Using Clinical Decision Support to Provide Social Risk-Informed Care for Opioid Use Disorder in the Emergency Department

The overarching goal of this proposal is to integrate patient social risk information into an existing electronic health record (EHR)-based clinical decision support (CDS) tool (CDSv1) to facilitate emergency department (ED)-initiated, social risk-informed opioid use disorder (OUD) medication treatment and ultimately improve treatment adherence and follow up. The investigators will evaluate the feasibility and acceptability of the social care-enhanced CDS tool, CDSv2, (compared to CDSv1) at a single study site (UCSF) as an intervention to increase medication treatment adherence and follow up for adult ED patients experiencing opioid use disorder using a mixed-methods, before-after approach.

Over 2.7 million people suffer from opioid use disorder (OUD) in the United States (US), resulting in more than 80,000 opioid overdose deaths in 2021. Medications for opioid use disorder are underused disproportionately in patients living in poverty, whose unmet food, housing, and transportation needs impede access to medications and routine healthcare. Emergency departments (EDs) are the primary (and often only) healthcare access points for vulnerable populations with social needs, including people with OUD. In response, healthcare professional organizations have increasingly called for ED-initiated medications for OUD (MOUD), which has been shown to lead to better adherence compared to referrals to treatment alone. Clinical decision support (CDS) tools in electronic health records (EHRs) can be used to support ED-initiated MOUD. They enhance care quality by providing actionable information to clinicians in real time; a study of a CDS tool for MOUD showed that it significantly increased the number of MOUD prescribers. A major risk of ED-initiated MOUD, however, is that it could lead to inequitable outcomes unless closely paired with efforts to connect patients to services that also address social needs. For instance, patients with food or housing insecurity are unlikely to prioritize adherence to MOUD over meeting their basic material needs; patients with MOUD who lack reliable transportation may be unable to access follow up care for MOUD. Linking social interventions to MOUD initiation may improve the likelihood of adherence to treatment and follow-up care. Though CDS tools that use patients' social risk data have been developed to improve care for other chronic diseases, e.g., hypertension and diabetes, to date, the CDS tools that facilitate ED-initiated MOUD have not been designed to harness social risk information to improve MOUD care planning. There is an urgent need to design and test a CDS tool that simultaneously facilitates MOUD initiation and helps identify and intervene on patients' social needs. The overarching goal of this project is to evaluate the feasibility and acceptability of a social care-enhanced CDS tool (CDSv2) designed to facilitate ED-based, social risk-informed MOUD compared to an existing CDS tool for ED-based MOUD (CDSv1), with the ultimate goal of improving treatment adherence and follow up for ED patients experiencing OUD. Specific Aim: Assess the feasibility and acceptability of the social care-enhanced CDS tool (CDSv2, compared to CDSv1) at the UCSF ED as an intervention to improve medication treatment adherence and follow up for adult ED patients experiencing OUD. The investigators will perform a mixed-methods, before-after pilot study evaluating the basic CDS tool (CDSv1) and the social care-enhanced CDS tool (CDSv2) over 28 months. To assess feasibility of patient recruitment and primary endpoint collection (e.g, adherence, follow up), the investigators will perform chart review and outreach to patients. To measure clinician utilization and acceptability, the investigators will collect EHR-based audit log and survey data. The investigators will also conduct semi-structured interviews with a purposive sample of ED clinicians and patients to further capture their experiences (acceptability) with the social care-enhanced CDS tool and the basic CDS tool. The expected sample size of 300 will include 240 providers and 60 patients.