Follow-up after ED visits for opioid use disorder: Do they reduce future overdoses?

Pathways of care following opioid overdose among people with opioid use disorder: A multilevel cohort study

BACKGROUND

The care that people with opioid use disorder (OUD) receive during hospitalizations for opioid overdoses present opportunities for support, yet initiation of opioid agonist treatment (OAT) remains low. Therefore, we sought to determine factors associated with treatment initiation following hospitalization for an opioid overdose.

METHODS

We conducted a population-based cohort study of people with OUD discharged from hospital following an opioid overdose between January 1, 2014 and December 31, 2021 in Ontario, Canada. Our primary outcome was initiation of treatment (OAT and/or safer opioid supply) within 30 days of discharge. Proportional hazards frailty models were used to account for the clustering of hospital and geographic-level variables with cause-specific hazards ratios calculated for each factor.

RESULTS

Overall, 13,253 individuals experienced 22,848 opioid overdoses and were discharged from 175 hospitals across Ontario. Treatment was initiated in 10.3 % of opioid overdoses. Person-related variables associated with treatment initiation included hepatitis C diagnoses (HR=1.15, 95 % CI=1.01-1.30) and public drug benefit eligibility (HR=1.50, 95 % CI=1.36-1.66). Longer stays in hospital were also associated with a significant increase in treatment initiation over the first 10 days of follow-up only (HR=1.10 per 5 days in hospital; 95 % CI=1.06-1.15). People discharged from regions with the highest quantile of fatal opioid overdose rates had an increased hazard of treatment initiation (HR=1.26; 95 % CI=1.06-1.51), compared to regions in the lowest quantile.

CONCLUSION

The identification of factors associated with treatment initiation following overdose may be associated with promoting longer stays in hospital and enhancing accessibility in regions with less experience managing opioid overdoses.

Development and evaluation of a machine learning model to predict acute care for opioid use disorder among Medicaid enrollees engaged in a community-based treatment program

AIMS

To develop machine-learning algorithms for predicting the risk of a hospitalization or emergency department (ED) visit for opioid use disorder (OUD) (i.e. OUD acute events) in Pennsylvania Medicaid enrollees in the Opioid Use Disorder Centers of Excellence (COE) program and to evaluate the fairness of model performance across racial groups.

METHODS

We studied 20 983 United States Medicaid enrollees aged 18 years or older who had COE visits between April 2019 and March 2021. We applied multivariate logistic regression, least absolute shrinkage and selection operator models, random forests, and eXtreme Gradient Boosting (XGB), to predict OUD acute events following the initial COE visit. Our models included predictors at the system, patient, and regional levels. We assessed model performance using multiple metrics by racial groups. Individuals were divided into a low, medium and high-risk group based on predicted risk scores.

RESULTS

The training (n = 13 990) and testing (n = 6993) samples displayed similar characteristics (mean age 38.1 ± 9.3 years, 58% male, 80% White enrollees) with 4% experiencing OUD acute events at baseline. XGB demonstrated the best prediction performance (C-statistic = 76.6% [95% confidence interval = 75.6%-77.7%] vs. 72.8%-74.7% for other methods). At the balanced cutoff, XGB achieved a sensitivity of 68.2%, specificity of 70.0%, and positive predictive value of 8.3%. The XGB model classified the testing sample into high-risk (6%), medium-risk (30%), and low-risk (63%) groups. In the high-risk group, 40.7% had OUD acute events vs. 16.5% and 5.0% in the medium- and low-risk groups. The high- and medium-risk groups captured 44% and 26% of individuals with OUD events. The XGB model exhibited lower false negative rates and higher false positive rates in racial/ethnic minority groups than White enrollees.

CONCLUSIONS

New machine-learning algorithms perform well to predict risks of opioid use disorder (OUD) acute care use among United States Medicaid enrollees and improve fairness of prediction across racial and ethnic groups compared with previous OUD-related models.

Initiation of extended-release buprenorphine in emergency department patients: A retrospective cohort study

OBJECTIVE

To determine the outcomes of emergency department (ED) patients with opioid use disorder (OUD) who were treated with high dose sublingual and subcutaneous buprenorphine and admitted to an inpatient withdrawal management unit (WiMU).

METHODS

We conducted a retrospective chart review of patients with OUD who presented to the ED of the Timmins and District Hospital (TADH) and who had received high (minimum 16 mg, no upper bound) dose sublingual buprenorphine (SL bup), administration of 300 mg injectable extended-release buprenorphine (ER bup), and admission to the WiMu.

RESULTS

Ninety patients met the inclusion criteria: the majority were fentanyl users (98 %) and Indigenous (61 %). There were no adverse events, including precipitated withdrawal, as a result of receiving high dose SL bup and ER bup. Treatment retention at 3, 6, and 12 months was 58 %, 44 %, and 36 % respectively. In the year following treatment initiation, there was a reduction in non-fatal overdoses (21.9 %, p = 0.0018), ED visits (78.1 %, p < 0.0001), and hospitalizations (77.1 %, p < 0.0001) compared to the year prior to treatment initiation.

CONCLUSIONS

In patients with OUD presenting to a community ED, a treatment regimen of high dose SL bup and ER bup, and admission to a designated unit resulted in significantly reduced nonfatal overdoses, ED visits, and hospitalizations at one year.

Advancing Health Equity Through Substance Use Medical Record Data Sharing: Insights from Healthcare Providers

BACKGROUND

Better care is delivered when patients and providers share health information. Unfortunately, critical health data are often unavailable due to fragmentation within healthcare systems. Sensitive health information, like substance use disorder, is often sequestered in ways that do not meet patient data privacy choices and provider data access needs. This study explored healthcare providers' perspectives on barriers and facilitators to substance use data sharing and its impact on care.

METHODS

Focus groups were conducted with 31 healthcare providers from four treatment facilities. Discussions focused on privacy concerns, data-sharing workflows, and scenarios involving four Healthcare Effectiveness Data and Information Set (HEDIS) substance use disorder specific metrics. Open coding identified key concepts, and thematic analysis was employed to identify barriers and facilitators influencing data sharing and care outcomes.

RESULTS

Providers identified five main barriers: patient reluctance to share (48%), data access challenges (42%), poor provider coordination (29%), incomplete health information (26%), and complexity of privacy regulations (23%). Key facilitators included patient understanding (26%), patient-provider relationship (16%), and reliability of health information systems (16%).

DISCUSSION

This study sets the stage for understanding and addressing sensitive healthcare data access and privacy concerns through improved care coordination, systems interoperability, education, and policy reform.

Outcomes of Emergency Department Patients With Opioid Use Disorder Utilizing a Virtual Addiction Bridge Clinic: A Case Series

OBJECTIVES

Within the last decade, there has been a dramatic increase in the rate of emergency department (ED) visits and death from opioid overdose. Those who present to the ED are at high risk for subsequent morbidity and mortality. Despite effective treatment, many patients do not get rapidly connected to outpatient care. The aim of this investigation was to describe outpatient treatment engagement after ED discharge among patients with opioid use disorder (OUD) enrolled in a virtual Addiction Bridge Clinic (ABC).

METHODS

This was a retrospective case series describing an ED-initiated referral for rapid telehealth follow-up among patients with OUD. The primary outcome was addiction treatment engagement among those who completed the initial virtual ABC visit (engaged in ABC) vs. those who did not complete an ABC visit (Not engaged in ABC) at 1 week, 1 month, and 3 and 6 months timepoint intervals after the initial ED presentation.

RESULTS

Of the N = 201 patients referred to the ABC between March and December 2021, a majority were Black (71%) and male (77%). Of the 201 referrals, 85 (42%) completed an initial ABC telehealth visit. Subsequent treatment engagement was 26% at 1 week, 26% at 1 month, 22% at 3 months, and 18% at 6 months after the index ED visit.

CONCLUSIONS

A telehealth-enabled virtual addiction bridge clinic is one potential approach to reduce barriers to rapid treatment access. Strategies are needed to improve subsequent addiction treatment engagement after a virtual addiction bridge clinic visit.

Effectiveness of Substance Use Navigation for Emergency Department Patients With Substance Use Disorders: An Implementation Study

STUDY OBJECTIVE

We implemented a whole person care-informed intervention delivered by substance use navigators (SUN) for emergency department (ED) patients with substance use disorders.

METHODS

This was an implementation study of adult patients discharged from 3 public hospital EDs between September 1, 2021 through January 31, 2022 with cocaine, methamphetamine, alcohol, and opioid use-related diagnoses. The primary effectiveness outcome was treatment engagement within 30 days of ED discharge among patients with and without the SUN intervention. We used logistic regression and nearest neighbor propensity score matching without replacement to control for confounding effects.

RESULTS

There were 1,328 patients in the cohort, and 119 (9.0%) received the SUN intervention; 50.4% of patients in the SUN intervention group and 15.9% of patients without the SUN intervention were engaged in outpatient treatment within 30 days of ED discharge (difference in proportions: 34.5%, 95% confidence interval [CI] 25.3% to 43.8%). In the unadjusted analysis, the SUN intervention was associated with higher rates of treatment engagement after ED discharge for patients with alcohol, opioid, and cocaine-related diagnoses; patients with methamphetamine-related diagnoses had low engagement rates with or without the SUN intervention. In addition, the SUN intervention was associated with higher odds of treatment engagement in the multivariable model (aOR 3.7, 95% CI 2.4 to 5.8) and in the propensity score-matched analysis (OR 2.1, 95% CI 1.2 to 3.5).

CONCLUSION

A whole person care-informed intervention delivered by SUNs for ED patients with substance use disorders was strongly associated with higher engagement rates in addiction treatment after discharge.