This clinical trial aims to evaluate the pilot implementation of a machine-learning (ML)-driven clinical decision support (CDS) tool designed to predict opioid overdose risk within the electronic health record (EHR) system at UF Health Internal Medicine and Family Medicine clinics in Gainesville, Florida. The study will use a pre- versus post-implementation design to compare outcomes within clinics, focusing on measures such as naloxone prescribing rates and opioid overdose occurrences. Researchers will also assess the usability, acceptability, and feasibility of the CDS tool through qualitative interviews with primary care clinicians (PCPs) in the participating clinics.
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Composite patient-level outcomes related to opioids
Timeframe: From enrollment and up to 12 months (3, 6, 12 months) post implementation of the OPA
PCP's use feedback of the Overdose Prevention Alert (OPA)
Timeframe: From enrollment and up to 7 months post implementation of the OPA