Health Information Management and Patient Profile Estimation Using Data Mining Classification Techniques

IF 1 Q4 HEALTH POLICY & SERVICES
Duygu Karabulut Şimşek, Filiz Ersöz
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引用次数: 0

Abstract

Nowadays, the rapid advancement of technological developments consists of complex and large databases. Software programmes are needed because it can be very difficult to process the complex data. The aim of the study is to reveal the patient profile by data mining of the hospital information system and to help make strategic decisions according to patient profile analysis in the establishment of a new hospital or additional hospital departments in the future. The application of data mining in the health sector provides the sector with a faster, reliable and different perspective on decision-making by reaching the desired data. For this purpose, data mining decision tree algorithms were applied, and patient profile estimations were found by using the data of patients receiving service from a private health institution with hospitals in different settlements. By categorising the characteristics of the individuals receiving service and the branches from which they receive service, it was revealed with which variables the patient profile is related. It is thought that determining patient profile will help to follow a more accurate path in the stage of meeting their demands.
使用数据挖掘分类技术的健康信息管理和患者概况估计
如今,快速发展的技术发展构成了复杂而庞大的数据库。软件程序是必需的,因为处理复杂的数据非常困难。本研究的目的是透过医院资讯系统的资料挖掘,揭示病患资料,并在未来新设医院或增设医院科室时,根据病患资料分析,协助制定策略决策。数据挖掘在卫生部门的应用通过获得所需的数据,为该部门提供了更快、可靠和不同的决策视角。为此,应用数据挖掘决策树算法,利用在不同居民点的私立医疗机构接受服务的患者数据进行患者概况估计。通过对接受服务的个人的特征和他们接受服务的分支进行分类,揭示了患者概况与哪些变量相关。人们认为,确定患者的个人资料将有助于在满足其需求的阶段遵循更准确的路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Health Management
Journal of Health Management HEALTH POLICY & SERVICES-
CiteScore
3.40
自引率
0.00%
发文量
84
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