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Machine learning can be used to comb through online reviews of substance use treatment facilities to home in on qualities that are important to patients but remain hard to capture via formal means, such as surveys, researchers from the Perelman School of Medicine at the University of Pennsylvania show. The researchers found that professionalism and staff dedication to patients were two of the top qualities that could be attributed to either a negative or positive review of the facility. Findings from this study were published today in the
Journal of General Internal Medicine.
"Searching for - and connecting with - therapy can be very difficult and confusing. Many individuals start their search online, where they are likely to see an online review accompanying other information about a treatment facility," said the study's lead author, Anish Agarwal, MD, a clinical innovation manager in the Penn Medicine Center for Digital Health and an assistant professor of Emergency Medicine. "These online reviews can provide commentary on what is driving positive, or negative, patient experiences throughout recovery, but they must be accurately identified. Through machine learning, we've shown that this is possible, and we hope such findings can be used to improve patient-centered addiction care."