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Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community

BACKGROUND: A rapidly ageing population with increasing prevalence of chronic disease presents policymakers the urgent task of tailoring healthcare services to optimally meet changing needs. While healthcare needs-based segmentation is a promising approach to efficiently assessing and responding to...

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Autores principales: Chong, Jia Loon, Low, Lian Leng, Matchar, David Bruce, Malhotra, Rahul, Lee, Kheng Hock, Thumboo, Julian, Chan, Angelique Wei-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7045405/
https://www.ncbi.nlm.nih.gov/pubmed/32103728
http://dx.doi.org/10.1186/s12877-020-1480-9
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author Chong, Jia Loon
Low, Lian Leng
Matchar, David Bruce
Malhotra, Rahul
Lee, Kheng Hock
Thumboo, Julian
Chan, Angelique Wei-Ming
author_facet Chong, Jia Loon
Low, Lian Leng
Matchar, David Bruce
Malhotra, Rahul
Lee, Kheng Hock
Thumboo, Julian
Chan, Angelique Wei-Ming
author_sort Chong, Jia Loon
collection PubMed
description BACKGROUND: A rapidly ageing population with increasing prevalence of chronic disease presents policymakers the urgent task of tailoring healthcare services to optimally meet changing needs. While healthcare needs-based segmentation is a promising approach to efficiently assessing and responding to healthcare needs at the population level, it is not clear how available schemes perform in the context of community-based surveys administered by non-medically trained personnel. The aim of this prospective cohort, community setting study is to evaluate 4 segmentation schemes in terms of practicality and predictive validity for future health outcomes and service utilization. METHODS: A cohort was identified from a cross-sectional health and social characteristics survey of Singapore public rental housing residents aged 60 years and above. Baseline survey data was used to assign individuals into segments as defined by 4 predefined population segmentation schemes developed in Singapore, Delaware, Lombardy and North-West London. From electronic data records, mortality, hospital admissions, emergency department visits, and specialist outpatient clinic visits were assessed for 180 days after baseline segment assignment and compared to segment membership for each segmentation scheme. RESULTS: Of 1324 residents contacted, 928 agreed to participate in the survey (70% response). All subjects could be assigned an exclusive segment for each segmentation scheme. Individuals in more severe segments tended to have lower quality of life as assessed by the EQ-5D Index for health utility. All population segmentation schemes were observed to exhibit an ability to differentiate different levels of mortality and healthcare utilization. CONCLUSIONS: It is practical to assign individuals to healthcare needs-based population segments through community surveys by non-medically trained personnel. The resulting segments for all 4 schemes evaluated in this way have an ability to predict health outcomes and utilization over the medium term (180 days), with significant overlap for some segments. Healthcare needs-based segmentation schemes which are designed to guide action hold particular promise for promoting efficient allocation of services to meet the needs of salient population groups. Further evaluation is needed to determine if these schemes also predict responsiveness to interventions to meet needs implied by segment membership.
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spelling pubmed-70454052020-03-03 Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community Chong, Jia Loon Low, Lian Leng Matchar, David Bruce Malhotra, Rahul Lee, Kheng Hock Thumboo, Julian Chan, Angelique Wei-Ming BMC Geriatr Research Article BACKGROUND: A rapidly ageing population with increasing prevalence of chronic disease presents policymakers the urgent task of tailoring healthcare services to optimally meet changing needs. While healthcare needs-based segmentation is a promising approach to efficiently assessing and responding to healthcare needs at the population level, it is not clear how available schemes perform in the context of community-based surveys administered by non-medically trained personnel. The aim of this prospective cohort, community setting study is to evaluate 4 segmentation schemes in terms of practicality and predictive validity for future health outcomes and service utilization. METHODS: A cohort was identified from a cross-sectional health and social characteristics survey of Singapore public rental housing residents aged 60 years and above. Baseline survey data was used to assign individuals into segments as defined by 4 predefined population segmentation schemes developed in Singapore, Delaware, Lombardy and North-West London. From electronic data records, mortality, hospital admissions, emergency department visits, and specialist outpatient clinic visits were assessed for 180 days after baseline segment assignment and compared to segment membership for each segmentation scheme. RESULTS: Of 1324 residents contacted, 928 agreed to participate in the survey (70% response). All subjects could be assigned an exclusive segment for each segmentation scheme. Individuals in more severe segments tended to have lower quality of life as assessed by the EQ-5D Index for health utility. All population segmentation schemes were observed to exhibit an ability to differentiate different levels of mortality and healthcare utilization. CONCLUSIONS: It is practical to assign individuals to healthcare needs-based population segments through community surveys by non-medically trained personnel. The resulting segments for all 4 schemes evaluated in this way have an ability to predict health outcomes and utilization over the medium term (180 days), with significant overlap for some segments. Healthcare needs-based segmentation schemes which are designed to guide action hold particular promise for promoting efficient allocation of services to meet the needs of salient population groups. Further evaluation is needed to determine if these schemes also predict responsiveness to interventions to meet needs implied by segment membership. BioMed Central 2020-02-27 /pmc/articles/PMC7045405/ /pubmed/32103728 http://dx.doi.org/10.1186/s12877-020-1480-9 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Chong, Jia Loon
Low, Lian Leng
Matchar, David Bruce
Malhotra, Rahul
Lee, Kheng Hock
Thumboo, Julian
Chan, Angelique Wei-Ming
Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title_full Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title_fullStr Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title_full_unstemmed Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title_short Do healthcare needs-based population segments predict outcomes among the elderly? Findings from a prospective cohort study in an urbanized low-income community
title_sort do healthcare needs-based population segments predict outcomes among the elderly? findings from a prospective cohort study in an urbanized low-income community
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7045405/
https://www.ncbi.nlm.nih.gov/pubmed/32103728
http://dx.doi.org/10.1186/s12877-020-1480-9
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