Kaiser Permanente researchers weigh in on algorithm that predicts risk of H.I.V. infection

A recent article in The New York Times examines an algorithm, developed at Kaiser Permanente Northern California, that doctors can use to assess patient risk for H.I.V and recommend a daily pill to prevent infection – a strategy referred to as PrEP. The idea to use data from electronic health records to determine if patients are at high risk for H.I.V. infection was borne from researchers at Kaiser Permanente Division of Research in Northern California and Harvard.

The Times article references a study conducted by investigators at Kaiser Permanente San Francisco, the Division of Research, Beth Israel Deaconess Medical Center, and Harvard Medical School that was published earlier this month in The Lancet HIV. Study co-authors Jonathan Volk, MD, MPH, and Michael Silverberg, PhD, MPH, were quoted in a recent article about its results.

The findings suggest that it is possible to correctly identify men who are at high risk for H.I.V infection – the virus that causes AIDS – by examining stored medical data. How doctors decide to use this tool moving forward is a delicate issue. However, with nearly 40,000 new H.I.V. infections a year in the United States, use of PrEP could prove to be highly valuable among high-risk patients.

“We intuitively felt like there were many data elements in the electronic health record that could predict risk,” Julia Marcus, MD, MPH, former postdoctoral fellow at the Division of Research, who developed the algorithm, is quoted as saying in the article.

The use of PrEP stands to help educate patients and doctors by opening a dialogue to discuss H.I.V. infection risk.

For more information, read the full article on The New York Times website.