Evidence map›Paper›PMID 31707981›Full record

ArticleInternational journal for equity in health2019

Defining 'actionable' high- costhealth care use: results using the Canadian Institute for Health Information population grouping methodology.

Maureen Anderson, Crawford W Revie, Henrik Stryhn, Cordell Neudorf, Yvonne Rosehart, Wenbin Li, Meriç Osman, David L Buckeridge, Laura C Rosella, Walter P Wodchis

Abstract read
In one paragraph

Article in International journal for equity in health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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.

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

13 citing papers in PubMed.

  1. Observational
  2. The Patient Reported Inventory of Self-Management of Chronic Conditions (PRISM-CC): testing for bias across patient characteristics and languages.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

10 authors.

Maureen AndersonDepartment of Health Management, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada. mfanderson@upei.ca.ORCID 0000-0002-6487-2620
Crawford W RevieDepartment of Health Management, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada.
Henrik StryhnDepartment of Health Management, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada.
Cordell NeudorfDepartment of Community Health and Epidemiology, College of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Yvonne RosehartCanadian Institute for Health Information, Ottawa, Ontario, Canada.
Wenbin LiSaskatchewan Health Quality Council, Saskatoon, Saskatchewan, Canada.
Meriç OsmanSaskatchewan Health Quality Council, Saskatoon, Saskatchewan, Canada.
David L BuckeridgeDepartment of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada.
Laura C RosellaInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Walter P WodchisInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.

Funding

Canadian Institute for Health Research 2015-04-30
6 · The paper itself

Abstract

backgroundA small proportion of the population consumes the majority of health care resources. High-cost health care users are a heterogeneous group. We aim to segment a provincial population into relevant homogenous sub-groups to provide actionable information on risk factors associated with high-cost health care use within sub-populations.

methodsThe Canadian Institute for Health Information (CIHI) Population Grouping methodology was used to define mutually exclusive and clinically relevant health profile sub-groups. High-cost users (> = 90th percentile of health care spending) were defined within each sub-group. Univariate analyses explored demographic, socio-economic status, health status and health care utilization variables associated with high-cost use. Multivariable logistic regression models were constructed for the costliest health profile groups.

resultsFrom 2015 to 2017, 1,175,147 individuals were identified for study. High-cost users consumed 41% of total health care resources. Average annual health care spending for individuals not high-cost were $642; high-cost users were $16,316. The costliest health profile groups were 'long-term care', 'palliative', 'major acute', 'major chronic', 'major cancer', 'major newborn', 'major mental health' and 'moderate chronic'. Both 'major acute' and 'major cancer' health profile groups were largely explained by measures of health care utilization and multi-morbidity. In the remaining costliest health profile groups modelled, 'major chronic', 'moderate chronic', 'major newborn' and 'other mental health', a measure of socio-economic status, low neighbourhood income, was statistically significantly associated with high-cost use.

interpretationModel results point to specific, actionable information within clinically meaningful subgroups to reduce high-cost health care use. Health equity, specifically low socio-economic status, was statistically significantly associated with high-cost use in the majority of health profile sub-groups. Population segmentation methods, and more specifically, the CIHI Population Grouping Methodology, provide specificity to high-cost health care use; informing interventions aimed at reducing health care costs and improving population health.

Indexed as

AdolescentAdultAgedAged, 80 and overCanadaDemographyFemaleHealth Care CostsHealth StatusHumansMaleMiddle AgedPatient Acceptance of Health CareRisk FactorsSocioeconomic FactorsYoung Adult

Identifiers

PMID31707981
PMCPMC6842471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.