Application and Validation of Case-Finding Algorithms for Identifying Individuals with Human Immunodeficiency Virus from Administrative Data in British Columbia, Canada

Resource type
Date created
2013
Authors/Contributors
Abstract
ObjectiveTo define a population-level cohort of individuals infected with the human immunodeficiency virus (HIV) in the province of British Columbia from available registries and administrative datasets using a validated case-finding algorithm.MethodsIndividuals were identified for possible cohort inclusion from the BC Centre for Excellence in HIV/AIDS (CfE) drug treatment program (antiretroviral therapy) and laboratory testing datasets (plasma viral load (pVL) and CD4 diagnostic test results), the BC Centre for Disease Control (CDC) provincial HIV surveillance database (positive HIV tests), as well as databases held by the BC Ministry of Health (MoH); the Discharge Abstract Database (hospitalizations), the Medical Services Plan (physician billing) and PharmaNet databases (additional HIV-related medications). A validated case-finding algorithm was applied to distinguish true HIV cases from those likely to have been misclassified. The sensitivity of the algorithms was assessed as the proportion of confirmed cases (those with records in the CfE, CDC and MoH databases) positively identified by each algorithm. A priori hypotheses were generated and tested to verify excluded cases.ResultsA total of 25,673 individuals were identified as having at least one HIV-related health record. Among 9,454 unconfirmed cases, the selected case-finding algorithm identified 849 individuals believed to be HIV-positive. The sensitivity of this algorithm among confirmed cases was 88%. Those excluded from the cohort were more likely to be female (44.4% vs. 22.5%; p<0.01), had a lower mortality rate (2.18 per 100 person years (100PY) vs. 3.14/100PY; p<0.01), and had lower median rates of health service utilization (days of medications dispensed: 9745/100PY vs. 10266/100PY; p<0.01; days of inpatient care: 29/100PY vs. 98/100PY; p<0.01; physician billings: 602/100PY vs. 2,056/100PY; p<0.01).ConclusionsThe application of validated case-finding algorithms and subsequent hypothesis testing provided a strong framework for defining a population-level cohort of HIV infected people in BC using administrative databases.
Document
Identifier
DOI: 10.1371/journal.pone.0054416
Published as
Nosyk B, Colley G, Yip B, Chan K, Heath K, et al. (2013) Application and Validation of Case-Finding Algorithms for Identifying Individuals with Human Immunodeficiency Virus from Administrative Data in British Columbia, Canada. PLoS ONE 8(1): e54416. doi:10.1371/journal.pone.0054416
Publication title
PLoS ONE
Document title
Application and Validation of Case-Finding Algorithms for Identifying Individuals with Human Immunodeficiency Virus from Administrative Data in British Columbia, Canada
Date
2013
Volume
8
Issue
1
Publisher DOI
10.1371/journal.pone.0054416
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Copyright is held by the author(s).
Scholarly level
Peer reviewed?
Yes
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Member of collection
Attachment Size
HIV2.pdf 1.97 MB