Evidence map›Paper›PMID 32103728›Full record

ArticleBMC geriatrics2020

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

Jia Loon Chong, Lian Leng Low, David Bruce Matchar, Rahul Malhotra, Kheng Hock Lee, Julian Thumboo, Angelique Wei-Ming Chan

Registry-linked trialAbstract read
In one paragraph

Article in BMC geriatrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07580690 (Integrating Health and Social Service Needs for Frail Elders at Point of Care), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07580690 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Integrating Health and Social Service Needs for Frail Elders at Point of Care: Development and Evaluation of an IT-based Digital Needs-assessment Tool

TypeinterventionalSponsorDuke-NUS Graduate Medical SchoolRan2026 to 2027Enrolled200ConditionsFrail Elderly Patients, Geriatric Syndromes, Frail Older AdultsArmsCore: SST-informed care planning, Additional telephone calls
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jia Loon ChongSignature Program in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.
Lian Leng LowDepartment of Family Medicine and Continuing Care, Singapore General Hospital, 20 College Road, Singapore, 169856, Singapore.
David Bruce MatcharSignature Program in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore. david.matchar@duke-nus.edu.sg.ORCID 0000-0003-3020-2108
Rahul MalhotraSignature Program in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.
Kheng Hock LeeDepartment of Family Medicine and Continuing Care, Singapore General Hospital, 20 College Road, Singapore, 169856, Singapore.
Julian ThumbooSignature Program in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.
Angelique Wei-Ming ChanSignature Program in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, Singapore, 169857, Singapore.

Funding

SingHealth Foundation SHF/HSRAg004/2015
6 · The paper itself

Abstract

backgroundA 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.

methodsA 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.

resultsOf 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.

conclusionsIt 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.

Indexed as

Quality of LifeAgedAged, 80 and overCross-Sectional StudiesDelivery of Health CareHumansLondonMalePoverty AreasProspective StudiesSingaporeAgingCommunity surveyConsensusDecision-makingHealthcare needHealthcare utilizationHealth services researchPopulation healthPopulation segmentationProgram evaluation

Identifiers

PMID32103728
PMCPMC7045405

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.