Validation of <scp>HIV</scp>‐infected cohort identification using automated clinical data in the Department of Veterans Affairs

Abstract

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.

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