Despite advances in preventing HIV infection, the number of people infected with HIV has only modestly decreased over the past several years.PrEP has emerged as a highly effective prevention strategy, reducing the risk of infection by up to 99% when taken consistently, but a lack of awareness is hindering that effectiveness.
With its position as North Texas' largest safety-net hospital system, Parkland Health serves an extensive population of at-risk patients, creating a vital opportunity to address this problem and enhance HIV testing and facilitate connections to PrEP programs. Using AI PCCI has developed and implemented a predictive model that has helped Parkland Hospital identify and reach at-risk people in Dallas County.
In late 2022, the model went live, using information from the EHR to predict the individuals at increased likelihood of acquiring HIV and who may be candidates for HIV PrEP. Once identified, the patients can be offered HIV testing, and if negative can be offered PrEP. The HIV Detection AI/ML Model has risk stratified hundreds of thousands of patients, demonstrating that machine learning models can be used for predicting and classifying the risk of HIV using available EHR data.
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