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Published in: BMC Health Services Research 1/2024

Open Access 01-12-2024 | Human Immunodeficiency Virus | Research

Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan

Authors: Gaia Pocobelli, Malia Oliver, Ladia Albertson-Junkans, Gabrielle Gundersen, Aruna Kamineni

Published in: BMC Health Services Research | Issue 1/2024

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Abstract

Background

Efficiently identifying patients with human immunodeficiency virus (HIV) using administrative health care data (e.g., claims) can facilitate research on their quality of care and health outcomes. No prior study has validated the use of only ICD-10-CM HIV diagnosis codes to identify patients with HIV.

Methods

We validated HIV diagnosis codes among women enrolled in a large U.S. integrated health care system during 2010–2020. We examined HIV diagnosis code-based algorithms that varied by type, frequency, and timing of the codes in patients’ claims data. We calculated the positive predictive values (PPVs) and 95% confidence intervals (CIs) of the algorithms using a medical record-confirmed diagnosis of HIV as the gold standard.

Results

A total of 272 women with ≥ 1 HIV diagnosis code in the administrative claims data were identified and medical records were reviewed for all 272 women. The PPV of an algorithm classifying women as having HIV as of the first HIV diagnosis code during the observation period was 80.5% (95% CI: 75.4–84.8%), and it was 93.9% (95% CI: 90.0-96.3%) as of the second. Little additional increase in PPV was observed when a third code was required. The PPV of an algorithm based on ICD-10-CM-era codes was similar to one based on ICD-9-CM-era codes.

Conclusion

If the accuracy measure of greatest interest is PPV, our findings suggest that use of ≥ 2 HIV diagnosis codes to identify patients with HIV may perform well. However, health care coding practices may vary across settings, which may impact generalizability of our results.
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Metadata
Title
Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan
Authors
Gaia Pocobelli
Malia Oliver
Ladia Albertson-Junkans
Gabrielle Gundersen
Aruna Kamineni
Publication date
01-12-2024
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2024
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-024-10685-x

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