Enhancing population-level research among people who inject drugs: a validation and retrospective cohort study using health administrative data in Ontario, Canada Article Swipe
Zoë R. Greenwald
,
Jordan J. Feld
,
Dan Werb
,
Peter C. Austin
,
S.S.M. Drover
,
Daniel J. Fridman
,
Ahmed Bayoumi
,
Tara Gomes
,
Claire Kendall
,
Lauren Lapointe‐Shaw
,
Ayden I. Scheim
,
Sofia Bartlett
,
Eric I Benchimol
,
Zachary Bouck
,
Christina Greenaway
,
Naveed Z. Janjua
,
Pamela Leece
,
William Wong
,
Beate Sander
,
Jeffrey C. Kwong
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.23889/ijpds.v9i5.2628
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.23889/ijpds.v9i5.2628
ObjectiveHealth administrative data can support population-level research among people who inject drugs (PWID), however these data sources remain underutilized due to the difficulty in identifying drug use in routinely collected data. We validated case-ascertainment algorithms to identify PWID and tested their application in a hepatitis C (HCV) cohort in Ontario, Canada. ApproachWe conducted a validation study using reference standard cohorts of PWID recruited via community-based studies and population controls linked to health administrative data in Ontario, Canada (1992-2020). Tested case-ascertainment algorithms included combinations of hospitalizations/emergency department (ED) visits for drug use/poisoning, physician visits for drug use, opioid agonist treatment (OAT), or injecting-related infections. Sensitivity and specificity were estimated for lifetime history and recent injecting (past 1-5 years). We applied a high-performing algorithm among all Ontarians with laboratory-confirmed HCV between 1999-2018, to identify a sub-cohort of PWID with HCV. ResultsAn algorithm including ≥1 hospitalization/ED visit or ≥1 physician visit for drug use or ≥1 OAT record had high accuracy for identifying IDU history (91.6% sensitivity, 94.2% specificity) and recent IDU (using 3 years lookback: 80.4% sensitivity, 99% specificity). When applied to a provincial cohort of 112,947 Ontarians diagnosed with HCV, this algorithm estimated 46% (N=52,248) had a history of IDU, of whom 52% (N=27,246) had an indication of recent IDU (within the past 3 years). ConclusionThe methods developed in this study can enhance the capacity of population-level health research among people who inject drugs and support applied public health interventions towards hepatitis C elimination.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.23889/ijpds.v9i5.2628
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402404959
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402404959Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.23889/ijpds.v9i5.2628Digital Object Identifier
- Title
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Enhancing population-level research among people who inject drugs: a validation and retrospective cohort study using health administrative data in Ontario, CanadaWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-09-10Full publication date if available
- Authors
-
Zoë R. Greenwald, Jordan J. Feld, Dan Werb, Peter C. Austin, S.S.M. Drover, Daniel J. Fridman, Ahmed Bayoumi, Tara Gomes, Claire Kendall, Lauren Lapointe‐Shaw, Ayden I. Scheim, Sofia Bartlett, Eric I Benchimol, Zachary Bouck, Christina Greenaway, Naveed Z. Janjua, Pamela Leece, William Wong, Beate Sander, Jeffrey C. KwongList of authors in order
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https://doi.org/10.23889/ijpds.v9i5.2628Publisher landing page
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YesWhether a free full text is available
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-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.23889/ijpds.v9i5.2628Direct OA link when available
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Medicine, Retrospective cohort study, Environmental health, Cohort, Cohort study, Population, Health data, Family medicine, Health care, Political science, Internal medicine, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| publication_date | 2024-09-10 |
| publication_year | 2024 |
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