Development of an electronic medical record-based algorithm to identify patients with unknown HIV status.

Individuals with unknown HIV status are at risk for undiagnosed HIV, but practical and reliable methods for identifying these individuals have not been described. We developed an algorithm to identify patients with unknown HIV status using data from the electronic medical record (EMR) of a large health care system. We developed EMR-based criteria to classify patients as having known status (HIV-positive or HIV-negative) or unknown status and applied these criteria to all patients seen in the affiliated health care system from 2008 to 2012. Performance characteristics of the algorithm for identifying patients with unknown HIV status were calculated by comparing a random sample of the algorithm's results to a reference standard medical record review. The algorithm classifies all patients as having either known or unknown HIV status. Its sensitivity and specificity for identifying patients with unknown status are 99.4% (95% CI: 96.5-100%) and 95.2% (95% CI: 83.8-99.4%), respectively, with positive and negative predictive values of 98.7% (95% CI: 95.5-99.8%) and 97.6% (95% CI: 87.1-99.1%), respectively. Using commonly available data from an EMR, our algorithm has high sensitivity and specificity for identifying patients with unknown HIV status. This algorithm may inform expanded HIV testing strategies aiming to test the untested.