Evidence map›Paper›PMID 26454558›Full record

ArticleCanadian journal of psychiatry. Revue canadienne de psychiatrie2015

Validation of a Population-Based Algorithm to Detect Chronic Psychotic Illness.

Paul Kurdyak, Elizabeth Lin, Diane Green, Simone Vigod

Registry-linked trialAbstract readValidation Study
In one paragraph

Article in Canadian journal of psychiatry. Revue canadienne de psychiatrie, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03919760 (Enhancing Evidence-Based Practice for Youth and Emerging Adults With Early Psychosis), which is not on this map. Cited by 115 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
115citing 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.

NCT03919760 nacompletednot on this mapstarted 2020, after this paper: background citation

Enhancing Evidence-Based Practice for Youth and Emerging Adults With Early Psychosis: Implementation and Evaluation in Diverse Service Settings

TypeinterventionalSponsorCentre for Addiction and Mental HealthRan2020 to 2024Enrolled100ConditionsFirst Episode Psychosis, Schizophrenia, Childhood, Psychosis, SchizophreniaArmsNAVIGATE, Treatment as Usual
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Pregnancy Outcomes Among Individuals With Cerebral Palsy: A Population-Based Cohort Study.BJOG : an international journal of obstetrics and gynaecology · 2026
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  12. Incidence of psychotic disorders by birth cohort: a population-based cohort study in Ontario, Canada.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2026
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  19. Pathways to autism diagnosis in adulthood.Journal of neurodevelopmental disorders · 2025
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  20. Antipsychotic treatment adherence and motor vehicle crash among drivers with schizophrenia: a case-crossover study.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2025
    Article

55 more citing papers are in PubMed but not listed here.

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

4 authors.

Paul KurdyakDirector, Health Systems Research, Social and Epidemiological Research, Centre for Addiction and Mental Health, Toronto, Ontario; Lead, Mental Health and Addictions Research Program, Institute for Clinical Evaluative Sciences, Toronto, Ontario; Assistant Professor, Department of Psychiatry and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario.
Elizabeth LinResearch Scientist, Provincial System Support Program, Centre for Addiction and Mental Health, Toronto, Ontario; Adjunct Scientist, Institute for Clinical Evaluative Sciences, Toronto, Ontario; Associate Professor, Department of Psychiatry, University of Toronto, Toronto, Ontario.
Diane GreenAnalyst, Institute for Clinical Evaluative Sciences, Toronto, Ontario.
Simone VigodScientist, Women's College Research Institute, Women's College Hospital, Toronto, Ontario; Assistant Professor, Department of Psychiatry and Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario; Adjunct Scientist, Institute for Clinical Evaluative Sciences, Toronto, Ontario.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo validate algorithms to detect people with chronic psychotic illness in population-based health administrative databases.

methodWe developed 8 algorithms to detect chronic psychotic illness using hospitalization and physician service claims data from administrative health databases in Ontario to identify cases of chronic psychotic illness between 2002 and 2007. Diagnostic data abstracted from the records of 281 randomly selected psychiatric patients from 2 hospitals in Toronto were linked to the administrative data cohort to test sensitivity, specificity, and positive predictive values (PPV) and negative predictive values.

resultsUsing only hospitalization data to capture chronic psychotic illness yielded the highest specificity (range 69.9% to 84.7%) and the highest PPV (range 55.2% to 80.8%). Using physician service claims in addition to hospitalization data to capture cases increased sensitivity (range 90.1% to 98.8%) but decreased specificity (range 31.1% to 68.0%) and PPV (range 38.4% to 71.1%).

conclusionUsing health administrative data to study population-based outcomes for people with chronic psychotic illness is feasible and valid. Researchers can select case identification methods based on whether a more sensitive or more specific definition of chronic psychotic illness is desired.

Indexed as

AlgorithmsAdultChronic DiseaseFemaleHospitalizationHumansMaleMedical RecordsMiddle AgedPsychotic DisordersRegistriesSchizophreniaSensitivity and Specificity

Identifiers

PMID26454558
PMCPMC4542516

What OpenQuestion holds

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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.