Validation of HIV-infected cohort identification using automated clinical data in the Department of Veterans Affairs

Autor: Donna L. White, Paul G. Richardson, Jennifer R. Kramer, Kathryn E. Royse, D Sanchez, Suchismita Raychaudhury, Aaron P. Thrift, Roxanne Desiderio, Christine Hartman, Elizabeth Y. Chiao
Rok vydání: 2019
Předmět:
Zdroj: HIV Med
ISSN: 1468-1293
Popis: Objectives The US Department of Veterans Affairs (VA) is the largest integrated health care provider for HIV-infected patients in the USA. VA data for HIV-specific clinical and quality improvement research are an important resource. We sought to determine the accuracy of using the VA Corporate Data Warehouse (CDW), a fully automated medical records database for all VA users nationally, to identify HIV-infected patients compared with a gold-standard VA HIV Clinical Case Registry (CCR). Methods We assessed the test performance characteristics of each of our CDW criteria-based algorithms (presence of one, two or all of the following: diagnostic codes for HIV, positive HIV laboratory tests, and prescription for HIV medication) by calculating their sensitivity (proportion of HIV-positive patients in the CCR accurately detected as HIV-positive by the CDW algorithm) and positive predictive value (PPV; the proportion of patients identified by the CDW algorithm who were classified as HIV-positive from the CCR). Results We found that using a CDW algorithm requiring two of three HIV diagnostic criteria yielded the highest sensitivity (95.2%) with very little trade-off in PPV (93.5%). Conclusions A two diagnostic criteria-based algorithm can be utilized to accurately identify HIV-infected cohorts seen in the nationwide VA health care system.
Databáze: OpenAIRE