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Identifying injection drug use and estimating population size of people who inject drugs using healthcare administrative datasets

Janjua, Naveed Zafar, Islam, Nazrul, Kuo, Margot, Yu, Amanda, Wong, Stanley, Butt, Zahid A., Gilbert, Mark, Buxton, Jane, Chapinal, Nuria, Samji, Hasina, Chong, Mei, Alvarez, Maria, Wong, Jason, Tyndall, Mark W., Krajden, Mel·2018·International Journal of Drug Policy
DOI 10.1016/j.drugpo.2018.02.001
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Abstract

Background Large linked healthcare administrative datasets could be used to monitor programs providing prevention and treatment services to people who inject drugs (PWID). However, diagnostic codes in administrative datasets do not differentiate non-injection from injection drug use (IDU). We validated algorithms based on diagnostic codes and prescription records representing IDU in administrative datasets against interview-based IDU data. Methods The British Columbia Hepatitis Testers Cohort (BC-HTC) includes ∼1.7 million individuals tested for HCV/HIV or reported HBV/HCV/HIV/tuberculosis cases in BC from 1990 to 2015, linked to administrative datasets including physician visit, hospitalization and prescription drug records. IDU, assessed through interviews as part of enhanced surveillance at the time of HIV or HCV/HBV diagnosis from a subset of cases included in the BC-HTC (n = 6559), was used as the gold standard. ICD-9/ICD-10 codes for IDU and injecting-related infections (IRI) were grouped with records of opioid substitution therapy (OST) into multiple IDU algorithms in administrative datasets. We assessed the performance of IDU algorithms through calculation of sensitivity, specificity, positive predictive, and negative predictive values. Results Sensitivity was highest (90-94%), and specificity was lowest (42-73%) for algorithms based either on IDU or IRI and drug misuse codes. Algorithms requiring both drug misuse and IRI had lower sensitivity (57-60%) and higher spec…

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Metadata

Authors
Janjua, N. Z., Islam, N., Kuo, M., Yu, A., Wong, S., Butt, Z. A., Gilbert, M., Buxton, J., Chapinal, N., Samji, H., Chong, M., Alvarez, M., Wong, J., Tyndall, M. W., & Krajden, M.
Venue
International Journal of Drug Policy
Publisher
Elsevier BV
Published
2018-05
Volume
55
Pages
31-39
ISSN
0955-3959
DOI
10.1016/j.drugpo.2018.02.001
Cited by
102
References
2
Language
en
Licence
Funders
  • Canadian Institutes of Health Research (NHC-142832, PHE-141773)
  • Public Health Agency of Canada
  • Michael Smith Foundation for Health Research

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