Evidence map›Paper›PMID 31594882›Full record

ArticleBMJ open2019

Validation study of health administrative data algorithms to identify individuals experiencing homelessness and estimate population prevalence of homelessness in Ontario, Canada.

Lucie Richard, Stephen W Hwang, Cheryl Forchuk, Rosane Nisenbaum, Kristin Clemens, Kathryn Wiens, Richard Booth, Mahmoud Azimaee, Salimah Z Shariff

Abstract readValidation Study
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 2 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

40 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Physician explanation of Z-coded homelessness in medicaid claims.Health services & outcomes research methodology · 2025
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  14. Dementia care and mortality in people experiencing homelessness: A matched cohort study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
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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

9 authors.

Lucie RichardICES Western, London, Ontario, Canada lucie.richard@ices.on.ca.ORCID 0000-0001-6577-5067
Stephen W HwangSt Michael's Hospital, Toronto, Ontario, Canada.
Cheryl ForchukArthur Labatt Family School of Nursing, Western University, London, Ontario, Canada.
Rosane NisenbaumSt Michael's Hospital, Toronto, Ontario, Canada.
Kristin ClemensSchulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Kathryn WiensDalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
Richard BoothArthur Labatt Family School of Nursing, Western University, London, Ontario, Canada.
Mahmoud AzimaeeICES, Toronto, Ontario, Canada.
Salimah Z ShariffICES Western, London, Ontario, Canada.

Funding

CIHR HOA-80066CIHR MOP-86765
6 · The paper itself

Abstract

objectivesTo validate case ascertainment algorithms for identifying individuals experiencing homelessness in health administrative databases between 2007 and 2014; and to estimate homelessness prevalence trends in Ontario, Canada, between 2007 and 2016.

designA population-based retrospective validation study.

settingOntario, Canada, from 2007 to 2014 (validation) and 2007 to 2016 (estimation).

participantsOur reference standard was the known housing status of a longitudinal cohort of housed (n=137 200) and homeless or vulnerably housed (n=686) individuals. Two reference standard definitions of homelessness were adopted: the housing episode and the annual housing experience (any homelessness within a calendar year).

main outcome measuresSensitivity, specificity, positive and negative predictive values and positive likelihood ratios of 30 case ascertainment algorithms for detecting homelessness using up to eight health service databases.

resultsSensitivity estimates ranged from 10.8% to 28.9% (housing episode definition) and 18.5% to 35.6% (annual housing experience definition). Specificities exceeded 99% and positive likelihood ratios were high using both definitions. The most optimal algorithm estimates that 59 974 (95% CI 55 231 to 65 208) Ontarians (0.53% of the adult population) experienced homelessness in 2016, a 67.3% increase from 2007.

conclusionsIn Ontario, case ascertainment algorithms for identifying homelessness had low sensitivity but very high specificity and positive likelihood ratio. The use of health administrative databases may offer opportunities to track individuals experiencing homelessness over time and inform efforts to improve housing and health status in this vulnerable population.

Indexed as

Health Status DisparitiesHousingAdultAlgorithmsEmigrants and ImmigrantsFemaleHealth ServicesHealth Services ResearchHumansIll-Housed PersonsLongitudinal StudiesMaleMiddle AgedNeeds AssessmentOntarioPrevalencehealth services researchHomelessnessvalidation

Identifiers

PMID31594882
PMCPMC6797366

What OpenQuestion holds

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LicenceCC BY-NC
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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.