基于数据挖掘技术的门诊医疗管理研究-计算机技术专业论文.docx

万方数据 万方数据 Dissertation Submitted to Hebei University of Technology for The Master Degree of Computer Technology Management of outpatient medical research based on data mining technology by Chen Yong Supervisor： Prof. Gu Junhua MAY 2015 摘 要 近几年随着医疗软件开发的深入与完善，医院信息化程度得到了提升，在其信息 系统数据库中有很多潜在的知识与规律，不管是在临床的辅助诊断还是在医院的运营 管理方面，我们可以借助一些数据挖掘的平台或工具挖掘出这些规律。 本文主要通过 SQL Server2012 建立了基于 HIS 系统的数据仓库，再利用数据挖 掘技术，对数据进行分析，从临床辅助诊疗和门诊管理两个方面进行设计与实现。 首先，经过分析门诊管理需求，建立了基于 HIS 系统的数据仓库。 其次，使用 SQL Server2012 数据挖掘工具，利用关联规则方法对门诊药品类医嘱 进行挖掘，发现哪些药品有最强的关联性。在经过临床专家分析挖掘后的数据，得出 有价值的结论。 再次，使用 WEKA 挖掘工具，利用 Apriori 算法对处方数据进行挖掘。看挖掘的 结果对处方管理是否有指导意义。 最后，使用 SQL Server2012 数据挖掘工具中的 Microsoft 神经网络算法对门诊患 者满意度相关数据进行挖掘。查看哪些因素对门诊患者满意度影响较大。 通过分析以上挖掘结果，得出了有实用价值的一些结论，这些结论可以辅助门诊 诊疗，为门诊医疗管理决策提供数据支持。 关键字：关联规则 神经网络 门诊管理 数据挖掘 医嘱信息 I ABSTRACT And perfect along with the development of medical software development in recent years, the hospital informationization level has improved, there are a lot of potential in its information system database knowledge and rules, both in clinical auxiliary diagnosis and operation management in hospitals, we can use some of the data mining platform or tools to dig up these rules. This article mainly created based on the HIS data warehouse by the SQL Server2012, using data mining technology, the analysis of data, from two aspects of clinical auxiliary diagnosis and outpatient service management experiment design and implementation. The first to use the SQL Server2012 data mining tools, doctors advice for outpatient prescription drugs category using the association rules mining, found the diazepam and tartaric acid metoprolol pills have the strongest correlation. After clinical expert analysis mining data, they found the rules of the said after generalization can also form the clinic doctors use manual, auxiliary clinical diagnosis and treatment, to repare for later realize intelligent prescription system. Second use relationship rules mining the data related to prescribing information, use the