Background As the emergency department (ED) has evolved into the de-facto site of care for a variety of substance use disorder (SUD) presentations, trends in ED utilization are an essential public health surveillance tool. Changes in ED visit patterns during the COVID-19 pandemic may reflect changes in access to outpatient treatment, changes in SUD incidence, or the unintended effects of public policy to mitigate COVID-19. We use a national emergency medicine registry to describe and characterize trends in ED visitation for SUDs since 2019. Methods We included all ED visits identified in a national emergency medicine clinical quality registry, which included 174 sites across 33 states with data from January 2019 through June 2021. We defined SUD using ED visit diagnosis codes including: opioid overdose and opioid use disorder (OUD), alcohol use disorders (AUD), and other SUD. To characterize changes in ED utilization, we plotted the 3-week moving average ratio of visit counts in 2020 and 2021 as compared to visit counts in 2019. Findings While overall ED visits declined in the early pandemic period and had not returned to 2019 baseline by June 2021, ED visit counts for SUD demonstrated smaller declines in March and April of 2020, so that the proportion of overall ED visits that were for SUD increased. Furthermore, in the second half of 2020, ED visits for SUD returned to baseline, and increased above baseline for OUD ever since May 2020. Conclusions We observe distinct patterns in ED visitation for SUDs over the course of the COVID-19 pandemic, particularly for OUD for which ED visitation barely declined and now exceeds previous baselines. These trends likely demonstrate the essential role of hospital-based EDs in providing 24/7/365 care for people with SUDs and mental health conditions. Allocation of resources must be directed towards the ED as a de-facto safety net for populations in crisis.

Background: Gaps in electronic health record (EHR) data collection and the paucity of standardized clinical data elements (CDEs) captured from electronic and digital data sources have impeded research efforts aimed at understanding the epidemiology and quality of care for opioid use disorder (OUD). We identified existing CDEs and evaluated their validity and usability, which is required prior to infrastructure implementation within EHRs. Methods: We conducted (a) a systematic literature review of publications in Medline, Embase and the Web of Science using a combination of at least one term related to OUD and EHR and (b) an environmental scan of publicly available data systems and dictionaries used in national informatics and quality measurement of policy initiatives. Opioid-related data elements identified within the environmental scan were compared with related data elements contained within nine common health data code systems and each element was graded for alignment with match results categorized as "exact", "partial", or "none. " Results: The literature review identified 5186 articles for title search, of which 75 abstracts were included for review and 38 articles were selected for full-text review. Full-text articles yielded 237 CDEs, only 12 (5.06%) of which were opioid-specific. The environmental scan identified 379 potential data elements and value sets across 9 data systems and libraries, among which only 84 (22%) were opioid-specific. We found substantial variability in the types of clinical data elements with limited overlap and no single data system included CDEs across all major data element types such as substance use disorder, OUD, medication and mental health. Relative to common health data code systems, few data elements had an exact match (< 1%), while 61% had a partial match and 38% had no matches. Conclusions: Despite the increasing ubiquity of EHR data standards and national attention placed on the opioid epidemic, we found substantial fragmentation in the design and construction of OUD related CDEs and little OUD specific CDEs in existing data dictionaries, systems and literature. Given the significant gaps in data collection and reporting, future work should leverage existing structured data elements to create standard workflow processes to improve OUD data capture in EHR systems.

Background The emergency department (ED) offers an important opportunity to identify patients with opioid use disorder (OUD) and initiate treatment. However, post-ED follow-up is challenging, and novel approaches to enhance care transitions are urgently needed. Outcomes following ED visits have traditionally focused on overdose, treatment engagement, and mortality with an absence of patient reported outcomes (PROs), for example patient ability to schedule follow-up OUD treatment appointments or pick up a prescription medication, that may better inform evaluation of treatment pathways and near-term outcomes after acute events. In the context of increasing novel secure mobile health (mHealth) platforms, we explored the feasibility and acceptability of electronically collecting PROs from ED patients with non-medical opioid use to enhance care in the ED and transitions of care. Methods ED patients with non-medical opioid use or opioid overdose who endorsed willingness and ability to complete electronic surveys after discharge were enrolled from a tertiary, urban academic ED. Participants were enrolled in an mHealth platform, shared electronic health records with researchers, and completed electronic surveys of PROs at baseline, three- and thirty-days post discharge from the hospital, including questions about ability to schedule a follow-up appointment, pick up a prescription medication and overdose risk behaviors. Primary outcomes were measures of feasibility and acceptability of electronic PRO collection among ED patients with non-medical opioid use. Results Among 1,808 patients assessed for eligibility between June-December 2019, 101 of 130 (78%) eligible adult patients consented to participate. Ninety-six (95%) of 101 patients completed registration in the mHealth platform, and 77/96 (80%) were successful in sharing their electronic health data. Completion rates for the baseline, three-day and thirty-day surveys were 97% (93/96), 49% (47/96) and 42% (40/96). Implementation challenges included short engagement window during ED visit, limited access to smartphones/computers, insufficient battery life of participant phone to access email and password, forgotten emails and passwords, multi-step verification processes for account set-up, and complaints about hospital care, most of which were effectively addressed by study personnel. Conclusions ED patients with OUD were willing to share electronic health information and PROs, although implementation challenges were common, and more than half of participants were lost-to-follow-up after hospital discharge at 30 days. Efforts to streamline communication and remove barriers to engagement are needed to improve the collection of PROs and pathways of care in ED patients with OUD. Clinical Trial Registration ClinicalTrials.gov (NCT03985163). Date of Registration: June 10, 2019, Retrospectively registered (First enrollment June 8, 2019). https://clinicaltrials.gov/ct2/show/record/NCT03985163

Objective: Prior research has identified gaps in the capacity of electronic health records (EHRs) to capture the intricacies of opioid-related conditions. We sought to enhance the opioid data infrastructure within the American College of Emergency Physicians' Clinical Emergency Data Registry (CEDR), the largest national emergency medicine registry, through data mapping, validity testing, and feasibility assessment. Methods:We compared the CEDR data dictionary to opioid common data elements identified through prior environmental scans of publicly available data systems and dictionaries used in national informatics and quality measurement of policy initiatives. Validity and feasibility assessments of CEDR opioid-related data were conducted through the following steps: (1) electronic extraction of CEDR data meeting criteria for an opioid-related emergency care visit, (2) manual chart review assessing the quality of the extracted data, (3) completion of feasibility scorecards, and (4) qualitative interviews with physician reviewers and informatics personnel. Results: We identified several data gaps in the CEDR data dictionary when compared with prior environmental scans including urine drug testing, opioid medication, and social history data elements. Validity testing demonstrated correct or partially correct data for >90% of most extracted CEDR data elements. Factors affecting validity included lack of standardization, data incorrectness, and poor delimitation between emergency department (ED) versus hospital care. Feasibility testing highlighted low-to-moderate feasibility of date and social history data elements, significant EHR platform variation, and inconsistency in the extraction of common national data standards (eg, Logical Observation Identifiers Names and Codes, International Classification of Diseases, Tenth Revision codes).

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