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Identification of homelessness using health administrative data in Ontario, Canada following a national coding mandate: a validation study.
Richard, Lucie; Carter, Brooke; Nisenbaum, Rosane; Liu, Michael; Hwang, Stephen W.
Afiliación
  • Richard L; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, Ontario, Canada. Electronic address: lucie.richard@unityhealth.to.
  • Carter B; ICES Western, London Health Sciences Research Institute, London, Ontario, Canada.
  • Nisenbaum R; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, Ontario, Canada.
  • Liu M; Harvard Medical School, Boston, MA, USA.
  • Hwang SW; MAP Centre for Urban Health Solutions, Unity Health Toronto, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada; ICES, Toronto, O
J Clin Epidemiol ; 172: 111430, 2024 Aug.
Article en En | MEDLINE | ID: mdl-38880439
ABSTRACT

OBJECTIVES:

Conducting longitudinal health research about people experiencing homelessness poses unique challenges. Identification through administrative data permits large, cost-effective studies; however, case validity in Ontario is unknown after a 2018 Canada-wide policy change mandating homelessness coding in hospital databases. We validated case definitions for identifying homelessness using Ontario health administrative databases after introduction of this coding mandate. STUDY DESIGN AND

SETTING:

We assessed 42 case definitions in a representative sample of people experiencing homelessness in Toronto (n = 640) from whom longitudinal housing history (ranging from 2018 to 2022) was obtained, and a randomly selected sample of presumably housed people (n = 128,000) in Toronto. We evaluated sensitivity, specificity, positive and negative predictive values, and positive likelihood ratios to select an optimal definition, and compared the resulting true positives against false positives and false negatives to identify potential causes of misclassification.

RESULTS:

The optimal case definition included any homelessness indicator during a hospital-based encounter within 180 days of a period of homelessness (sensitivity = 52.9%; specificity = 99.5%). For periods of homelessness with ≥1 hospital-based healthcare encounter, the optimal case definition had greatly improved sensitivity (75.1%) while retaining excellent specificity (98.5%). Review of false positives suggested that homeless status is sometimes erroneously carried forward in healthcare databases after an individual transitioned out of homelessness.

CONCLUSION:

Case definitions to identify homelessness using Ontario health administrative data exhibit moderate to good sensitivity and excellent specificity. Sensitivity has more than doubled since the implementation of a national coding mandate. Mandatory collection and reporting of homelessness information within administrative data present invaluable opportunities for advancing research on the health and healthcare needs of people experiencing homelessness.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Personas con Mala Vivienda Límite: Adult / Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: J Clin Epidemiol Asunto de la revista: EPIDEMIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Personas con Mala Vivienda Límite: Adult / Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: J Clin Epidemiol Asunto de la revista: EPIDEMIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos