Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/93313
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGatt, Michelle Louise-
dc.contributor.authorCassar, Maria-
dc.contributor.authorButtigieg, Sandra C.-
dc.date.accessioned2022-04-11T07:47:51Z-
dc.date.available2022-04-11T07:47:51Z-
dc.date.issued2022-
dc.identifier.citationGatt, M. L., Cassar, M., & Buttigieg, S. C. (2022). A review of literature on risk prediction tools for hospital readmissions in older adults. Journal of Health Organization and Management. DOI 10.1108/JHOM-11-2020-0450en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/93313-
dc.description.abstractPurpose – The purpose of this paper is to identify and analyse the readmission risk prediction tools reported in the literature and their benefits when it comes to healthcare organisations and management.en_GB
dc.description.abstractDesign/methodology/approach – Readmission risk prediction is a growing topic of interest with the aim of identifying patients in particular those suffering from chronic diseases such as congestive heart failure, chronic obstructive pulmonary disease and diabetes, who are at risk of readmission. Several models have been developed with different levels of predictive ability. A structured and extensive literature search of several databases was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis strategy, and this yielded a total of 48,984 records.en_GB
dc.description.abstractFindings – Forty-three articles were selected for full-text and extensive review after following the screening process and according to the eligibility criteria. About 34 unique readmission risk prediction models were identified, in which their predictive ability ranged from poor to good (c statistic 0.5–0.86). Readmission rates ranged between 3.1 and 74.1% depending on the risk category. This review shows that readmission risk prediction is a complex process and is still relatively new as a concept and poorly understood. It confirms that readmission prediction models hold significant accuracy at identifying patients at higher risk for such an event within specific context.en_GB
dc.description.abstractResearch limitations/implications – Since most prediction models were developed for specific populations, conditions or hospital settings, the generalisability and transferability of the predictions across wider or other contexts may be difficult to achieve. Therefore, the value of prediction models remains limited to hospital management. Future research is indicated in this regarden_GB
dc.description.abstractOriginality/value – This review is the first to cover readmission risk prediction tools that have been published in the literature since 2011, thereby providing an assessment of the relevance of this crucial KPI to health organisations and managers.en_GB
dc.language.isoenen_GB
dc.publisherEmerald Publishing Limiteden_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectCongestive heart failureen_GB
dc.subjectComorbidityen_GB
dc.subjectRisk managementen_GB
dc.subjectHospitals -- Admission and dischargeen_GB
dc.subjectHospital utilization -- Length of stayen_GB
dc.subjectChronic diseasesen_GB
dc.titleA review of literature on risk prediction tools for hospital readmissions in older adultsen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1108/JHOM-11-2020-0450-
dc.publication.titleJournal of Health Organization and Managementen_GB
Appears in Collections:Scholarly Works - FacHScHSM

Files in This Item:
File Description SizeFormat 
A_review_of_literature_on_risk_prediction_tools_for_hospital_readmissions_in_older_adults(2022).pdf
  Restricted Access
765.43 kBAdobe PDFView/Open Request a copy


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.