A new study led by Drew Wilimitis, statistical analyst in the lab, is out now in JAMA Network Open. Co-authors include our wonderful collaborators Robert Turer, MD, MS; Michael Ripperger; Allison McCoy, PhD; Sarah Sperry, PhD; Elliot Fielstein, PhD; and Troy Kurz, MD. In this study, we asked: what happens when we combine automated risk…
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New Paper – Risky business: a scoping review for communicating results of predictive models between providers and patients
Given widespread excitement around predictive analytics and the proliferation of machine learning algorithms that predict outcomes, a key next step is understanding how this information is — or should be — communicated with patients. In collaboration with Mollie McKillop, Patricia Lee, Joyce Harris, Christopher Simpson, and Laurie Novak, we conducted a scoping review to identify…
New Paper – Ensemble learning to predict opioid-related overdose using statewide prescription drug monitoring program and hospital discharge data in the state of Tennessee
Over 2,000 Tennesseans died in 2019 from overdose – can we predict overdose risk anywhere in the state to guide prevention? Our study on this question is out now in the Journal of the American Medical Informatics Association. Since 2012, Tennessee has participated in a comprehensive Prescription Drug Monitoring Program called the Controlled Substance Monitoring…
Walsh Science 