Evidence map›Paper›PMID 34755337›Full record

ArticleHealth services research2021

Validation and application of a needs-based segmentation tool for cross-country comparisons.

Lize Duminy, Nirmali Ruth Sivapragasam, David Bruce Matchar, Abhijit Visaria, John Pastor Ansah, Carl Rudolf Blankart, Lukas Schoenenberger

Abstract readValidation Study
In one paragraph

Article in Health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
  4. Article
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.

Lize DuminyInstitute for Health Policy and Health Economics, Bern University of Applied Sciences, Bern, Switzerland.ORCID 0000-0002-9173-5955
Nirmali Ruth SivapragasamProgram in Health Services and Systems Research Service, Duke-NUS Medical School Singapore, Singapore, Singapore.
David Bruce MatcharProgram in Health Services and Systems Research Service, Duke-NUS Medical School Singapore, Singapore, Singapore.ORCID 0000-0003-3020-2108
Abhijit VisariaCentre for Ageing Research and Education, Duke-NUS Medical School Singapore, Singapore, Singapore.
John Pastor AnsahProgram in Health Services and Systems Research Service, Duke-NUS Medical School Singapore, Singapore, Singapore.
Carl Rudolf BlankartSwiss Institute of Translational and Entrepreneurial Medicine, Bern, Switzerland.ORCID 0000-0001-6719-0038
Lukas SchoenenbergerInstitute for Health Policy and Health Economics, Bern University of Applied Sciences, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare countries' health care needs by segmenting populations into a set of needs-based health states. DATA SOURCES: We used seven waves of the Survey of Health, Aging and Retirement in Europe (SHARE) panel survey data. STUDY

designWe developed the Cross-Country Simple Segmentation Tool (CCSST), a validated clinician-administered instrument for categorizing older individuals by distinct, homogeneous health and related social service needs. Using clinical indicators, self-reported physician diagnosis of chronic disease, and performance-based tests conducted during the survey interview, individuals were assigned to 1-5 global impressions (GI) segments and assessed for having any of the four identifiable complicating factors (CFs). We used Cox proportional hazard models to estimate the risk of mortality by segment. First, we show the segmentation cross-sectionally to assess cross-country differences in the fraction of individuals with different levels of medical needs. Second, we compare the differences in the rate at which individuals transition between those levels and death. DATA COLLECTION/EXTRACTION

methodsWe segmented 270,208 observations (from Austria, Belgium, Czech Republic, Denmark, France, Germany, Greece, Israel, Italy, the Netherlands, Poland, Spain, Sweden, and Switzerland) from 96,396 individuals into GI and CF categories. PRINCIPAL

findingsThe CCSST is a valid tool for segmenting populations into needs-based states, showing Switzerland with the lowest fraction of individuals in high medical needs segments, followed by Denmark and Sweden, and Poland with the highest fraction, followed by Italy and Israel. Comparing hazard ratios of transitioning between health states may help identify country-specific areas for analysis of ecological and cultural risk factors.

conclusionsThe CCSST is an innovative tool for aggregate cross-country comparisons of both health needs and transitions between them. A cross-country comparison gives policy makers an effective means of comparing national health system performance and provides targeted guidance on how to identify strategies for curbing the rise of high-need, high-cost patients.

Indexed as

Cross-Cultural ComparisonEuropeFemaleHealth Services Needs and DemandHumansIsraelMalePatient Acceptance of Health CareRisk FactorsSurveys and Questionnairesaccess/demand/utilization of serviceschronic diseasecomparative health systems/international healthgeriatricshealth care organizations and systemsintegrated delivery systemsmodeling: multi-levelsurvey research and questionnaire design

Identifiers

PMID34755337
PMCPMC8579203

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.