用隐马尔可夫模型分析再入院情况-充血性心力衰竭的案例

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

Information Systems Management Pub Date : 2020-12-01 DOI:10.1080/10580530.2020.1847362

O. Ben‐Assuli, Tsipi Heart, J. Vest, Roni Ramon-Gonen, N. Shlomo, R. Klempfner

{"title":"用隐马尔可夫模型分析再入院情况-充血性心力衰竭的案例","authors":"O. Ben‐Assuli, Tsipi Heart, J. Vest, Roni Ramon-Gonen, N. Shlomo, R. Klempfner","doi":"10.1080/10580530.2020.1847362","DOIUrl":null,"url":null,"abstract":"ABSTRACT Reducing costly hospital readmissions of patients with Congestive Heart Failure (CHF) is important. We analyzed 4,661 CHF patients (from 2007 to 2017) using Hidden Markov Models in order to profile CHF readmission risk over time. This method proved practical in identifying three patient groups with distinctive characteristics, which might guide physicians in tailoring personalized care to prevent hospital readmission. We thus demonstrate how applying appropriate AI analytics can save costs and improve the quality of care.","PeriodicalId":56289,"journal":{"name":"Information Systems Management","volume":"38 1","pages":"237 - 249"},"PeriodicalIF":3.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10580530.2020.1847362","citationCount":"5","resultStr":"{\"title\":\"Profiling Readmissions Using Hidden Markov Model - the Case of Congestive Heart Failure\",\"authors\":\"O. Ben‐Assuli, Tsipi Heart, J. Vest, Roni Ramon-Gonen, N. Shlomo, R. Klempfner\",\"doi\":\"10.1080/10580530.2020.1847362\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Reducing costly hospital readmissions of patients with Congestive Heart Failure (CHF) is important. We analyzed 4,661 CHF patients (from 2007 to 2017) using Hidden Markov Models in order to profile CHF readmission risk over time. This method proved practical in identifying three patient groups with distinctive characteristics, which might guide physicians in tailoring personalized care to prevent hospital readmission. We thus demonstrate how applying appropriate AI analytics can save costs and improve the quality of care.\",\"PeriodicalId\":56289,\"journal\":{\"name\":\"Information Systems Management\",\"volume\":\"38 1\",\"pages\":\"237 - 249\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/10580530.2020.1847362\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems Management\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/10580530.2020.1847362\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/10580530.2020.1847362","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}

引用次数: 5

摘要

摘要减少充血性心力衰竭（CHF）患者再次入院的费用非常重要。我们使用隐马尔可夫模型分析了4661名CHF患者（从2007年到2017年），以描述一段时间内CHF再次入院的风险。该方法在识别三个具有独特特征的患者群体方面被证明是实用的，这可能会指导医生定制个性化护理，以防止再次入院。因此，我们展示了应用适当的人工智能分析可以节省成本并提高护理质量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Profiling Readmissions Using Hidden Markov Model - the Case of Congestive Heart Failure

ABSTRACT Reducing costly hospital readmissions of patients with Congestive Heart Failure (CHF) is important. We analyzed 4,661 CHF patients (from 2007 to 2017) using Hidden Markov Models in order to profile CHF readmission risk over time. This method proved practical in identifying three patient groups with distinctive characteristics, which might guide physicians in tailoring personalized care to prevent hospital readmission. We thus demonstrate how applying appropriate AI analytics can save costs and improve the quality of care.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

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.