Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12913-019-4769-7
DC FieldValue
dc.titleThe heterogeneous health state profiles of high-risk healthcare utilizers and their longitudinal hospital readmission and mortality patterns
dc.contributor.authorNg, S.C.W.
dc.contributor.authorKwan, Y.H.
dc.contributor.authorYan, S.
dc.contributor.authorTan, C.S.
dc.contributor.authorLow, L.L.
dc.date.accessioned2021-12-09T02:56:43Z
dc.date.available2021-12-09T02:56:43Z
dc.date.issued2019
dc.identifier.citationNg, S.C.W., Kwan, Y.H., Yan, S., Tan, C.S., Low, L.L. (2019). The heterogeneous health state profiles of high-risk healthcare utilizers and their longitudinal hospital readmission and mortality patterns. BMC Health Services Research 19 (1) : 931. ScholarBank@NUS Repository. https://doi.org/10.1186/s12913-019-4769-7
dc.identifier.issn1472-6963
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/209880
dc.description.abstractBackground: High-risk patients are most vulnerable during transitions of care. Due to the high burden of resource allocation for such patients, we propose that segmentation of this heterogeneous population into distinct subgroups will enable improved healthcare resource planning. In this study, we segmented a high-risk population with the aim to identify and characterize a patient subgroup with the highest 30-day and 90-day hospital readmission and mortality. Methods: We extracted data from our transitional care program (TCP), a Hospital-to-Home program launched by the Singapore Ministry of Health, from June to November 2018. Latent class analysis (LCA) was used to determine the optimal number and characteristics of latent subgroups, assessed based on model fit and clinical interpretability. Regression analysis was performed to assess the association of class membership on 30- and 90-day all-cause readmission and mortality. Results: Among 752 patients, a 3-class best fit model was selected: Class 1 "Frail, cognitively impaired and physically dependent", Class 2 "Pre-frail, but largely physically independent" and Class 3 "Physically independent". The 3 classes have distinct demographics, medical and socioeconomic characteristics (p < 0.05), 30- and 90-day readmission (p < 0.05) and mortality (p < 0.01). Class 1 patients have the highest age-adjusted 90-day readmission (OR = 2.04, 95%CI: 1.21-3.46, p = 0.008), 30- (OR = 6.92, 95%CI: 1.76-27.21, p = 0.006) and 90-day mortality (OR = 11.51, 95%CI: 4.57-29.02, p < 0.001). Conclusions: We identified a subgroup with the highest readmission and mortality risk amongst high-risk patients. We also found a lack of interventions in our TCP that specifically addresses increased frailty and poor cognition, which are prominent features in this subgroup. These findings will help to inform future program modifications and strengthen existing transitional healthcare structures currently utilized in this patient cohort. © 2019 The Author(s).
dc.publisherBioMed Central Ltd.
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScopus OA2019
dc.subjectHigh-risk healthcare utilizers
dc.subjectHospital readmissions
dc.subjectIntegrated care
dc.subjectLatent class analysis
dc.subjectMortality
dc.subjectTransitional care program
dc.typeArticle
dc.contributor.departmentSAW SWEE HOCK SCHOOL OF PUBLIC HEALTH
dc.description.doi10.1186/s12913-019-4769-7
dc.description.sourcetitleBMC Health Services Research
dc.description.volume19
dc.description.issue1
dc.description.page931
Appears in Collections:Elements
Staff Publications

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_s12913-019-4769-7.pdf534.31 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons