Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan
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 identi...
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BMC
2024-02-01
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Series: | BMC Health Services Research |
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Online Access: | https://doi.org/10.1186/s12913-024-10685-x |
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author | Gaia Pocobelli Malia Oliver Ladia Albertson-Junkans Gabrielle Gundersen Aruna Kamineni |
author_facet | Gaia Pocobelli Malia Oliver Ladia Albertson-Junkans Gabrielle Gundersen Aruna Kamineni |
author_sort | Gaia Pocobelli |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-07T15:13:00Z |
format | Article |
id | doaj.art-5dc59452cf214e19ae59b04394617fce |
institution | Directory Open Access Journal |
issn | 1472-6963 |
language | English |
last_indexed | 2024-03-07T15:13:00Z |
publishDate | 2024-02-01 |
publisher | BMC |
record_format | Article |
series | BMC Health Services Research |
spelling | doaj.art-5dc59452cf214e19ae59b04394617fce2024-03-05T18:05:28ZengBMCBMC Health Services Research1472-69632024-02-012411610.1186/s12913-024-10685-xValidation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health planGaia Pocobelli0Malia Oliver1Ladia Albertson-Junkans2Gabrielle Gundersen3Aruna Kamineni4Kaiser Permanente Washington Health Research InstituteKaiser Permanente Washington Health Research InstituteKaiser Permanente Washington Health Research InstituteKaiser Permanente Washington Health Research InstituteKaiser Permanente Washington Health Research InstituteAbstract 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.https://doi.org/10.1186/s12913-024-10685-xHIVPredictive value of testsValidation studyElectronic health recordsICD codes |
spellingShingle | Gaia Pocobelli Malia Oliver Ladia Albertson-Junkans Gabrielle Gundersen Aruna Kamineni Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan BMC Health Services Research HIV Predictive value of tests Validation study Electronic health records ICD codes |
title | Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan |
title_full | Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan |
title_fullStr | Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan |
title_full_unstemmed | Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan |
title_short | Validation of human immunodeficiency virus diagnosis codes among women enrollees of a U.S. health plan |
title_sort | validation of human immunodeficiency virus diagnosis codes among women enrollees of a u s health plan |
topic | HIV Predictive value of tests Validation study Electronic health records ICD codes |
url | https://doi.org/10.1186/s12913-024-10685-x |
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