A Novel Use of the "3-Day Rule": Post-discharge Methadone Dosing in the Emergency Department.

Introduction: Methadone is a medically necessary and lifesaving medication for many patients with opioid use disorder. To adequately address these patients' needs, methadone should be offered in the hospital, but barriers exist that limit its continuation upon discharge. The code of federal regulations allows for methadone dosing as an inpatient as well as outpatient dispensing for up to three days to facilitate linkage to treatment. As a quality initiative, we created a new workflow for discharging patients on methadone to return to the emergency department (ED) for uninterrupted dosing. Methods: Our addiction medicine team changed hospital methadone policy to better allow hospitalization as a window of opportunity to start methadone. This necessitated the creation of a warm-handoff process to link patients to methadone clinics if that linkage could not happen immediately on discharge. Thus, our team created the "ED Bridge" process, which uses the "3-day rule" to dispense methadone from the ED post hospital discharge. We then followed every patient we directed through this workflow as an observational cohort for outcomes and trends. Results: Of the patients for whom ED bridge dosing was planned, 40.4% completed all bridge dosing and an additional 17.3% received at least one but not all bridge doses. Established methadone patients made up 38.1% of successful linkages, and 61.9% were patients who were newly started on methadone in the hospital. Conclusion: Improving methadone as a treatment option remains an ongoing issue for policymakers and advocates. Our ED bridge workflow allows us to expand access and continuation of methadone now using existing laws and regulations, and to better use hospitals as a point of entry into methadone treatment.

The Evaluation of a Clinical Decision Support Tool Using Natural Language Processing to Screen Hospitalized Adults for Unhealthy Substance Use: Protocol for a Quasi-Experimental Design.

BACKGROUND: Automated and data-driven methods for screening using natural language processing (NLP) and machine learning may replace resource-intensive manual approaches in the usual care of patients hospitalized with conditions related to unhealthy substance use. The rigorous evaluation of tools that use artificial intelligence (AI) is necessary to demonstrate effectiveness before system-wide implementation. An NLP tool to use routinely collected data in the electronic health record was previously validated for diagnostic accuracy in a retrospective study for screening unhealthy substance use. Our next step is a noninferiority design incorporated into a research protocol for clinical implementation with prospective evaluation of clinical effectiveness in a large health system. OBJECTIVE: This study aims to provide a study protocol to evaluate health outcomes and the costs and benefits of an AI-driven automated screener compared to manual human screening for unhealthy substance use. METHODS: A pre-post design is proposed to evaluate 12 months of manual screening followed by 12 months of automated screening across surgical and medical wards at a single medical center. The preintervention period consists of usual care with manual screening by nurses and social workers and referrals to a multidisciplinary Substance Use Intervention Team (SUIT). Facilitated by a NLP pipeline in the postintervention period, clinical notes from the first 24 hours of hospitalization will be processed and scored by a machine learning model, and the SUIT will be similarly alerted to patients who flagged positive for substance misuse. Flowsheets within the electronic health record have been updated to capture rates of interventions for the primary outcome (brief intervention/motivational interviewing, medication-assisted treatment, naloxone dispensing, and referral to outpatient care). Effectiveness in terms of patient outcomes will be determined by noninferior rates of interventions (primary outcome), as well as rates of readmission within 6 months, average time to consult, and discharge rates against medical advice (secondary outcomes) in the postintervention period by a SUIT compared to the preintervention period. A separate analysis will be performed to assess the costs and benefits to the health system by using automated screening. Changes from the pre- to postintervention period will be assessed in covariate-adjusted generalized linear mixed-effects models. RESULTS: The study will begin in September 2022. Monthly data monitoring and Data Safety Monitoring Board reporting are scheduled every 6 months throughout the study period. We anticipate reporting final results by June 2025. CONCLUSIONS: The use of augmented intelligence for clinical decision support is growing with an increasing number of AI tools. We provide a research protocol for prospective evaluation of an automated NLP system for screening unhealthy substance use using a noninferiority design to demonstrate comprehensive screening that may be as effective as manual screening but less costly via automated solutions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03833804; https://clinicaltrials.gov/ct2/show/NCT03833804. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42971.

The substance use intervention team: A hospital-based intervention and outpatient clinic to improve care for patients with substance use disorders.

PURPOSE: In response to the opioid crisis, public health advocates urge hospitals to perform substance use disorder (SUD) screening, brief intervention, discharge planning with referral to treatment, and naloxone education. Universal screening makes specialized treatment available to all patients and decreases stigma around SUDs, allowing patients and providers to address SUDs during their hospitalization. Additionally, hospital and emergency department-initiated medications to treat SUD improve patient engagement with treatment and decrease opioid use, and use of medications for opioid use disorder after nonfatal overdoses decreases mortality. SUMMARY: A substance use intervention team (SUIT) service was established to offer universal screening and consultation by an interdisciplinary team at our urban academic medical center. The SUIT program provides inpatient consultation services as well as medical and behavioral clinic visits to transition patients to long-term treatment and is comprised of physicians, nurse practitioners, a clinical pharmacist, social workers, and a nurse. Successes attributed to enhanced medication use as a function of having a designated pharmacist as an integral member of the team are highlighted. Our medical center initiated screening efforts in tandem with its interdisciplinary team and clinic. The team attempts to start appropriately selected patients with SUD on medications for SUD while hospitalized. From January through December 2018, 87.2% of patients admitted to the hospital received initial SUD screening. Of the patients who screened positive, 1,400 received a brief intervention by a unit social worker; the SUIT service was consulted on 880 patients, and multiple medications for SUD were started during inpatient care. CONCLUSION: A screening, brief intervention, and referral to treatment service was successfully implemented in our hospital, with the SUIT program in place to provide interdisciplinary addiction care and initiate medications for SUD in appropriate patients.