Development and implementation of a prescription opioid registry across diverse health systems

Objective: Develop and implement a prescription opioid registry in 10 diverse health systems across the US and describe trends in prescribed opioids between 2012 and 2018. Materials and Methods: Using electronic health record and claims data, we identified patients who had an outpatient fill for any prescription opioid, and/or an opioid use disorder diagnosis, between January 1, 2012 and December 31, 2018. The registry contains distributed files of prescription opioids, benzodiazepines and other select medications, opioid antagonists, clinical diagnoses, procedures, health services utilization, and health plan membership. Rates of outpatient opioid fills over the study period, standardized to health system demographic distributions, are described by age, gender, and race/ethnicity among members without cancer. Results: The registry includes 6 249 710 patients and over 40 million outpatient opioid fills. For the combined registry population, opioid fills declined from a high of 0.718 per member-year in 2013 to 0.478 in 2018, and morphine milligram equivalents (MMEs) per fill declined from 985 MMEs per fill in 2012 to 758 MMEs in 2018. MMEs per member declined from 692 MMEs per member in 2012 to 362 MMEs per member in 2018. Conclusion: This study established a population-based opioid registry across 10 diverse health systems that can be used to address questions related to opioid use. Initial analyses showed large reductions in overall opioid use per member among the combined health systems. The registry will be used in future studies to answer a broad range of other critical public health issues relating to prescription opioid use

Associations between Psychiatric Disorders and Cannabis-Related Disorders Documented in Electronic Health Records

Data from a large network of community health centers connected via a single electronic health record (EHR) system examined associations between psychiatric disorders and documentation of a cannabis-related disorder among patients with reported cannabis use. Participants were adults who had at least one ambulatory visit at a clinic in three states between 1/1/2012 and 12/31/2016 and had either 1) a documented cannabis-related disorder indicated by an ICD-9/10 code on the problem list or encounter list or 2) documentation of cannabis use in the EHR social history section. Clinics included 101,405 patients with either cannabis use recorded in the social history of the EHR (n = 71,660) or a cannabis-related disorder documented in the encounter or problem list (n = 29,745). GEE logistic regression modeling estimated adjusted odds ratios (aOR). Odds of patients having cannabis-related disorder recorded on the encounter or problem list were higher for individuals with depression (aOR = 1.08, 95% CI: 1.04–1.13), anxiety (aOR = 1.16, CI: 1.11–1.21) and bipolar disorder (aOR = 1.16, CI: 1.10–1.23). A diagnosis of schizophrenia increased the odds of a cannabis-related disorder by 62% (aOR = 1.62, CI: 1.48– 1.78). Primary care providers should routinely screen for and document cannabis-related disorders and psychiatric disorders

Associations between psychiatric disorders and cannabis related disorders documented in electronic health records

Data from a large network of community health centers connected via a single electronic health record (EHR) system examined associations between psychiatric disorders and documentation of a cannabis-related disorder among patients with reported cannabis use. Participants were adults who had at least one ambulatory visit at a clinic in three states between 1/1/2012 and 12/31/2016 and had either 1) a documented cannabis-related disorder indicated by an ICD-9/10 code on the problem list or encounter list or 2) documentation of cannabis use in the EHR social history section. Clinics included 101,405 patients with either cannabis use recorded in the social history of the EHR (n = 71,660) or a cannabis-related disorder documented in the encounter or problem list (n = 29,745). GEE logistic regression modeling estimated adjusted odds ratios (aOR). Odds of patients having cannabis-related disorder recorded on the encounter or problem list were higher for individuals with depression (aOR = 1.08, 95% CI: 1.04–1.13), anxiety (aOR = 1.16, CI: 1.11–1.21) and bipolar disorder (aOR = 1.16, CI: 1.10–1.23). A diagnosis of schizophrenia increased the odds of a cannabis-related disorder by 62% (aOR = 1.62, CI: 1.48– 1.78). Primary care providers should routinely screen for and document cannabis-related disorders and psychiatric disorders

2021 SAEM Consensus Conference Proceedings: Research Priorities for Implementing Emergency Department Screening for Social Risks and Needs

Introduction: Despite literature on a variety of social risks and needs screening interventions in emergency department (ED) settings, there is no universally accepted or evidence-based process for conducting such interventions. Many factors hamper or promote implementation of social risks and needs screening in the ED, but the relative impact of these factors and how best to mitigate/leverage them is unknown.  Methods: Drawing on an extensive literature review, expert assessment, and feedback from participants in the 2021 Society for Academic Emergency Medicine Consensus Conference through moderated discussions and follow-up surveys, we identified research gaps and rated research priorities for implementing screening for social risks and needs in the ED. We identified three main knowledge gaps: 1) screening implementation mechanics; 2) outreach and engagement with communities; and 3) addressing barriers and leveraging facilitators to screening. Within these gaps, we identified 12 high-priority research questions as well as research methods for future studies.  Results: Consensus Conference participants broadly agreed that social risks and needs screening is generally acceptable to patients and clinicians and feasible in an ED setting. Our literature review and conference discussion identified several research gaps in the specific mechanics of screening implementation, including screening and referral team composition, workflow, and use of technology. Discussions also highlighted a need for more collaboration with stakeholders in screening design and implementation.  Additionally, discussions identified the need for studies using adaptive designs or hybrid effectiveness-implementation models to test multiple strategies for implementation and sustainability.  Conclusion: Through a robust consensus process we developed an actionable research agenda for implementing social risks and needs screening in EDs. Future work in this area should use implementation science frameworks and research best practices to further develop and refine ED screening for social risks and needs and to address barriers as well as leverage facilitators to such screening

Comparison of medical cannabis use reported on a confidential survey vs documented in the electronic health record among primary care patients.

Question: What is the prevalence of patient-reported explicit (ie, medical use) and implicit (ie, health reasons for use) medical cannabis use, and how does electronic health record documentation compare with patient report of medical use? Findings: In this survey study, among 1688 primary care patients, 26.5% reported explicit and 35.1% reported implicit medical use of cannabis. The prevalence of medical use documented in the electronic health record was 4.8%, missing most medical cannabis use reported by patients. Meaning: These findings suggest that asking about use of cannabis for managing pain, sleep, mood, or other health concerns may increase recognition and documentation of medical cannabis use

Prescription Opioid Dose Reductions and Potential Adverse Events: a Multi-site Observational Cohort Study in Diverse US Health Systems

BACKGROUND: In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events. OBJECTIVE: Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality). DESIGN: This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of  ≥ 50 during six consecutive months. PATIENTS: We identified 60,040 non-cancer patients with  ≥ one 2-month dose reduction period (600,234 unique dose reduction periods). MAIN MEASURES: Analyses examined associations between dose reduction levels (1- \u3c 15%, 15- \u3c 30%, 30- \u3c 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics. KEY RESULTS: Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- \u3c 15%, dose reductions of 30- \u3c 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- \u3c 30%, compared to 1- \u3c 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality. CONCLUSIONS: Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored