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

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 PR...

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Bibliographic Details
Published in:Information systems management 2021-07, Vol.38 (3), p.250-266
Main Author: Ben-Assuli, Ofir
Format: Article
Language:English
Subjects:
Chronic conditions
Chronic illnesses
Chronic obstructive pulmonary disease
Machine learning
Patient admissions
prediction analytics
preferred reporting items for systematic reviews and meta-analyses
Readmission
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Summary: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.
ISSN:1058-0530
1934-8703
DOI:10.1080/10580530.2021.1928341