Health Care Use Among Patients Retroactively Insured via a Hospital-Based Insurance Linkage Program.

OBJECTIVE: Over 25% of the 27 million uninsured individuals in the United States are eligible for Medicaid. Many hospitals have insurance linkage programs that assist eligible patients with enrollment, but little is known about the impact of these programs on care utilization. This research assessed health care utilization and health outcomes among patients enrolled in Medicaid via a hospital-based insurance linkage program. METHODS: This retrospective cohort study included adults aged 18-64 admitted to the hospital from 2016 to 2021. Those who obtained insurance retroactively via insurance linkage (RI) were compared with those who presented with Medicaid (MI) or remained uninsured (UI). The primary outcome was the presence of at least one visit with a primary care provider (PCP) in the 12 months following index admission. Secondary outcomes included having an assigned PCP, ED revisits, and hospital readmissions. For patients with diabetes and hypertension, 12-month hemoglobin A1c (HbA1c) and blood pressure (BP) readings were tracked. RESULTS: Of 3882 patients admitted with no insurance, 2905 (74.8%) were enrolled in insurance (RI). In multivariable analysis, RI patients were 14% more likely (OR 1.14, p = 0.020) to have completed at least one PCP visit by 12 months after index admission compared to those with preexisting Medicaid (MI), and uninsured patients were 29% less likely (OR 0.71, p = 0.003). MI and RI patients also had more ED revisits (p < 0.001) and greater 12-month reductions in blood pressure (p < 0.001) compared with uninsured patients. CONCLUSION: Hospital-based insurance linkage reached three-quarters of uninsured patients and was associated with increased utilization of acute and outpatient health care services. An acute care encounter represents an opportunity to connect patients to insurance, a key step toward improving their health outcomes.

Association between patient-reported onset-to-door time and mortality in patients hospitalized with COVID-19 disease.

INTRODUCTION: Timely hospital presentation and treatment are critical for recovery from coronavirus disease (COVID-19). However, the relationship between symptom onset-to-door time and key clinical outcomes, such as inpatient mortality, has been poorly understood due to the difficulty of retrospectively measuring symptom onset in observational data. This study examines the association between patient-reported symptom onset-to-door time (ODT) and mortality among patients hospitalized and treated for COVID-19 disease. METHODS: We conducted a retrospective cohort study of emergency department (ED) encounters of patients with COVID-19 disease who were hospitalized and received remdesivir and/or dexamethasone between March 1, 2020, and March 1, 2022. The exposure was patient-reported ODT in days. The outcome of interest was inpatient mortality, including referral to hospice care. We used multivariable logistic regression to examine the association between ODT and mortality while adjusting for patient characteristics, hospital sites, and seasonality. We tested whether severe illness on hospital presentation modified the association between ODT and mortality. Severe illness was defined by Emergency Severity Index triage level 1 or 2 and hypoxia (SpO2 < 94%). RESULTS: Of the 3451 ED hospitalizations included, 439 (12.7%) resulted in mortality, and 1693 (49.1%) involved patients with severe illness on hospital presentation. Greater ODT was significantly associated with lower odds of inpatient mortality (adjusted odds ratio (AOR) = 0.96, 95% CI = 0.93-1.00, P = 0.023). There was a statistically significant interaction between ODT and severe illness at hospital arrival on mortality, suggesting the negative association between ODT and mortality specifically pertained to patients who were not severely ill upon ED presentation (AOR = 0.93, 95% CI = 0.87-1.00, P = 0.035). The adjusted probability of mortality was significantly lower for non-severely ill, hospitalized patients who presented on days 8-14 (5.2%-3.3%) versus days 0-3 (9.4%-7.5%) after symptom onset. CONCLUSION: More days between symptom onset and hospital arrival were associated with lower mortality among hospitalized patients treated for COVID-19 disease, particularly if they did not have severe illness at ED presentation. However, onset-to-door time was not associated with mortality among hospitalized patients with severe illness at ED presentation. Collectively, these results suggest that non-severely ill COVID-19 patients who require hospitalization are less likely to decompensate with each passing day without severe illness. These findings may continue to guide clinical care delivery for hospitalized COVID-19 patients.

Trends in Before Medically Advised Discharges for Patients With Opioid Use Disorder, 2016-2020.

This study examines discharge trends for opioid-related admissions from 2016-2020 with a focus on admissions with opioid use disorder and an injection-related infection.

Identifying Patient Characteristics Associated With Opioid Use to Inform Surgical Pain Management.

Objective: Balancing surgical pain management and opioid stewardship is complex. Identifying patient-level variables associated with low or no use can inform tailored prescribing. Methods: A prospective, observational study investigating surgical procedures, prescription data, and patient-reported outcomes at an academic health system in Pennsylvania. Surgical patients were consented following surgery, and prospective data were captured using automated text messaging (May 1, 2021-February 29, 2022). The primary outcome was opioid use. Results: Three thousand six hundred three (30.2%) patients consented. Variation in patient reported used included 28.1% of men reported zero use versus 24.3% of women, 20.5% of Black patients reported zero use versus 27.2% of white patients. Opioid-naïve patients reported more zero use as compared with chronic use (29.7% vs 9.8%). Patients reporting higher use had more telephone calls and office visits within 30 days but no change in emergency department utilization or admissions. Higher discharge pain score was associated with higher use. In the adjusted analysis, opioid use relative to the guideline, higher use was associated with age, male sex, obesity, discharge pain score, and history of mental health disorder. In the adjusted model, younger age and being opioid-naïve to be associated with low to zero use across procedures. Conclusions: Younger age, being opioid-naïve, and lower discharge pain score are associated with low or no postoperative opioid use. These characteristics can be used by clinicians to help tailor opioid prescribing to specific patients to reduce the risk of prolonged exposure and unused `ts in the community.

Association of Urine Fentanyl Concentration With Severity of Opioid Withdrawal Among Patients Presenting to the Emergency Department.

BACKGROUND AND AIMS: Fentanyl is involved in most US drug overdose deaths and its use can complicate opioid withdrawal management. Clinical applications of quantitative urine fentanyl testing have not been demonstrated previously. The aim of this study was to determine whether urine fentanyl concentration is associated with severity of opioid withdrawal. DESIGN: This is a retrospective cross-sectional study. SETTING: This study was conducted in 3 emergency departments in an urban, academic health system from January 1, 2020, to December 31, 2021. PARTICIPANTS: This study included patients with opioid use disorder, detectable urine fentanyl or norfentanyl, and Clinical Opiate Withdrawal Scale (COWS) recorded within 6 hours of urine drug testing. MEASUREMENTS: The primary exposure was urine fentanyl concentration stratified as high (>400 ng/mL), medium (40-399 ng/mL), or low (<40 ng/mL). The primary outcome was opioid withdrawal severity measured with COWS within 6 hours before or after urine specimen collection. We used a generalized linear model with γ distribution and log-link function to estimate the adjusted association between COWS and the exposures. FINDINGS: For the 1127 patients in our sample, the mean age (SD) was 40.0 (10.7), 384 (34.1%) identified as female, 332 (29.5%) reported their race/ethnicity as non-Hispanic Black, and 658 (58.4%) reported their race/ethnicity as non-Hispanic White. For patients with high urine fentanyl concentrations, the adjusted mean COWS (95% confidence interval) was 4.4 (3.9-4.8) compared with 5.5 (5.1-6.0) among those with medium and 7.7 (6.8-8.7) among those with low fentanyl concentrations. CONCLUSIONS: Lower urine fentanyl concentration was associated with more severe opioid withdrawal, suggesting potential clinical applications for quantitative urine measurements in evolving approaches to fentanyl withdrawal management.

Frequency and Trends of Pre-Pandemic Surge Periods in U.S. Emergency Departments, 2006-2019.

OBJECTIVES: To quantify the frequency, outside of the pandemic setting, with which individual healthcare facilities faced surge periods due to severe increases in demand for emergency department (ED) care. DESIGN: Retrospective cohort study. SETTING: U.S. EDs. PATIENTS: All ED encounters in the all-payer, nationally representative Nationwide Emergency Department Sample from the Healthcare Cost and Utilization Project, 2006-2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Frequency of surge periods defined as ED months in which an individual facility ED saw a greater than 50% increase in ED visits per month above facility-/calendar month-specific medians. During 2006-2019, 3,317 U.S. EDs reported 354,534,229 ED visits across 142,035 ED months. Fifty-seven thousand four hundred ninety-five ED months (40.5%) during the study period had a 0% to 50% increase in ED visits that month above facility-specific medians and 1,952 ED months (1.4%) qualified as surge periods and had a greater than 50% increase in ED visits that month above facility-specific medians. These surge months were experienced by 397 unique facility EDs (12.0%). Compared with 2006, the most proximal pre-pandemic period of 2016-2019 had a notably elevated likelihood of ED-month surge periods (odds ratios [ORs], 2.36-2.84; all p < 0.0005). Compared with the calendar month of January, the winter ED months in December through March have similar likelihood of an ED-month qualifying as a surge period (ORs, 0.84-1.03; all p > 0.05), while the nonwinter ED months in April through November have a lower likelihood of an ED-month qualifying as a surge period (ORs, 0.65-0.81; all p < 0.05). CONCLUSIONS: Understanding the frequency of surges in demand for ED care-which appear to have increased in frequency even before the COVID-19 pandemic and are concentrated in winter months-is necessary to better understand the burden of potential and realized acute surge events and to inform cost-effectiveness preparedness strategies.

Patient and clinician perspectives of a remote monitoring program for COVID-19 and lessons for future programs.

COVID Watch is a remote patient monitoring program implemented during the pandemic to support home dwelling patients with COVID-19. The program conferred a large survival advantage. We conducted semi-structured interviews of 85 patients and clinicians using COVID Watch to understand how to design such programs even better. Patients and clinicians found COVID Watch to be comforting and beneficial, but both groups desired more clarity about the purpose and timing of enrollment and alternatives to text-messages to adapt to patients' preferences as these may have limited engagement and enrollment among marginalized patient populations. Because inclusiveness and equity are important elements of programmatic success, future programs will need flexible and multi-channel human-to-human communication pathways for complex clinical interactions or for patients who do not desire tech-first approaches.

How Physician Self-Perceptions Affect the Impact of Peer Comparison Feedback on Opioid Prescribing.

Peer comparison feedback is a promising strategy for reducing opioid prescribing and opioid-related harms. Such comparisons may be particularly impactful among underestimating clinicians who do not perceive themselves as high prescribers relative to their peers. But peer comparisons could also unintentionally increase prescribing among overestimating clinicians who do not perceive themselves as lower prescribers than peers. The objective of this study was to assess if the impact of peer comparisons varied by clinicians' preexisting opioid prescribing self-perceptions. Subgroup analysis of a randomized trial of peer comparison interventions among emergency department and urgent care clinicians was used. Generalized mixed-effects models were used to assess whether the impact of peer comparisons, alone or combined with individual feedback, varied by underestimating or overestimating prescriber status. Underestimating and overestimating prescribers were defined as those who self-reported relative prescribing amounts that were lower and higher, respectively, than actual relative baseline amounts. The primary outcome was pills per opioid prescription. Among 438 clinicians, 54% (n = 236) provided baseline prescribing self-perceptions and were included in this analysis. Overall, 17% (n = 40) were underestimating prescribers whereas 5% (n = 11) were overestimating prescribers. Underestimating prescribers exhibited a differentially greater decrease in pills per prescription compared to nonunderestimating clinicians when receiving peer comparison feedback (1.7 pills, 95% CI, -3.2 to -0.2 pills) or combined peer and individual feedback (2.8 pills, 95% CI, -4.8 to -0.8 pills). In contrast, there were no differential changes in pills per prescription for overestimating versus nonoverestimating prescribers after receiving peer comparison (1.5 pills, 95% CI, -0.9 to 3.9 pills) or combined peer and individual feedback (3.0 pills, 95% CI, -0.3 to 6.2 pills). Peer comparisons were more impactful among clinicians who underestimated their prescribing compared to peers. By correcting inaccurate self-perceptions, peer comparison feedback can be an effective strategy for influencing opioid prescribing.

Disparities in emergency department and urgent care opioid prescribing before and after randomized clinician feedback interventions.

OBJECTIVES: Racial and ethnic minorities receive opioid prescriptions at lower rates and dosages than White patients. Though opioid stewardship interventions can improve or exacerbate these disparities, there is little evidence about these effects. We conducted a secondary analysis of a cluster-randomized controlled trial conducted among 438 clinicians from 21 emergency departments and 27 urgent care clinics. Our objective was to determine whether randomly allocated opioid stewardship clinician feedback interventions that were designed to reduce opioid prescriptions had unintended effects on disparities in prescribing by patient race and ethnicity. METHODS: The primary outcome was likelihood of receiving a low-pill prescription (low ≤10 pills, medium 11-19 pills, high ≥20 pills). Generalized mixed-effects models were used to determine patient characteristics associated with low-pill prescriptions during the baseline period. These models were then used to determine whether receipt of a low-pill prescription varied by patient race or ethnicity during the intervention period between usual care and three opioid stewardship interventions: (1) individual audit feedback, (2) peer comparison feedback, and (3) combined (individual audit + peer comparison) feedback. RESULTS: Compared with White patients, Black patients were more likely to receive a low-pill prescription during the baseline (adjusted odds ratio [OR] 1.18, 95% confidence interval [CI] 1.06-1.31, p = 0.002) and intervention (adjusted OR 1.43, 95% CI 1.07-1.91, p = 0.015). While combined feedback was associated with an overall increase in low-pill prescriptions as intended (adjusted OR 1.89, 95% CI 1.28-2.78, p = 0.001), there were no significant differences in treatment effects of any of the interventions by patient race and ethnicity. CONCLUSIONS: Combined individual audit and peer comparison feedback was associated with fewer opioid pills per prescription equally by patient race and ethnicity. However, the intervention did not significantly close the baseline disparity in prescribing by race.

The impact of Illinois' comprehensive handheld phone ban on talking on handheld and handsfree cellphones while driving.

INTRODUCTION: Distracted driving has been linked to multiple driving decrements and is responsible for thousands of motor-vehicle fatalities annually. Most U.S. states have enacted restrictions on cellphone use while driving, the strictest of which prohibit any manual operation of a cellphone while driving. Illinois enacted such a law in 2014. To better understand how this law affected cellphone behaviors while driving, associations between Illinois' handheld phone ban and self-reported talking on handheld, handsfree, and any cellphone (handheld or handsfree) while driving were estimated. METHODS: Data from annual administrations of the Traffic Safety Culture Index from 2012-2017 in Illinois and a set of control states were leveraged. The data were cast into a difference-in-differences (DID) modeling framework, which compared Illinois to control states in terms of pre- to post-intervention changes in the proportion of drivers who self-reported the three outcomes. Separate models for each outcome were fit, and additional models were fit to the subset of drivers who talk on cellphones while driving. RESULTS: In Illinois, the pre- to post-intervention decrease in the drivers' probability of self-reporting talking on a handheld phone was significantly more extreme than that of drivers in control states (DID estimate -0.22; 95% CI -0.31, -0.13). Among drivers who talk on cellphones while driving, those in Illinois exhibited a more extreme increase in the probability of talking on a handsfree phone while driving than those control states (DID estimate 0.13; 95% CI 0.03, 0.23). CONCLUSIONS: These results suggest that Illinois' handheld phone ban reduced talking on handheld phones while driving among study participants. They also corroborate the hypothesis that the ban promoted substitution from handheld to handsfree phones among drivers who talk on the phone while driving. PRACTICAL APPLICATIONS: These findings should encourage other states to enact comprehensive handheld phone bans to improve traffic safety.

How have firearm laws changed in states with unexpected decreases or increases in firearm homicide, 1990-2019?

Background: Firearm violence is one of the leading preventable causes of death and injury in the United States and is on the rise. While policies regulating access to firearms offer opportunities to prevent firearm-related deaths, an understanding of the holistic impact of changing state firearm policies on firearm homicide rates over the last 30 years is limited. Objectives: To identify US states that showed unexpected decreases and increases in firearm homicide rates and summarise their firearm policy changes in the last three decades. Methods: We analysed changes in firearm homicide rates by US state and county from 1990 to 2019. We triangulated across three estimation approaches to derive state rankings and identify the top and bottom three states which consistently showed unexpected decreases (low outliers) and increases (high outliers) in firearm homicide rates. We summarised firearm policy changes in state outliers using the RAND State Firearm Law Database. Results: We identified New York, District of Columbia, and Hawaii as low state outliers and Delaware, New Jersey, and Missouri as high state outliers. Low state outliers made more restrictive firearm policy changes than high state outliers, which covered a wider range of policy types. Restrictive changes in high state outliers primarily targeted high-risk populations (e.g., prohibited possessors, safe storage). Specific legislative details, such as the age threshold (18 vs 21 years old) for firearm minimum age requirements, also emerged as important for differentiating low from high state outliers. Conclusions: While no firearm law change emerged as necessary or sufficient, an accumulation of diverse restrictive firearm policies may be key to alleviating the death toll from firearm homicide.

Are There Differences in Postoperative Opioid Prescribing Across Racial and Ethnic Groups? Assessment of an Academic Health System.

BACKGROUND: Previous studies have demonstrated racial disparities in opioid prescribing in emergency departments and after surgical procedures. Orthopaedic surgeons account for a large proportion of dispensed opioid prescriptions, yet there are few data investigating whether racial or ethnic disparities exist in opioid dispensing after orthopaedic procedures. QUESTIONS/PURPOSES: (1) Are Black, Hispanic or Latino, or Asian or Pacific Islander (PI) patients less likely than non-Hispanic White patients to receive an opioid prescription after an orthopaedic procedure in an academic United States health system? (2) Of the patients who do receive a postoperative opioid prescription, do Black, Hispanic or Latino, or Asian or PI patients receive a lower analgesic dose than non-Hispanic White patients when analyzed by type of procedure performed? METHODS: Between January 2017 and March 2021, 60,782 patients underwent an orthopaedic surgical procedure at one of the six Penn Medicine healthcare system hospitals. Of these patients, we considered patients who had not been prescribed an opioid within 1 year eligible for the study, resulting in 61% (36,854) of patients. A total of 40% (24,106) of patients were excluded because they did not undergo one of the top eight most-common orthopaedic procedures studied or their procedure was not performed by a Penn Medicine faculty member. Missing data consisted of 382 patients who had no race or ethnicity listed in their record or declined to provide a race or ethnicity; these patients were excluded. This left 12,366 patients for analysis. Sixty-five percent (8076) of patients identified as non-Hispanic White, 27% (3289) identified as Black, 3% (372) identified as Hispanic or Latino, 3% (318) identified as Asian or PI, and 3% (311) identified as another race ("other"). Prescription dosages were converted to total morphine milligram equivalents for analysis. Statistical differences in receipt of a postoperative opioid prescription were assessed with multivariate logistic regression models within procedure, adjusted for age, gender, and type of healthcare insurance. Kruskal-Wallis tests were used to assess for differences in the total morphine milligram equivalent dosage of the prescription, stratified by procedure. RESULTS: Almost all patients (95% [11,770 of 12,366]) received an opioid prescription. After risk adjustment, we found no differences in the odds of Black (odds ratio 0.94 [95% confidence interval 0.78 to 1.15]; p = 0.68), Hispanic or Latino (OR 0.75 [95% CI 0.47 to 1.20]; p = 0.18), Asian or PI (OR 1.00 [95% CI 0.58 to 1.74]; p = 0.96), or other-race patients (OR 1.33 [95% CI 0.72 to 2.47]; p = 0.26) receiving a postoperative opioid prescription compared with non-Hispanic White patients. There were no race or ethnicity differences in the median morphine milligram equivalent dose of postoperative opioid analgesics prescribed (p > 0.1 for all eight procedures) based on procedure. CONCLUSION: In this academic health system, we did not find any differences in opioid prescribing after common orthopaedic procedures by patient race or ethnicity. A potential explanation is the use of surgical pathways in our orthopaedic department. Formal standardized opioid prescribing guidelines may reduce variability in opioid prescribing. LEVEL OF EVIDENCE: Level III, therapeutic study.

Hospital Strain and Variation in Sepsis ICU Admission Practices and Associated Outcomes.

To understand how strain-process-outcome relationships in patients with sepsis may vary among hospitals. DESIGN: Retrospective cohort study using a validated hospital capacity strain index as a within-hospital instrumental variable governing ICU versus ward admission, stratified by hospital. SETTING: Twenty-seven U.S. hospitals from 2013 to 2018. PATIENTS: High-acuity emergency department patients with sepsis who do not require life support therapies. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The mean predicted probability of ICU admission across strain deciles ranged from 4.9% (lowest ICU-utilizing hospital for sepsis without life support) to 61.2% (highest ICU-utilizing hospital for sepsis without life support). The difference in the predicted probabilities of ICU admission between the lowest and highest strain deciles ranged from 9.0% (least strain-sensitive hospital) to 45.2% (most strain-sensitive hospital). In pooled analyses, emergency department patients with sepsis (n = 90,150) experienced a 1.3-day longer median hospital length of stay (LOS) if admitted initially to the ICU compared with the ward, but across the 27 study hospitals (n = 517-6,564), this effect varied from 9.0 days shorter (95% CI, -10.8 to -7.2; p < 0.001) to 19.0 days longer (95% CI, 16.7-21.3; p < 0.001). Corresponding ranges for inhospital mortality with ICU compared with ward admission revealed odds ratios (ORs) from 0.16 (95% CI, 0.03-0.99; p = 0.04) to 4.62 (95% CI, 1.16-18.22; p = 0.02) among patients with sepsis (pooled OR = 1.48). CONCLUSIONS: There is significant among-hospital variation in ICU admission rates for patients with sepsis not requiring life support therapies, how sensitive those ICU admission decisions are to hospital capacity strain, and the association of ICU admission with hospital LOS and hospital mortality. Hospital-level heterogeneity should be considered alongside patient-level heterogeneity in critical and acute care study design and interpretation.

Safety and preliminary outcomes of short-acting opioid agonist treatment (sOAT) for hospitalized patients with opioid use disorder.

BACKGROUND: Patients with opioid use disorder (OUD) frequently leave the hospital as patient directed discharges (PDDs) because of untreated withdrawal and pain. Short-acting opioids can complement methadone, buprenorphine, and non-opioid adjuvants for withdrawal and pain, however little evidence exists for this approach. We described the safety and preliminary outcomes of short-acting opioid agonist treatment (sOAT) for hospitalized patients with OUD at an academic hospital in Philadelphia, PA. METHODS: From August 2021 to March 2022, a pharmacist guided implementation of a pilot sOAT protocol consisting of escalating doses of oxycodone or oral hydromorphone scheduled every four hours, intravenous hydromorphone as needed, and non-opioid adjuvants for withdrawal and pain. All patients were encouraged to start methadone or buprenorphine treatment for OUD. We abstracted data from the electronic health record into a secure platform. The primary outcome was safety: administration of naloxone, over-sedation, or a fall. Secondary outcomes were PDDs and respective length of stay (LOS), discharges on methadone or buprenorphine, and discharges with naloxone. We compared secondary outcomes to hospitalizations in the 12 months prior to the index hospitalization among the same cohort. RESULTS: Of the 23 cases, 13 (56.5%) were female, 19 (82.6%) were 40 years or younger, and 22 (95.7%) identified as White. Twenty-one (91.3%) regularly injected opioids and four (17.3%) were enrolled in methadone or buprenorphine prior to hospitalization. sOAT was administered at median doses of 200-320 morphine milligram equivalents per 24-h period. Naloxone administration was documented once in the operating room, over-sedation was documented once after unsanctioned opioid use, and there were no falls. The PDD rate was 44% with median LOS 5 days (compared to PDD rate 69% with median LOS 3 days for prior admissions), 65% of sOAT cases were discharged on buprenorphine or methadone (compared to 33% for prior admissions), and 65% of sOAT cases were discharged with naloxone (compared to 19% for prior admissions). CONCLUSIONS: Pilot implementation of sOAT was safe. Compared to prior admissions in the same cohort, the PDD rate was lower, LOS for PDDs was longer, and more patients were discharged on buprenorphine or methadone and with naloxone, however efficacy for these secondary outcomes remains to be established.

Precipitated opioid withdrawal after buprenorphine administration in patients presenting to the emergency department: A case series.

Objectives: Buprenorphine is a highly effective medication for the treatment of opioid use disorder, but it can cause precipitated withdrawal (PW) from opioids. Incidence, risk factors, and best approaches to management of PW are not well understood. Our objective was to describe adverse outcomes after buprenorphine administration among emergency department (ED) patients and assess whether they met the criteria for PW. Methods: This study is a case series using retrospective chart review in a convenience sample of patients from 3 hospitals in an urban academic health system. This study included patients who were reported by clinicians as potential cases of PW. Relevant clinical data were abstracted from the electronic health record using a structured retrospective chart review instrument. Results: A total of 13 cases were included and classified into the following 3 categories: (1) PW after buprenorphine administration consistent with guidelines (n = 5), (2) PW after deviating from guidelines (n = 4), and (3) protracted opioid withdrawal with no increase in Clinical Opiate Withdrawal Scale score (n = 4). A total of 11 patients had urine drug testing positive for fentanyl, and 11 patients received additional doses of buprenorphine for symptom management. Of the patients, 5 had self-directed hospital discharges, and 6 were ultimately discharged with prescriptions for buprenorphine. Conclusions: Cases of adverse outcomes after buprenorphine administration in the ED and hospital meet criteria for PW, although some cases may have represented protracted opioid withdrawal. Further investigation into the incidence, risk factors, management of PW as well as patient perspectives is needed to expand and sustain the use of buprenorphine in EDs and hospitals.