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Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis
INTRODUCTION: High users of hospital services require targeted healthcare services planning for effective resource allocation due to their high costs. This study aims to segmentize the population in the “Ageing In Place-Community Care Team” (AIP-CCT), a programme for complex patients with high inpat...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10335687/ https://www.ncbi.nlm.nih.gov/pubmed/37432942 http://dx.doi.org/10.1371/journal.pone.0288441 |
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author | Ginting, Mimaika Luluina Ang, Yan Hoon Ho, Soon Hoe Sum, Grace Wong, Chek Hooi |
author_facet | Ginting, Mimaika Luluina Ang, Yan Hoon Ho, Soon Hoe Sum, Grace Wong, Chek Hooi |
author_sort | Ginting, Mimaika Luluina |
collection | PubMed |
description | INTRODUCTION: High users of hospital services require targeted healthcare services planning for effective resource allocation due to their high costs. This study aims to segmentize the population in the “Ageing In Place-Community Care Team” (AIP-CCT), a programme for complex patients with high inpatient service use, and examine the association of segment membership and healthcare utilisation and mortality. METHODS: We analysed 1,012 patients enrolled between June 2016 and February 2017. To identify patient segments, a cluster analysis was performed based on medical complexity and psychosocial needs. Next, multivariable negative binomial regression was performed using patient segments as the predictor, with healthcare and programme utilisation over the 180-day follow-up as outcomes. Multivariate cox proportional hazard regression was applied to assess the time to first hospital admission and mortality between segments within the 180-day follow-up. All models were adjusted for age, gender, ethnicity, ward class, and baseline healthcare utilisation. RESULTS: Three distinct segments were identified (Segment 1 (n = 236), Segment 2 (n = 331), and Segment 3 (n = 445)). Medical, functional, and psychosocial needs of individuals were significantly different between segments (p-value<0.001). The rates of hospitalisation in Segments 1 (IRR = 1.63, 95%CI:1.3–2.1) and 2 (IRR = 2.11, 95%CI:1.7–2.6) were significantly higher than in Segment 3 on follow-up. Similarly, both Segments 1 (IRR = 1.76, 95%CI:1.6–2.0) and 2 (IRR = 1.25, 95%CI:1.1–1.4) had higher rates of programme utilisation compared to Segment 3. Patients in Segments 1 (HR = 2.48, 95%CI:1.5–4.1) and 2 (HR = 2.25, 95%CI:1.3–3.6) also had higher mortality on follow-up. CONCLUSIONS: This study provided a data-based approach to understanding healthcare needs among complex patients with high inpatient services utilisation. Resources and interventions can be tailored according to the differences in needs among segments, to facilitate better allocation. |
format | Online Article Text |
id | pubmed-10335687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-103356872023-07-12 Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis Ginting, Mimaika Luluina Ang, Yan Hoon Ho, Soon Hoe Sum, Grace Wong, Chek Hooi PLoS One Research Article INTRODUCTION: High users of hospital services require targeted healthcare services planning for effective resource allocation due to their high costs. This study aims to segmentize the population in the “Ageing In Place-Community Care Team” (AIP-CCT), a programme for complex patients with high inpatient service use, and examine the association of segment membership and healthcare utilisation and mortality. METHODS: We analysed 1,012 patients enrolled between June 2016 and February 2017. To identify patient segments, a cluster analysis was performed based on medical complexity and psychosocial needs. Next, multivariable negative binomial regression was performed using patient segments as the predictor, with healthcare and programme utilisation over the 180-day follow-up as outcomes. Multivariate cox proportional hazard regression was applied to assess the time to first hospital admission and mortality between segments within the 180-day follow-up. All models were adjusted for age, gender, ethnicity, ward class, and baseline healthcare utilisation. RESULTS: Three distinct segments were identified (Segment 1 (n = 236), Segment 2 (n = 331), and Segment 3 (n = 445)). Medical, functional, and psychosocial needs of individuals were significantly different between segments (p-value<0.001). The rates of hospitalisation in Segments 1 (IRR = 1.63, 95%CI:1.3–2.1) and 2 (IRR = 2.11, 95%CI:1.7–2.6) were significantly higher than in Segment 3 on follow-up. Similarly, both Segments 1 (IRR = 1.76, 95%CI:1.6–2.0) and 2 (IRR = 1.25, 95%CI:1.1–1.4) had higher rates of programme utilisation compared to Segment 3. Patients in Segments 1 (HR = 2.48, 95%CI:1.5–4.1) and 2 (HR = 2.25, 95%CI:1.3–3.6) also had higher mortality on follow-up. CONCLUSIONS: This study provided a data-based approach to understanding healthcare needs among complex patients with high inpatient services utilisation. Resources and interventions can be tailored according to the differences in needs among segments, to facilitate better allocation. Public Library of Science 2023-07-11 /pmc/articles/PMC10335687/ /pubmed/37432942 http://dx.doi.org/10.1371/journal.pone.0288441 Text en © 2023 Ginting et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ginting, Mimaika Luluina Ang, Yan Hoon Ho, Soon Hoe Sum, Grace Wong, Chek Hooi Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title | Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title_full | Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title_fullStr | Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title_full_unstemmed | Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title_short | Understanding the characteristics of high users of hospital services in Singapore and their associations with healthcare utilisation and mortality: A cluster analysis |
title_sort | understanding the characteristics of high users of hospital services in singapore and their associations with healthcare utilisation and mortality: a cluster analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10335687/ https://www.ncbi.nlm.nih.gov/pubmed/37432942 http://dx.doi.org/10.1371/journal.pone.0288441 |
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