人欠费预测模型研究

针对住院病人欠费现象,以医院信息系统历年数据为基础建立数据仓库,对欠逃费病人数据进行多角度、多层次分析,采用Bayes算法和关联等规则,对欠逃费影响因素之间的关联关系进行量化分析,以欠逃费行为潜在的规律及其关键影响因素来建立数学预测模型;并以此预测和分析现有住院患者欠逃费的可能性,将分析结果提供给医院管理人员,加强关注欠逃费概率高的在院病人,以规避潜在欠逃费行为.同时,通过分析欠逃费病人发生的原因,指导医院对相关病种、科室的管理,提升医疗质量和管理水平,为医院科学管理和决策提供辅助支持.

The Research of Inpatient Delinquency Forecasting Model

When hospital insists on the principle of public interest, it should search for the good balance between patient satisfaction and self development, and transform the business data to the information scheme required by hospital decision. Aiming at a lot of inpatients arrears every year, it sets up data warehouse based on data of hospital information system over the years, and makes multilevel analysis and data mining by the strong analysis function of business intelligence technology on data of inpatient arrears, and then it should utilize Bayes algorithm and associative rules to make quantitative methods on associative relationship among the influence factors of arrears, as well as build up the mathematical forecast model by the potential rule and key influence factors of arrears; based on this, it makes predication and analysis on the possibility of existing inpatients arrears, and provides the analysis result to hospital administrator and pays more attention to inpatients with high probability of arrears, in order to avoid such behavior. Meanwhile, by analyzing the reason of inpatient arrears, it should instruct hospital the relevant entities and department management, to enhance the medical quality and management level, and provide the auxiliary support for hospital scientific management and decision.