应用PRISMA方法对慢性充血性心力衰竭和慢性阻塞性肺病的预测分析研究综述

IF 3 3区管理学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Systems Management Pub Date : 2021-05-25 DOI:10.1080/10580530.2021.1928341

O. Ben‐Assuli

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引用次数: 3

摘要

慢性疾病再入院是一个普遍存在的现象，是医疗保健部门不断增长的成本的主要贡献者。在这里，PRISMA被用于识别涉及预测CHF和COPD患者再入院的研究，这些研究采用了机器学习技术。PRISMA的输出结果为21篇符合纳入标准的文章。建议包括以前的就诊数据，并在预测这些再入院时跟踪同一患者的多次就诊。

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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Review of Prediction Analytics Studies on Readmission for the Chronic Conditions of CHF and COPD: Utilizing the PRISMA Method

ABSTRACT Hospital readmission for chronic illness is a ubiquitous phenomenon that is a major contributor to the growing costs of the healthcare sector. Here, PRISMA was used to identify studies dealing with predicting readmissions for CHF and COPD patients that implemented machine learning techniques. The PRISMA output yielded 21 articles that met the inclusion criteria. It is recommended to include previous visit data, and track the same patients over multiple visits when predicting these readmissions.

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来源期刊

Information Systems Management 工程技术-计算机：信息系统

CiteScore

14.60

自引率

1.60%

发文量

审稿时长

>12 weeks

期刊介绍： Information Systems Management (ISM) is the on-going exchange of academic research, best practices, and insights based on managerial experience. The journal’s goal is to advance the practice of information systems management through this exchange. To meet this goal, ISM features themed papers examining a particular topic. In addition to themed papers, the journal regularly publishes on the following topics in IS management. Achieving Strategic IT Alignment and Capabilities IT Governance CIO and IT Leadership Roles IT Sourcing Planning and Managing an Enterprise Infrastructure IT Security Selecting and Delivering Application Solutions Portfolio Management Managing Complex IT Projects E-Business Technologies Supporting Knowledge Work The target readership includes both academics and practitioners. Hence, submissions integrating research and practice, and providing implications for both, are encouraged.