Trends in the Prescribing of Buprenorphine for Opioid Use Disorder, 2019-2023.

Objective: To evaluate whether access to buprenorphine to treat opioid use disorder (OUD) was associated with the coronavirus disease pandemic, the relaxation of training requirements to obtain an X-Waiver to prescribe buprenorphine (April 2021), and the removal of the X-Waiver (December 2022). Patients and Methods: The OptumLabs Data Warehouse, which includes claims from Commercial and Medicare Advantage enrollees, was used to evaluate trends in prescription fills from January 1, 2019, to June 30, 2023. We compared fill patterns of buprenorphine for OUD with acamprosate to treat alcohol use disorder and naltrexone to treat alcohol use disorder or OUD. We evaluated trends in the rate ratio (RR) of overall fills; RR by days supply; distribution of fills by daily dose; and distribution of fills by prescriber type. Results: Coronavirus disease (RR, 1.06; 95% CI, 1.01-1.11) was associated with a slightly increased rate of fills for Commercial enrollees but not overall or for Medicare Advantage enrollees. There were also no significant increases (P>0.05) associated with the change in training requirements or removal of the X-Waiver. Over the study period, there was an increasing share of fills for 16+ mg for Commercial enrollees, and buprenorphine prescribers were more likely to be advanced practice nurses or physician assistants. Conclusion: We did not find meaningful improvement in access in response to coronavirus disease or the changes in the X-Waiver. These findings suggest that interventions beyond removing the X-Waiver may be needed to improve buprenorphine access.

Risk of falls is associated with 30-day mortality among older adults in the emergency department.

OBJECTIVE: Falls in older adults correlate with heightened morbidity and mortality. Assessing fall risk in the emergency department (ED) not only aids in identifying candidates for prevention interventions but may also offer insights into overall mortality risk. We sought to examine the link between fall risk and 30-day mortality in older ED adults. METHODS: Observational cohort study of adults aged ≥ 75years who presented to an academic ED and who were assessed for fall risk using the Memorial Emergency Department Fall Risk Assessment Tool (MEDFRAT), a validated, ED-specific screening tool. The fall risk was classified as low (0-2 points), moderate (3-4 points), or high (≥5) risk. The primary outcome was 30-day mortality. Hazard ratios (HR) with 95% confidence intervals (CIs) were calculated. RESULTS: A total of 941 patients whose fall risk was assessed in the ED were included in the study. Median age was 83.7 years; 45.6% were male, 75.6% lived in private residences, and 62.7% were admitted. Mortality at 30 days among the high fall risk group was four times that of the low fall risk group (11.8% vs 3.1%; HR 4.00, 95% CI 2.18 to 7.34, p < 0.001). Moderate fall risk individuals had nearly double the mortality rate of the low-risk group (6.0% vs 3.1%), but the difference was not statistically significant (HR 1.98, 95% CI 0.91 to 4.32, p = 0.087). CONCLUSION: ED fall risk assessments are linked to 30-day mortality. Screening may facilitate the stratification of older adults at risk for health deterioration.

Quantifying EHR and Policy Factors Associated with the Gender Productivity Gap in Ambulatory, General Internal Medicine.

BACKGROUND: The gender gap in physician compensation has persisted for decades. Little is known about how differences in use of the electronic health record (EHR) may contribute. OBJECTIVE: To characterize how time on clinical activities, time on the EHR, and clinical productivity vary by physician gender and to identify factors associated with physician productivity. DESIGN, SETTING, AND PARTICIPANTS: This longitudinal study included general internal medicine physicians employed by a large ambulatory practice network in the Northeastern United States from August 2018 to June 2021. MAIN MEASURES: Monthly data on physician work relative value units (wRVUs), physician and practice characteristics, metrics of EHR use and note content, and temporal trend variables. KEY RESULTS: The analysis included 3227 physician-months of data for 108 physicians (44% women). Compared with men physicians, women physicians generated 23.8% fewer wRVUs per month, completed 22.1% fewer visits per month, spent 4.0 more minutes/visit and 8.72 more minutes on the EHR per hour worked (all p < 0.001), and typed or dictated 36.4% more note characters per note (p = 0.006). With multivariable adjustment for physician age, practice characteristics, EHR use, and temporal trends, physician gender was no longer associated with productivity (men 4.20 vs. women 3.88 wRVUs/hour, p = 0.31). Typing/dictating fewer characters per note, relying on greater teamwork to manage orders, and spending less time on documentation were associated with higher wRVUs/hour. The 2021 E/M code change was associated with higher wRVUs/hour for all physicians: 10% higher for men physicians and 18% higher for women physicians (p < 0.001 and p = 0.009, respectively). CONCLUSIONS: Increased team support, briefer documentation, and the 2021 E/M code change were associated with higher physician productivity. The E/M code change may have preferentially benefited women physicians by incentivizing time-intensive activities such as medical decision-making, preventive care discussion, and patient counseling that women physicians have historically spent more time performing.

Trends in new and persistent opioid use in older adults with and without cancer.

BACKGROUND: The impact of ongoing efforts to decrease opioid use on patients with cancer remains undefined. Our objective was to determine trends in new and additional opioid use in patients with and without cancer. METHODS: This retrospective cohort study used data from Surveillance, Epidemiology, and End Results program-Medicare for opioid-naive patients with solid tumor malignancies diagnosed from 2012 through 2017 and a random sample of patients without cancer. We identified 238 470 eligible patients with cancer and further focused on 4 clinical strata: patients without cancer, patients with metastatic cancer, patients with nonmetastatic cancer treated with surgery alone ("surgery alone"), and patients with nonmetastatic cancer treated with surgery plus chemotherapy or radiation therapy ("surgery+"). We identified new, early additional, and long-term additional opioid use and calculated the change in predicted probability of these outcomes from 2012 to 2017. RESULTS: New opioid use was higher in patients with cancer (46.4%) than in those without (6.9%) (P < .001). From 2012 to 2017, the predicted probability of new opioid use was more stable in the cancer strata (relative declines: 0.1% surgery alone; 2.4% surgery+; 8.8% metastatic cancer), than in the noncancer stratum (20.0%) (P < .001 for each cancer to noncancer comparison). Early additional use declined among surgery patients (‒14.9% and ‒17.5% for surgery alone and surgery+, respectively) but was stable among patients with metastatic disease (‒2.8%, P = .50). CONCLUSIONS: Opioid prescribing declined over time at a slower rate in patients with cancer than in patients without cancer. Our study suggests important but tempered effects of the changing opioid climate on patients with cancer.

Development of a machine learning algorithm based on administrative claims data for identification of ED anaphylaxis patient visits.

Background: Epidemiologic studies of anaphylaxis commonly rely on International Classification of Diseases (ICD) codes to identify anaphylaxis cases, which may lead to suboptimal epidemiologic classification. Objective: We sought to develop and assess the accuracy of a machine learning algorithm using ICD codes and other administrative data compared with ICD code-only algorithms to identify emergency department (ED) anaphylaxis visits. Methods: We conducted a retrospective review of ED visits from January 2013 to September 2017. Potential ED anaphylaxis visits were identified using 3 methods: anaphylaxis ICD diagnostic codes (method 1), ICD symptom-based codes with or without a code indicating an allergic trigger (method 2), and ICD codes indicating a potential allergic reaction only (method 3). A machine learning algorithm was developed from administrative data, and test characteristics were compared with ICD code-only algorithms. Results: A total of 699 of 2191 (31.9%) potential ED anaphylaxis visits were classified as anaphylaxis. The sensitivity and specificity of method 1 were 49.1% and 87.5%, respectively. Method 1 used in combination with method 2 resulted in a sensitivity of 53.9% and a specificity of 68.7%. Method 1 used in combination with method 3 resulted in a sensitivity of 98.4% and a specificity of 15.1%. The sensitivity and specificity of the machine learning algorithm were 87.3% and 79.1%, respectively. Conclusions: ICD coding alone demonstrated poor sensitivity in identifying cases of anaphylaxis, with venom-related anaphylaxis missing 96% of cases. The machine learning algorithm resulted in a better balance of sensitivity and specificity and improves upon previous strategies to identify ED anaphylaxis visits.

Uptake of Biosimilar Among Privately Insured Patients Undergoing Infliximab Treatment.

BACKGROUND: Recent literature has found rapid uptake of short-acting filgrastim biosimilars but slower uptake of other biosimilars, such as infliximab, in both Medicare and privately insured enrollees. OBJECTIVES: To describe patient, provider, and health plan characteristics associated with a switch to biosimilar among existing infliximab patients. RESEARCH DESIGN: We constructed a retrospective panel dataset of patients undergoing active infliximab treatments and the choice of infliximab drug for each infusion. We used mixed logit regression controlling for patient, provider, and health plan characteristics as well as time-fixed effects. SUBJECTS: Medicare Advantage and privately insured enrollees with evidence of active infliximab treatments between 2016 and 2020 (n=357,430). MEASURES: Our primary outcome of interest was to switch from infliximab originator to one of the infliximab biosimilars. Exposure variables of interest variables such as out-of-pocket, site of care, and in-network deductible. RESULTS: Our study found nominally low switching among existing infliximab originator users (3.4%). We found that patients who previously received 1 infliximab originator infusion were 63.7% more likely to switch to biosimilar compared with patients who previously received administration of 20 infliximab originators. We found that biosimilar's placement as health's plan preferred drug was attributed to higher likelihood of biosimilar use (odds ratio: 1.666; P -value=0.001). We did not observe any statistically significant effect among out-of-pocket amount or deductible with respect to switch to infliximab biosimilar. CONCLUSIONS: To encourage uptake and switch to biosimilar, policymakers should consider targeted policies that include leveraging health plan tools such as placement of biosimilar as preferred drug and aim to educate patients on the clinical equivalence between infliximab biosimilar and originator.

Longitudinal Patterns in Testosterone Prescribing After US FDA Safety Communication in 2014.

BACKGROUND: The objective of this study was to describe changes in testosterone prescribing following a 2014 US Food and Drug Administration (FDA) safety communication and how changes varied by physician characteristics. METHODS: Data were extracted from a 20% random sample of Medicare fee-for-service administrative claims data from 2011 through 2019. The sample included 1,544,604 unique male beneficiaries who received evaluation and management (E&M) services from 58,819 unique physicians that prescribed testosterone between 2011 and 2013. Patients were categorized based on presence of coronary artery disease (CAD) and non-age-related hypogonadism. Physician characteristics were identified in the OneKey database and included specialty and affiliations with teaching hospitals, for-profit hospitals, hospitals in integrated delivery networks, and hospitals in the top decile of case mix index. Linear segmented models described how testosterone prescriptions changed following a 2014 FDA safety communication and how changes were associated with physician and organizational characteristics. RESULTS: Among 65,089,560 physician-patient-quarter-year observations, mean (standard deviation) age ranged from 72.16 (5.84) years for observations without CAD or non-age-related hypogonadism to 75.73 (6.92) years with CAD and without non-age-related hypogonadism. Following the safety communication, immediate changes in off-label testosterone prescription levels fell by 0.22 percentage points (pp) (95% confidence interval [CI] -0.33 to -0.11) for patients with CAD and by -0.16 pp (95% CI -0.19 to -0.16) for patients without CAD. A similar change was noticed in on-label prescribing levels. Off-label testosterone prescription quarterly trend, however, increased for patients with CAD and without CAD; on-label testosterone prescription trends declined for both groups. Declines in off-label prescribing were larger when treated by primary care physicians vs. non-primary care physicians, and physicians affiliated with teaching compared to nonteaching hospitals. Physician and organizational characteristics were not associated with changes in on-label prescribing. CONCLUSION: On-label and off-label testosterone therapy declined following the FDA safety communication. Certain physician characteristics were associated with changes in off-label, but not on-label, prescribing.

Association of delirium with increased short-term mortality among older emergency department patients: A cohort study.

STUDY OBJECTIVE: To evaluate the association between delirium and subsequent short-term mortality in geriatric patients presenting to the emergency department (ED). METHODS: This was an observational cohort study of adults age ≥75 years who presented to an academic ED and were screened for delirium during their ED visit. The Delirium Triage Screen followed by the Brief Confusion Assessment Method were used to ascertain the presence of delirium. In-hospital, 7-day, and 30-day mortality were compared between patients with and without ED delirium. Odds ratios with 95% confidence intervals (CIs) were calculated through logistic regression after adjusting for confounders including age, sex, history of dementia, ED disposition, and acuity. RESULTS: A total of 967 ED visits were included for analysis among which delirium was detected in 107 (11.1%). The median age of the cohort was 83 years (IQR 79, 88), 526 (54.4%) were female, 285 (29.5%) had documented dementia, and 171 (17.7%) had a high acuity Emergency Severity Index triage level 1 or 2. During the hospitalization, 5/107 (4.7%) of those with delirium and 4/860 (0.5%) of those without delirium died. Within 7 days of ED departure, 6/107 (5.6%) of those with delirium and 6/860 (0.7%) of those without delirium died (unadjusted OR 8.46, 95% CI 2.68-26.71). Within 30 days, 18/107 (16.8%) of those with delirium and 37/860 (4.3%) of those without delirium died (unadjusted OR 4.50, 95% CI 2.46-8.23). ED delirium remained associated with higher 7-day (adjusted OR 5.23, 95% CI 1.44-19.05, p = 0.008) and 30-day mortality (adjusted OR 2.82, 95% CI 1.45-5.46, p = 0.002). CONCLUSION: Delirium is an important prognostic factor that ED clinicians and nurses must be aware of to optimize delirium prevention, management, disposition, and communication with patients and families.

Racial and ethnic disparities in emergency department-initiated buprenorphine across five health care systems.

BACKGROUND: Opioid overdose deaths have disproportionately impacted Black and Hispanic populations, in part due to disparities in treatment access. Emergency departments (EDs) serve as a resource for patients with opioid use disorder (OUD), many of whom have difficulty accessing outpatient addiction programs. However, inequities in ED treatment for OUD remain poorly understood. METHODS: This secondary analysis examined racial and ethnic differences in buprenorphine access using data from EMBED, a study of 21 EDs across five health care systems evaluating a clinical decision support system for initiating ED buprenorphine. The primary outcome was receipt of buprenorphine, ED administered or prescribed. Hospital type (academic vs. community) was evaluated as an effect modifier. Hierarchical models with cluster effects for site and clinician were used to assess buprenorphine receipt by race and ethnicity. RESULTS: Black patients were less likely to receive buprenorphine (6.4% [51/801] vs. White patients 8.5% [268/3154], odds ratio [OR] 0.59, 95% confidence interval [CI] 0.45-0.78). This association persisted after adjusting for age, insurance, gender, clinician X-waiver, hospital type, and urbanicity (adjusted OR [aOR] 0.64, 95% CI 0.48-0.84) but not when discharge diagnosis was included (aOR 0.75, 95% CI 0.56-1.02). Hispanic patients were more likely to receive buprenorphine (14.8% [122/822] vs. non-Hispanic patients, 11.6% [475/4098]) in unadjusted (OR 1.57, 95% CI 1.09-1.83) and adjusted models (aOR 1.41, 95% CI 1.08-1.83) but not including discharge diagnosis (aOR 1.32, 95% CI 0.99-1.77). Odds of buprenorphine were similar in academic and community EDs by race (interaction p = 0.97) and ethnicity (interaction p = 0.64). CONCLUSIONS: Black patients with OUD were less likely to receive buprenorphine whereas Hispanic patients were more likely to receive buprenorphine in academic and community EDs. Differences were attenuated with discharge diagnosis, as fewer Black and non-Hispanic patients were diagnosed with opioid withdrawal. Barriers to medication treatment are heterogenous among patients with OUD; research must continue to address the multiple drivers of health inequities at the patient, clinician, and community level.

A prediction model for asthma exacerbations after stopping asthma biologics.

BACKGROUND: Little is known regarding the prediction of the risks of asthma exacerbation after stopping asthma biologics. OBJECTIVE: To develop and validate a predictive model for the risk of asthma exacerbations after stopping asthma biologics using machine learning models. METHODS: We identified 3057 people with asthma who stopped asthma biologics in the OptumLabs Database Warehouse and considered a wide range of demographic and clinical risk factors to predict subsequent outcomes. The primary outcome used to assess success after stopping was having no exacerbations in the 6 months after stopping the biologic. Elastic-net logistic regression (GLMnet), random forest, and gradient boosting machine models were used with 10-fold cross-validation within a development (80%) cohort and validation cohort (20%). RESULTS: The mean age of the total cohort was 47.1 (SD, 17.1) years, 1859 (60.8%) were women, 2261 (74.0%) were White, and 1475 (48.3%) were in the Southern region of the United States. The elastic-net logistic regression model yielded an area under the curve (AUC) of 0.75 (95% confidence interval [CI], 0.71-0.78) in the development and an AUC of 0.72 in the validation cohort. The random forest model yielded an AUC of 0.75 (95% CI, 0.68-0.79) in the development cohort and an AUC of 0.72 in the validation cohort. The gradient boosting machine model yielded an AUC of 0.76 (95% CI, 0.72-0.80) in the development cohort and an AUC of 0.74 in the validation cohort. CONCLUSION: Outcomes after stopping asthma biologics can be predicted with moderate accuracy using machine learning methods.

Long-Term Opioid Therapy Among Patients With Systemic Lupus Erythematosus in the Community: A Lupus Midwest Network (LUMEN) Study.

OBJECTIVE: There is little information about the epidemiology and factors associated with opioid therapy in systemic lupus erythematosus (SLE). We aimed to assess the prevalence of opioid therapy and explore factors associated with long-term opioid therapy (LTOT) in patients with SLE. METHODS: Patients with SLE were matched with controls without SLE in a population-based cohort on January 1, 2015. We captured demographics, manifestations of SLE, comorbidities (ie, fibromyalgia, mood disorders, osteoarthritis, chronic low back pain [CLBP], chronic kidney disease (CKD), avascular necrosis, osteoporosis, fragility fractures, and cancer), and the Area Deprivation Index (ADI). Opioid prescription data were used to assess the prevalence of LTOT, defined as contiguous prescriptions (gaps of < 30 days between prescriptions) and receiving opioid therapy for ≥ 90 days or ≥ 10 prescriptions before the index date. RESULTS: A total of 465 patients with SLE and 465 controls without SLE were included. In total, 13% of patients with SLE and 3% of controls without SLE were receiving opioid therapy (P < 0.001), and 11% of patients with SLE were on LTOT vs 1% of controls without SLE. Among patients with SLE, acute pericarditis (odds ratio [OR] 3.92, 95% CI 1.78-8.66), fibromyalgia (OR 7.78, 95% CI 3.89-15.55), fragility fractures (OR 3.72, 95% CI 1.25-11.07), CLBP (OR 4.00, 95% CI 2.13-7.51), and mood disorders (OR 2.76, 95% CI 1.47-5.16) were associated with LTOT. We did not find an association between opioid therapy and ADI. CONCLUSION: Patients with SLE are more likely to receive LTOT than controls. Among patients with SLE, LTOT was associated with pericarditis and several comorbidities. However, LTOT was not associated with CKD despite the limited pain control options among these patients.

Changes in all-cause and cause-specific mortality during the first year of the COVID-19 pandemic in Minnesota: population-based study.

BACKGROUND: The COVID-19 pandemic resulted in unprecedented increases in mortality in the U.S. and worldwide. To better understand the impact of the COVID-19 pandemic on mortality in the state of Minnesota, U.S.A., we characterize the changes in the causes of death during 2020 (COVID-19 period), compared to 2018-2019 (baseline period), assessing for differences across ages, races, ethnicities, sexes, and geographic characteristics. METHODS: Longitudinal population-based study using Minnesota death certificate data, 2018-2020. Using Poisson regression models adjusted for age and sex, we calculated all-cause and cause-specific (by underlying causes of death) mortality rates per 100,000 Minnesotans, the demographics of the deceased, and years of life lost (YLL) using the Chiang's life table method in 2020 relative to 2018-2019. RESULTS: We identified 89,910 deaths in 2018-2019 and 52,030 deaths in 2020. The mean daily mortality rate increased from 123.1 (SD 11.7) in 2018-2019 to 144.2 (SD 22.1) in 2020. COVID-19 comprised 9.9% of deaths in 2020. Other categories of causes of death with significant increases in 2020 compared to 2018-2019 included assault by firearms (RR 1.68, 95% CI 1.34-2.11), accidental poisonings (RR 1.49, 95% CI 1.37-1.61), malnutrition (RR 1.48, 95% CI 1.17-1.87), alcoholic liver disease (RR, 95% CI 1.14-1.40), and cirrhosis and other chronic liver diseases (RR 1.28, 95% CI 1.09-1.50). Mortality rates due to COVID-19 and non-COVID-19 causes were higher among racial and ethnic minority groups, older adults, and non-rural residents. CONCLUSIONS: The COVID-19 pandemic was associated with a 17% increase in the death rate in Minnesota relative to 2018-2019, driven by both COVID-19 and non-COVID-19 causes. As the COVID-19 pandemic enters its third year, it is imperative to examine and address the factors contributing to excess mortality in the short-term and monitor for additional morbidity and mortality in the years to come.

Comparison of emergency department throughput and process times between male and female patients: A retrospective cohort investigation by the Reducing Disparities Increasing Equity in Emergency Medicine Study Group.

Introduction: Health equity for all patients is an important characteristic of an effective healthcare system. Bias has the potential to create inequities. In this study, we examine emergency department (ED) throughput and care measures for sex-based differences, including metrics such as door-to-room (DTR) and door-to-healthcare practitioner (DTP) times to look for potential signs of systemic bias. Methods: We conducted an observational cohort study of all adult patients presenting to the ED between July 2015 and June 2017. We collected ED operational, throughput, clinical, and demographic data. Differences in the findings for male and female patients were assessed using Poisson regression and generalized estimating equations (GEEs). A priori, a clinically significant time difference was defined as 10 min. Results: A total of 106,011 adult visits to the ED were investigated. Female patients had 8-min longer median length-of-stay (LOS) than males (P < 0.01). Females had longer DTR (2-min median difference, P < 0.01), and longer DTP (5-min median difference, P < 0.01). Females had longer median door-to-over-the-counter analgesia time (84 vs. 80, P = 0.58), door-to-advanced analgesia (95 vs. 84, P < 0.01), door-to-PO (by mouth) ondansetron (70 vs. 62, P = 0.02), and door-to-intramuscular/intravenous antiemetic (76 vs. 69, P = 0.02) times compared with males. Conclusion: Numerous statistically significant differences were identified in throughput and care measures-mostly these differences favored male patients. Few of these comparisons met our criteria for clinical significance.

Demographic Trends in Emergency Department Visits for Psychiatric Concerns During the COVID-19 Pandemic.

Objective: To describe changes in emergency department (ED) psychiatric visits during the pandemic in both rural and nonrural regions in the United States. Methods: This cohort study was performed across 22 EDs in the Midwest and Southern United States from January 1, 2019 to April 22, 2021. Prevalence of psychiatric visits before and after the COVID-19 pandemic, defined as starting on March 1, 2020, were compared. Psychiatric and nonpsychiatric visits were defined on the basis of primary clinician-assigned diagnosis. The primary end point was average daily visits normalized to the average daily visit count before the pandemic, labeled as relative mean daily visits (RMDVs). Results: Psychiatric visits decreased by 9% [RMDVs, 0.91; 95% confidence interval (CI), 0.89-0.93] during the pandemic period, whereas nonpsychiatric visits decreased by 17% (RMDVs, 0.83; 95% CI, 0.81-0.84). Black patients were the only demographic group with a significant increase in psychiatric visits during the pandemic (RMDVs, 1.12; 95% CI, 1.04-1.19). Periods of outbreaks of psychiatric emergencies were identified in most demographic groups, including among male and pediatric patients. However, the outbreaks detected among Black patients sustained the longest at 6 months. Unlike older adults who experienced outbreaks in the spring and fall of 2020, outbreaks among pediatric patients were detected later in 2021. Conclusion: In this multisite study, total ED visits declined during the pandemic; however, psychiatric visits declined less than nonpsychiatric visits. Black patients experienced a greater increase in psychiatric emergencies than other demographic groups. There is also a concern for increasing outbreaks of pediatric psychiatric visits as the pandemic progresses.

User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial.

OBJECTIVE: To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder. DESIGN: Pragmatic cluster randomized controlled trial (EMBED). SETTING: 18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform. PARTICIPANTS: 599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder. INTERVENTION: A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral. MAIN OUTCOME MEASURES: Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework. RESULTS: 1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01). CONCLUSIONS: User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT03658642.

Association between emergency department modifiable risk factors and subsequent delirium among hospitalized older adults.

STUDY OBJECTIVE: To evaluate the association between potential emergency department (ED)-based modifiable risk factors and subsequent development of delirium among hospitalized older adults free of delirium at the time of ED stay. METHODS: Observational cohort study of patients aged ≥75 years who screened negative for delirium in the ED, were subsequently admitted to the hospital, and had delirium screening performed within 48 h of admission. Potential ED-based risk factors for delirium included ED length of stay (LOS), administration of opioids, benzodiazepines, antipsychotics, or anticholinergics, and the placement of urinary catheter while in the ED. Odds ratios (OR) and mean differences (MD) with 95% confidence intervals (CIs) were calculated. RESULTS: Among 472 patients without delirium in the ED (mean age 84 years, 54.2% females), 33 (7.0%) patients developed delirium within 48 h of hospitalization. The ED LOS of those who developed delirium was similar to those who did not develop delirium (312.1 vs 325.6 min, MD -13.5 min, CI -56.1 to 29.0). Patients who received opioids in the ED were as likely to develop delirium as those who did not receive opioids (7.2% vs 6.9%: OR 1.04, CI 0.44 to 2.48). Patients who received benzodiazepines had a higher risk of incident delirium, the difference was clinically but not statistically significant (37.3% vs 6.5%, OR 5.35, CI 0.87 to 23.81). Intermittent urinary catheterization (OR 2.05, CI 1.00 to 4.22) and Foley placement (OR 3.69, CI 1.55 to 8.80) were associated with a higher risk of subsequent delirium. After adjusting for presence of dementia, only Foley placement in the ED remained significantly associated with development of in-hospital delirium (adjusted OR 3.16, CI 1.22 to 7.53). CONCLUSION: ED LOS and ED opioid use were not associated with higher risk of incident delirium in this cohort. Urinary catheterization in the ED was associated with an increased risk of subsequent delirium. These findings can be used to design ED-based initiatives and increase delirium prevention efforts.

REcognizing DElirium in geriatric Emergency Medicine: The REDEEM risk stratification score.

OBJECTIVE: The objective was to derive a risk score that uses variables available early during the emergency department (ED) encounter to identify high-risk geriatric patients who may benefit from delirium screening. METHODS: This was an observational study of older adults age ≥ 75 years who presented to an academic ED and who were screened for delirium during their ED visit. Variable selection from candidate predictors was performed through a LASSO-penalized logistic regression. A risk score was derived from the final prediction model, and predictive accuracy characteristics were calculated with 95% confidence intervals (CIs). RESULTS: From the 967 eligible ED visits, delirium was detected in 107 (11.1%). The area under the curve for the REcognizing DElirium in Emergency Medicine (REDEEM) score was 0.901 (95% CI = 0.864-0.938). The REEDEM risk score included 10 different variables (seven based on triage information and three obtained during early history taking) with a score ranging from -3 to 66. Using an optimal cutoff of ≥11, we found a sensitivity of 84.1% (90 of 107 ED delirium patients, 95% CI = 75.5%-90.2%) and a specificity of 86.6% (745 of 860 non-ED delirium patients, 95% CI = 84.1%-88.8%). A lower cutoff of ≥5 was found to minimize false negatives with an improved sensitivity at 91.6% (98 of 107 ED delirium patients, 95% CI = 84.2%-95.8%). CONCLUSION: A risk stratification score was derived with the potential to augment delirium recognition in geriatric ED patients. This has the potential to assist on delirium-targeted screening of high-risk patients in the ED. Validation of REDEEM, however, is needed prior to implementation.

Emergency Department Visits for Nonfatal Opioid Overdose During the COVID-19 Pandemic Across Six US Health Care Systems.

STUDY OBJECTIVE: People with opioid use disorder are vulnerable to disruptions in access to addiction treatment and social support during the COVID-19 pandemic. Our study objective was to understand changes in emergency department (ED) utilization following a nonfatal opioid overdose during COVID-19 compared to historical controls in 6 healthcare systems across the United States. METHODS: Opioid overdoses were retrospectively identified among adult visits to 25 EDs in Alabama, Colorado, Connecticut, North Carolina, Massachusetts, and Rhode Island from January 2018 to December 2020. Overdose visit counts and rates per 100 all-cause ED visits during the COVID-19 pandemic were compared with the levels predicted based on 2018 and 2019 visits using graphical analysis and an epidemiologic outbreak detection cumulative sum algorithm. RESULTS: Overdose visit counts increased by 10.5% (n=3486; 95% confidence interval [CI] 4.18% to 17.0%) in 2020 compared with the counts in 2018 and 2019 (n=3020 and n=3285, respectively), despite a 14% decline in all-cause ED visits. Opioid overdose rates increased by 28.5% (95% CI 23.3% to 34.0%) from 0.25 per 100 ED visits in 2018 to 2019 to 0.32 per 100 ED visits in 2020. Although all 6 studied health care systems experienced overdose ED visit rates more than the 95th percentile prediction in 6 or more weeks of 2020 (compared with 2.6 weeks as expected by chance), 2 health care systems experienced sustained outbreaks during the COVID-19 pandemic. CONCLUSION: Despite decreases in ED visits for other medical emergencies, the numbers and rates of opioid overdose-related ED visits in 6 health care systems increased during 2020, suggesting a widespread increase in opioid-related complications during the COVID-19 pandemic. Expanded community- and hospital-based interventions are needed to support people with opioid use disorder and save lives during the COVID-19 pandemic.