Using decision tree models and comprehensive statewide data to predict opioid overdoses following prison release.

PURPOSE: Identifying predictors of opioid overdose following release from prison is critical for opioid overdose prevention. METHODS: We leveraged an individually linked, state-wide database from 2015-2020 to predict the risk of opioid overdose within 90 days of release from Massachusetts state prisons. We developed two decision tree modeling schemes: a model fit on all individuals with a single weight for those that experienced an opioid overdose and models stratified by race/ethnicity. We compared the performance of each model using several performance measures and identified factors that were most predictive of opioid overdose within racial/ethnic groups and across models. RESULTS: We found that out of 44,246 prison releases in Massachusetts between 2015-2020, 2237 (5.1%) resulted in opioid overdose in the 90 days following release. The performance of the two predictive models varied. The single weight model had high sensitivity (79%) and low specificity (56%) for predicting opioid overdose and was more sensitive for White non-Hispanic individuals (sensitivity = 84%) than for racial/ethnic minority individuals. CONCLUSIONS: Stratified models had better balanced performance metrics for both White non-Hispanic and racial/ethnic minority groups and identified different predictors of overdose between racial/ethnic groups. Across racial/ethnic groups and models, involuntary commitment (involuntary treatment for alcohol/substance use disorder) was an important predictor of opioid overdose.

Overdose from Unintentional Fentanyl Use when Intending to Use a Non-opioid Substance: An Analysis of Medically Attended Opioid Overdose Events.

Fentanyl-mixed and substituted heroin is well-documented, but less is known about unintentional fentanyl use among people using stimulants. To determine the prevalence of and racial and ethnic disparities in unintentional fentanyl use among people experiencing a medically attended opioid overdose, we reviewed 448 suspected non-fatal overdose cases attended by a community paramedic overdose response team in San Francisco from June to September 2022. We applied a case definition for opioid overdose to paramedic records and abstracted data on intended substance use prior to overdose. Among events meeting case criteria with data on intended substance use, intentional opioid use was reported by 57.3%, 98.0% of whom intended to use fentanyl. No intentional opioid use was reported by 42.7%, with most intending to use stimulants (72.6%), including methamphetamine and cocaine. No intentional opioid use was reported by 58.5% of Black, 52.4% of Latinx, and 28.8% of White individuals (p = 0.021), and by 57.6% of women and 39.5% of men (p = 0.061). These findings suggest that unintentional fentanyl use among people without opioid tolerance may cause a significant proportion of opioid overdoses in San Francisco. While intentional fentanyl use might be underreported, the magnitude of self-reported unintentional use merits further investigation to confirm this phenomenon, explore mechanisms of use and disparities by race and ethnicity, and deploy targeted overdose prevention interventions.

Examining the association of rurality with opioid-related morbidity and mortality in Georgia: A geospatial analysis.

INTRODUCTION: The US opioid epidemic continues to escalate, with overdose deaths being the most-used metric to quantify its burden. There is significant geographic variation in opioid-related outcomes. Rural areas experience unique challenges, yet many studies oversimplify rurality characterizations. Contextual factors, such as area deprivation, are also important to consider when understanding a community's need for treatment services and prevention programming. This study aims to provide a geospatial snapshot of the opioid epidemic in Georgia using several metrics of opioid-related morbidity and mortality and explore differences by rurality across counties. METHODS: This was a spatial ecologic study. Negative binominal regression was used to model the relationship of county rurality with four opioid-related outcomes - overdose mortality, emergency department visits, inpatient hospitalizations, and overdose reversals - adjusting for county-level sex, racial/ethnic, and age distributions. Area Deprivation Index was also included. RESULTS: There was significant geographic variation across the state for all four opioid-related outcomes. Counts remained highest among the metro areas. For rates, counties in the top quartile of rates varied by outcome and were often rural areas. In the final models, rurality designation was largely unrelated to opioid outcomes, with the exception of medium metro areas (inversely related to hospitalizations and overdose reversals) and non-core areas (inversely related to hospitalizations), as compared to large central metro areas. Higher deprivation was significantly related to increased ED visits and hospitalizations, but not overdose mortality and reversals. CONCLUSIONS: When quantifying the burden of the opioid epidemic in a community, it is essential to consider multiple outcomes of morbidity and mortality. Understanding what outcomes are problematic for specific communities, in combination with their demographic and socioeconomic context, can provide insight into gaps in the treatment continuum and potential areas for intervention. Additionally, compared to demographic and socioeconomic factors, rurality may no longer be a salient predictor of the severity of the opioid epidemic in an area.

Characterizing opioid overdose hotspots for place-based overdose prevention and treatment interventions: A geo-spatial analysis of Rhode Island, USA.

OBJECTIVE: Examine differences in neighborhood characteristics and services between overdose hotspot and non-hotspot neighborhoods and identify neighborhood-level population factors associated with increased overdose incidence. METHODS: We conducted a population-based retrospective analysis of Rhode Island, USA residents who had a fatal or non-fatal overdose from 2016 to 2020 using an environmental scan and data from Rhode Island emergency medical services, State Unintentional Drug Overdose Reporting System, and the American Community Survey. We conducted a spatial scan via SaTScan to identify non-fatal and fatal overdose hotspots and compared the characteristics of hotspot and non-hotspot neighborhoods. We identified associations between census block group-level characteristics using a Besag-York-Mollié model specification with a conditional autoregressive spatial random effect. RESULTS: We identified 7 non-fatal and 3 fatal overdose hotspots in Rhode Island during the study period. Hotspot neighborhoods had higher proportions of Black and Latino/a residents, renter-occupied housing, vacant housing, unemployment, and cost-burdened households. A higher proportion of hotspot neighborhoods had a religious organization, a health center, or a police station. Non-fatal overdose risk increased in a dose responsive manner with increasing proportions of residents living in poverty. There was increased relative risk of non-fatal and fatal overdoses in neighborhoods with crowded housing above the mean (RR 1.19 [95 % CI 1.05, 1.34]; RR 1.21 [95 % CI 1.18, 1.38], respectively). CONCLUSION: Neighborhoods with increased prevalence of housing instability and poverty are at highest risk of overdose. The high availability of social services in overdose hotspots presents an opportunity to work with established organizations to prevent overdose deaths.

Association of medications for opioid use disorder with reduced risk of repeat opioid overdose in Medicaid: A cohort study.

INTRODUCTION: Following a nonfatal opioid overdose, patients are at high risk for repeat overdose. The objective of this study was to examine the association of MOUD after nonfatal opioid overdose with risk of repeat overdose in the following year. METHODS: This retrospective cohort study analyzed Missouri Medicaid claims from July 2012 to December 2021. The study identified opioid overdoses occurring between 2013 and 2020 using diagnosis codes for opioid poisoning in an inpatient or emergency department setting. The study implemented Cox models with a time-varying covariate for post-overdose receipt of MOUD. RESULTS: During the study period, MOUD receipt after overdose more than tripled, from 4.8 % to 18.9 %. Overall, only 12.1 % of patients received MOUD in the year after index. MOUD during follow-up was associated with significantly lower risk of repeat overdose (HR = 0.34, 95 % CI = 0.14-0.82). Out of 3017 individuals meeting inclusion criteria, 13.6 % had a repeat opioid overdose within 1 year. Repeat overdose risk was higher for those whose index overdose involved heroin or synthetic opioids (HR = 1.71, 95 % CI = 1.35-2.15), but MOUD was associated with significantly reduced risk in this group (HR = 0.34, 95 % CI = 0.13-0.92). CONCLUSIONS: MOUD receipt was associated with reduced risk of repeat overdose. Those whose index overdoses involved heroin or synthetic opioids were at greater risk of repeat overdose, but MOUD was associated with reduced risk in this group.

Risks of opioid overdose among New York State Medicaid recipients with chronic pain before and during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic contributed to healthcare disruptions for patients with chronic pain. Following initial disruptions, national policies were enacted to expand access to long-term opioid therapy (LTOT) for chronic pain and opioid use disorder (OUD) treatment services, which may have modified risk of opioid overdose. We examined associations between LTOT and/or OUD with fatal and non-fatal opioid overdoses, and whether the pandemic moderated overdose risk in these groups. METHODS: We analyzed New York State Medicaid claims data (3/1/2019-12/31/20) of patients with chronic pain (N = 236,391). We used generalized estimating equations models to assess associations between LTOT and/or OUD (neither LTOT or OUD [ref], LTOT only, OUD only, and LTOT and OUD) and the pandemic (03/2020-12/2020) with opioid overdose. RESULTS: The pandemic did not significantly (ns) affect opioid overdose among patients with LTOT and/or OUD. While patients with LTOT (vs. no LTOT) had a slight increase in opioid overdose during the pandemic (pre-pandemic: aOR:1.65, 95% CI:1.05, 2.57; pandemic: aOR:2.43, CI:1.75,3.37, ns), patients with OUD had a slightly attenuated odds of overdose during the pandemic (pre-pandemic: aOR:5.65, CI:4.73, 6.75; pandemic: aOR:5.16, CI:4.33, 6.14, ns). Patients with both LTOT and OUD also experienced a slightly reduced odds of opioid overdose during the pandemic (pre-pandemic: aOR:5.82, CI:3.58, 9.44; pandemic: aOR:3.70, CI:2.11, 6.50, ns). CONCLUSIONS: Findings demonstrated no significant effect of the pandemic on opioid overdose among people with chronic pain and LTOT and/or OUD, suggesting pandemic policies expanding access to chronic pain and OUD treatment services may have mitigated the risk of opioid overdose.

Healthcare costs and use before and after opioid overdose in Veterans Health Administration patients with opioid use disorder.

AIMS: To compare healthcare costs and use between United States (US) Veterans Health Administration (VHA) patients with opioid use disorder (OUD) who experienced an opioid overdose (OD cohort) and patients with OUD who did not experience an opioid overdose (non-OD cohort). DESIGN: This is a retrospective cohort study of administrative and clinical data. SETTING: The largest integrated national health-care system is the US Veterans Health Administration's healthcare systems. PARTICIPANTS: We included VHA patients diagnosed with OUD from October 1, 2017 through September 30, 2018. We identified the index date of overdose for patients who had an overdose. Our control group, which included patients with OUD who did not have an overdose, was randomly assigned an index date. A total of 66 513 patients with OUD were included for analysis (OD cohort: n = 1413; non-OD cohort: n = 65 100). MEASUREMENTS: Monthly adjusted healthcare-related costs and use in the year before and after the index date. We used generalized estimating equation models to compare patients with an opioid overdose and controls in a difference-in-differences framework. FINDINGS: Compared with the non-OD cohort, an opioid overdose was associated with an increase of $16 890 [95% confidence interval (CI) = $15 611-18 169; P < 0.001] in healthcare costs for an estimated $23.9 million in direct costs to VHA (95% CI = $22.1 million, $25.7 million) within the 30 days following overdose after adjusting for baseline characteristics. Inpatient costs ($13 515; 95% CI = $12 378-14 652; P < 0.001) reflected most of this increase. Inpatient days (+6.15 days; 95% CI, = 5.33-6.97; P < 0.001), inpatient admissions (+1.01 admissions; 95% CI = 0.93-1.10; P < 0.001) and outpatient visits (+1.59 visits; 95% CI = 1.34-1.84; P < 0.001) also increased in the month after opioid overdose. Within the overdose cohort, healthcare costs and use remained higher in the year after overdose compared with pre-overdose trends. CONCLUSIONS: The US Veterans Health Administration patients with opioid use disorder (OUD) who have experienced an opioid overdose have increased healthcare costs and use that remain significantly higher in the month and continuing through the year after overdose than OUD patients who have not experienced an overdose.

Racial Inequality in Receipt of Medications for Opioid Use Disorder.

BACKGROUND: Since 2010, Black persons in the United States have had a greater increase in opioid overdose-related mortality than other groups, but national-level evidence characterizing racial and ethnic disparities in the use of medications for opioid use disorder (OUD) is limited. METHODS: We used Medicare claims data from the 2016-2019 period for a random 40% sample of fee-for-service beneficiaries who were Black, Hispanic, or White; were eligible for Medicare owing to disability; and had an index event related to OUD (nonfatal overdose treated in an emergency department or inpatient setting, hospitalization with injection drug use-related infection, or inpatient or residential rehabilitation or detoxification care). We measured the receipt of medications to treat OUD (buprenorphine, naltrexone, and naloxone), the receipt of high-risk medications (opioid analgesics and benzodiazepines), and health care utilization, all in the 180 days after the index event. We estimated differences in outcomes according to race and ethnic group with adjustment for beneficiary age, sex, index event, count of chronic coexisting conditions, and state of residence. RESULTS: We identified 25,904 OUD-related index events among 23,370 beneficiaries, with 3937 events (15.2%) occurring among Black patients, 2105 (8.1%) among Hispanic patients, and 19,862 (76.7%) among White patients. In the 180 days after the index event, patients received buprenorphine after 12.7% of events among Black patients, after 18.7% of those among Hispanic patients, and after 23.3% of those among White patients; patients received naloxone after 14.4%, 20.7%, and 22.9%, respectively; and patients received benzodiazepines after 23.4%, 29.6%, and 37.1%, respectively. Racial differences in the receipt of medications to treat OUD did not change appreciably from 2016 to 2019 (buprenorphine receipt: after 9.1% of index events among Black patients vs. 21.6% of those among White patients in 2016, and after 14.1% vs. 25.5% in 2019). In all study groups, patients had multiple ambulatory visits in the 180 days after the index event (mean number of visits, 6.6 after events among Black patients, 6.7 after events among Hispanic patients, and 7.6 after events among White patients). CONCLUSIONS: Racial and ethnic differences in the receipt of medications to treat OUD after an index event related to this disorder among patients with disability were substantial and did not change over time. The high incidence of ambulatory visits in all groups showed that disparities persisted despite frequent health care contact. (Funded by the National Institute on Drug Abuse and the National Institute on Aging.).

Allocation of federal funding to address the opioid overdose crisis in the criminal legal system.

INTRODUCTION: The opioid overdose crisis remains a chief public health concern in the United States, and people involved in the criminal legal system are among the most vulnerable to opioid related harms. This study aimed to identify all discretionary federal funding allocated to states, cities, and counties targeting the overdose crisis for criminal legal system-involved populations in fiscal year (FY) 2019. We then aimed to assess the extent to which federal funding was allocated to states with the highest need. METHODS: We collected data from publicly available government databases (N = 22) to identify federal funding targeting opioid use disorder in criminal legal system-involved populations. Descriptive analyses examined the extent to which funding allocated per person in the criminal legal system-involved population was associated with funding need, proxied by a composite measure of opioid mortality and drug-related arrests. We created a generosity measure and dissimilarity index to assess the degree to which funding matched need across states. RESULTS: More than 590 million dollars were allocated across 517 grants by 10 federal agencies in FY 2019. About half of states received less than $100.00 dollars per capita in the state criminal legal system-involved population. Funding generosity ranged from 0 % to 504.2 %, with more than half of states (52.9 %, n = 27) receiving fewer dollars per opioid problem than the US average. Further, a dissimilarity index indicated that about 34.2 % of funding (~$202.3 million) would have to be reallocated to distribute funding more evenly across states. CONCLUSIONS: Results suggest that additional efforts are needed to more equitably distribute funds to meet the needs of states with more severe opioid problems.

The Opioid Epidemic: a Crisis Disproportionately Impacting Black Americans and Urban Communities.

The heroin epidemic has existed for decades, but a sharp rise in opioid overdose deaths (OODs) jolted the nation in the mid-twenty-teens and continues as a major health crisis to this day. Although the new wave of OODs was initially approached as a rural problem impacting a White/Caucasian demographic, surveillance records suggest severe impacts on African Americans and urban-dwelling individuals, which have been largely underreported. The focus of this report is on specific trends in OOD rates in Black and White residents in states with a significant Black urban population and declared as hotspots for OOD: (Maryland (MD), Illinois (IL), Michigan (MI), and Pennsylvania (PA)), and Washington District of Columbia (DC). We compare OODs by type of opioid, across ethnicities, across city/rural demographics, and to homicide rates using 2013-2020 data acquired from official Chief Medical Examiners' or Departments of Health (DOH) reports. With 2013 or 2014 as baseline, the OOD rate in major cities (Baltimore, Chicago, Detroit, Philadelphia) were elevated two-fold over all other regions of their respective state. In DC, Wards 7 and 8 OODs were consistently greater than other jurisdictions, until 2020 when the rate of change of OODs increased for the entire city. Ethnicity-wise, Black OOD rates exceeded White rates by four- to six-fold, with fentanyl and heroin having a disproportionate impact on Black opioid deaths. This disparity was aggravated by its intersection with the COVID-19 pandemic in 2020. African Americans and America's urban dwellers are vulnerable populations in need of social and political resources to address the ongoing opioid epidemic in under-resourced communities.

Changes in predicted opioid overdose risk over time in a state Medicaid program: a group-based trajectory modeling analysis.

BACKGROUND AND AIMS: The time lag encountered when accessing health-care data is one major barrier to implementing opioid overdose prediction measures in practice. Little is known regarding how one's opioid overdose risk changes over time. We aimed to identify longitudinal patterns of individual predicted overdose risks among Medicaid beneficiaries after initiation of opioid prescriptions. DESIGN, SETTING AND PARTICIPANTS: A retrospective cohort study in Pennsylvania, USA among Pennsylvania Medicaid beneficiaries aged 18-64 years who initiated opioid prescriptions between July 2017 and September 2018 (318 585 eligible beneficiaries (mean age = 39 ± 12 years, female = 65.7%, White = 62.2% and Black = 24.9%). MEASUREMENTS: We first applied a previously developed and validated machine-learning algorithm to obtain risk scores for opioid overdose emergency room or hospital visits in 3-month intervals for each beneficiary who initiated opioid therapy, until disenrollment from Medicaid, death or the end of observation (December 2018). We performed group-based trajectory modeling to identify trajectories of these predicted overdose risk scores over time. FINDINGS: Among eligible beneficiaries, 0.61% had one or more occurrences of opioid overdose in a median follow-up of 15 months. We identified five unique opioid overdose risk trajectories: three trajectories (accounting for 92% of the cohort) had consistent overdose risk over time, including consistent low-risk (63%), consistent medium-risk (25%) and consistent high-risk (4%) groups; another two trajectories (accounting for 8%) had overdose risks that substantially changed over time, including a group that transitioned from high- to medium-risk (3%) and another group that increased from medium- to high-risk over time (5%). CONCLUSIONS: More than 90% of Medicaid beneficiaries in Pennsylvania USA with one or more opioid prescriptions had consistent, predicted opioid overdose risks over 15 months. Applying opioid prediction algorithms developed from historical data may not be a major barrier to implementation in practice for the large majority of individuals.

COVID-19 economic impact payments and opioid overdose deaths.

BACKGROUND: Given the global economic recessions mediated by the COVID-19 pandemic and that many countries have implemented direct income support programs, we investigated the timing of the COVID-19 economic impact payments and opioid overdose deaths. METHODS: A longitudinal, observational study design that included data from the Ohio Department of Health was utilized. Statistical change point analyses were conducted to identify significant changes in weekly number of opioid overdose deaths from January 1 of 2018 to August 1 of 2020. Additional analyses including difference-in-difference, time series tests, interrupted time series regression analysis and Granger causality test were performed. RESULTS: A single change point was identified and occurred at week 16, 2020. For 2020, the median opioid overdose deaths numbers for weeks 1-16 and weeks 17-32 were 68.5 and 101, respectively. The opioid overdose deaths numbers from weeks 17-32 of 2020 were significantly higher than those in weeks 1-16 of 2020 and those in 2018 and 2019 (before and after week 16). The interrupted time series regression analysis indicated more than 203 deaths weekly for weeks 17-32 of 2020 compared to all other weeks. The result of the Granger causality test found that the identified change point (week 16 of 2020) directly influenced the increase in opioid overdose deaths in weeks 17-32 of 2020. CONCLUSION: The identified change point may refer to the timing of many factors, not only the economic payments and further research is warranted to investigate the potential relationship between the COVID-19 economic impact payments and overdose deaths.

Opioid overdose survivors: Medications for opioid use disorder and risk of repeat overdose in Medicaid patients.

BACKGROUND: Patients with medically-treated opioid overdose are at high risk for subsequent adverse outcomes, including repeat overdose. Understanding factors associated with repeat overdose can aid in optimizing post-overdose interventions. METHODS: We conducted a longitudinal, retrospective cohort study using NJ Medicaid data from 2014 to 2019. Medicaid beneficiaries aged 12-64 with an index opioid overdose from 2015 to 2018 were followed for one year for subsequent overdose. Exposures included patient demographics; co-occurring medical, mental health, and substance use disorders; service and medication use in the 180 days preceding the index overdose; and MOUD following index overdose. RESULTS: Of 4898 individuals meeting inclusion criteria, 19.6% had repeat opioid overdoses within one year. Index overdoses involving heroin/synthetic opioids were associated with higher repeat overdose risk than those involving prescription/other opioids only (HR = 1.44, 95% CI = 1.22-1.71). Risk was higher for males and those with baseline opioid use disorder diagnosis or ED visits. Only 21.7% received MOUD at any point in the year following overdose. MOUD was associated with a large decrease in repeat overdose risk among those with index overdose involving heroin/synthetic opioids (HR = 0.30, 95% CI = 0.20-0.46). Among those receiving MOUD at any point in follow-up, 10.5% (112/1065) experienced repeat overdose versus 22.1% (848/3833) for those without MOUD. CONCLUSIONS: Repeat overdose was common among individuals with medically-treated opioid overdose. Risk factors for repeat overdose varied by type of opioid involved in index overdose, with differential implications for intervention. MOUD following index opioid overdose involving heroin/synthetic opioids was associated with reduced repeat overdose risk.

Identifying barriers to emergency department-initiated buprenorphine: A spatial analysis of treatment facility access in Michigan.

STUDY OBJECTIVES: Emergency department (ED)-initiated buprenorphine/naloxone has been shown to improve treatment retention and reduce illicit opioid use; however, its potential may be limited by a lack of accessible community-based facilities. This study compared one state's geographic distribution of EDs to outpatient treatment facilities that provide buprenorphine treatment and identified ED and geographic factors associated with treatment access. METHODS: Treatment facility data were obtained from the SAMHSA 2018 National Directory of Drug and Alcohol Abuse Treatment Facilities, and ED data were obtained from the Michigan College of Emergency Physician's 2018 ED directory. Geospatial analysis compared EDs to buprenorphine treatment facilities using 5-, 10-, and 20-mile network buffers. RESULTS: Among 131 non-exclusively pediatric EDs in Michigan, 57 (43.5%) had a buprenorphine treatment facility within 5 miles, and 66 (50.4%) had a facility within 10 miles. EDs within 10 miles of a Medicaid-accepting, outpatient buprenorphine treatment facility had higher average numbers of beds (41 vs. 15; p < 0.0001) and annual patient volumes (58,616 vs. 17,484; p < 0.0001) compared to those without. Among Michigan counties with EDs, those with at least one buprenorphine facility had larger average populations (286,957 vs. 44,757; p = 0.005) and higher annual rates of opioid overdose deaths (mean 18.3 vs. 13.0 per 100,000; p = 0.02) but were similar in terms of opioid-related hospitalizations and socioeconomic distress. CONCLUSION: Only half of Michigan EDs are within 10 miles of a buprenorphine treatment facility. Given these limitations, expanding access to ED-initiated buprenorphine in states similar to Michigan may require developing alternative models of care.

Early buprenorphine-naloxone initiation for opioid use disorder reduces opioid overdose, emergency room visits, and healthcare cost compared to late initiation.

Background: Although the effectiveness of buprenorphine-naloxone (BUP-NX) has been established, real-world evidence on the benefits of early treatment initiation is limited.Objective: To evaluate the association between early BUP-NX initiation and health-related outcomes among insured adults with opioid use disorder (OUD).Methods: We conducted a cross-sectional analysis using the Optum's de-identified Clinformatics® Data Mart Database from 2010 to 2018. Patients who initiated BUP-NX within 30 days of OUD diagnosis were classified as early initiators. Patients who initiated BUP-NX later, but within the one-year follow-up, were defined as late initiators. Outcomes included opioid overdose, opioid overdose-related emergency department (ED) visits, and all-cause healthcare cost during the year after OUD diagnosis. We employed generalized linear models to compare outcomes between early and late initiators, adjusting for baseline covariates and accounting for missing information for covariates using multiple imputation.Results: A total of 8,388 patients with OUD were identified; mean age was 39.9 years; 36% were female; and 67.6% were early initiators. Early initiators had an estimated 42% lower rate of opioid overdose (adjusted rate ratio (aRR) = 0.58; 95% confidence interval (CI): 0.52, 0.64); 51% lower rate of opioid overdose-related ED visits (aRR = 0.49; 95% CI: 0.44, 0.55); and 31% lower total healthcare cost (adjusted cost ratio = 0.69; 95% CI: 0.66, 0.72), compared to late initiators.Conclusion: Compared to late BUP-NX initiation, early initiation was associated with a lower risk of opioid overdose and opioid overdose-related ED visits, and reduced total healthcare cost among insured adult patients with OUD.

Opioid overdose crises during the COVID-19 pandemic: implication of health disparities.

BACKGROUND: Recent data suggest a disproportionate impact of opioid overdoses on Black Americans. The study aims to describe emergency department (ED) visits at a Southern, urban ED pertaining to opioid overdose and associated health disparities. METHODS: Patients presenting to the ED at the University of Alabama at Birmingham Hospital with opioid overdoses from January 1 to October 31, 2019, and from January 1 to October 31, 2020, were identified from electronic medical records. RESULTS: The total number of opioid overdose visits increased 9.7% (556 to 611) between January and October 2020 compared with 2019. Among patients who presented with opioid overdose, the mean ages were 50.3 years and 48.3 years, in 2019 and 2020, respectively. In both 2019 and 2020, more Blacks than whites were treated for opioid overdose in the ED (284 vs. 258 in 2019, and 306 vs. 271 in 2020) although 28 patients did not record their race in 2020. Consistently, more overdose deaths were observed in Blacks than in whites in 2020. More individuals seeking opioid overdose treatment were single in both years. CONCLUSIONS: The study reported a greater number of visits for opioid overdoses from January to October of 2020 in an ED of a southeastern region, as well as higher overdose deaths in Blacks. Our findings highlight the importance of substance use treatment, harm reduction, and overdose prevention efforts that should be immediately present to reduce opioid overdose, especially for vulnerable populations in the South, i.e., Black community, and individuals experiencing singlehood.

Factors Associated With Calling 911 for an Overdose: An Ethnographic Decision Tree Modeling Approach.

Objectives. To identify factors that influence when people who use drugs (PWUDs) call 911 for an overdose. Methods. We conducted 45 qualitative interviews and 180 surveys with PWUDs who had recently witnessed overdoses in Southern California from 2017 to 2019. We used conditional inference tree and random forest models to generate and validate a model to predict whether 911 would be called. Results. Our model had good in- (83%) and out-of-sample (84%) predictive accuracy. Three aspects of the social and policy environment influenced calling 911 for an overdose: the effectiveness of response strategies employed, the behavior of other bystanders, and whether the responder believes it is their responsibility to call. Conclusions. Even in the presence of policies that provide some protections, PWUDs are faced with difficult decisions about calling 911 and must weigh their own safety against that of an overdose victim. Potential interventions include strengthening training and safety planning for PWUDs, bolstering protections for PWUDs when they call 911, and separating law enforcement response from emergency medical response to overdoses.

A rapid-cycle assessment strategy for understanding the opioid overdose epidemic in local communities.

Background: Certain communities in the United States experience greater opioid-involved overdose mortality than others. Interventions to stem overdose benefit from contextual understandings of communities' needs and strengths in addressing the opioid crisis. This project aims to understand multiple stakeholder perspectives on the opioid epidemic in communities disproportionately affected by opioid-involved overdose mortality. Methods: We performed a rapid-cycle qualitative assessment study utilizing in-depth interviews with community stakeholders and observations of community meetings in eight communities in Allegheny County, Pennsylvania, USA, disproportionately impacted by opioid-involved overdose mortality. Stakeholder categories included: current and past illicit users of opioids; medical and social service providers; emergency medical services; law enforcement; spouse or other family members of illicit users/former users of opioids; government officials; school officials; community members. Content analysis was utilized to identify themes and answer study questions. Regular feedback to stakeholders was provided to support targeted interventions. Results: We performed semi-structured, in-depth interviews with 130 community stakeholders and 29 community meeting observations in 2018-2019. Participants perceived similar economic and social determinants as origins of the opioid overdose epidemic including lack of economic resources, loss of jobs, transient populations and dilapidated housing. However, they differed in their awareness of and attention to the epidemic. Awareness was dependent on the visibility of opioid use (presence of paraphernalia litter, location of drug users, media coverage, and relationship to users). Overall, there was good knowledge of naloxone for opioid overdose reversal but less knowledge about local syringe services programs. Perceptions of harm reduction efforts were ambivalent. Conclusions: Members of communities impacted by the opioid epidemic perceived that economic downturn was a major factor in the opioid overdose epidemic. However, the varied beliefs within and between communities suggest that interventions need to be tailored according to the cultural norms of place.

Naloxone's role in the national opioid crisis-past struggles, current efforts, and future opportunities.

Over the past 25 years, naloxone has emerged as a critical lifesaving overdose antidote. Public health advocates and community activists established early methods for naloxone distribution to people who inject drugs, but a legacy of stigmatization and opposition to universal naloxone access continues to limit the drug's full potential to reduce opioid-related mortality. The establishment of naloxone distribution programs under the umbrella of syringe exchange programs faces the same practical, ideological and financial barriers to expansion similar to those faced by syringe exchange programs themselves. The expansion of naloxone from the confines of a few syringe exchange programs to what we see today represents an enormous triumph for the grass-roots activists, service providers, and public health professionals who have fought to guarantee lay access to naloxone. Despite the extensive efforts to expand access to naloxone, naloxone continues to remains a scarce resource in many US localities. Considerable naloxone "deserts" remain and even where there is naloxone access, it does not always reach those at risk. Promising areas for expansion include the development of more robust telehealth methods for naloxone distribution, including subsidized mail delivery programs; lowering barriers to pharmacy access; working with hospitals, ambulances, and law enforcement to expand naloxone "leave behind" programs; providing naloxone co-prescription with medications for opioid use disorder; and working with prisons, shelters, and networks of people who use drugs to increase access to the lifesaving medication. Efforts to ensure over-the-counter and low- or no-cost naloxone are ongoing and stand alongside medication-assisted treatments as efficacious, readily-actionable, and cost-efficient population-level interventions available for combatting opioid-related overdose in the United States.