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. Author manuscript; available in PMC: 2024 Jul 1.
Published in final edited form as: Am J Prev Med. 2023 Mar 10;65(1):19–29. doi: 10.1016/j.amepre.2023.01.037

Buprenorphine after non-fatal opioid overdose: Reduced mortality risk in Medicare disability beneficiaries

Hillary Samples 1,2, Molly Nowels 1,2, Arthur R Williams 3, Mark Olfson 3,4, Stephen Crystal 1,5
PMCID: PMC10293066  NIHMSID: NIHMS1870146  PMID: 36906496

Abstract

Introduction:

Opioid-involved overdose mortality is a persistent public health challenge, yet limited evidence exists on the relationship between opioid use disorder (OUD) treatment after non-fatal overdose and subsequent overdose death.

Methods:

National Medicare data were used to identify adult (18–64 years) disability beneficiaries who received inpatient or emergency treatment for non-fatal opioid-involved overdose in 2008–2016. OUD treatment was defined as: 1) buprenorphine, measured using medication days’ supply, and 2) psychosocial services, measured as 30-day exposures from and including each service date. Opioid-involved overdose fatalities were identified in the year after non-fatal overdose using linked National Death Index data. Cox proportional hazards models estimated associations between time-varying treatment exposures and overdose death. Analyses were conducted in 2022.

Results:

The sample (n=81,616) was mostly female (57.3%), 50 years or older (58.8%), and white (80.9%), with a significantly elevated overdose mortality rate compared to the general U.S. population (standardized mortality ratio [SMR]=132.4, 95% CI=129.9, 135.0). Only 6.5% of the sample (n=5329) had OUD treatment after the index overdose. Buprenorphine (n=3774, 4.6%) was associated with significantly lower risk of opioid-involved overdose death (adjusted hazard ratio [aHR]=0.38, 95% CI=0.23, 0.64), but OUD-related psychosocial treatment (n=2405, 2.9%) was not associated with risk of death (aHR=1.18, 95% CI=0.71, 1.95).

Conclusions:

Buprenorphine treatment after non-fatal opioid-involved overdose was associated with a 62% reduction in risk of opioid-involved overdose death. However, fewer than 1 in 20 individuals received buprenorphine in the subsequent year, highlighting a need to strengthen care connections following critical opioid-related events, particularly for vulnerable groups.

INTRODUCTION

Drug overdose mortality remains an urgent health concern in the U.S., surpassing 105,000 deaths in 2021, largely attributed to opioids.1 Opioid-involved overdose deaths are preventable with medication for opioid use disorder (MOUD), which has a well-established association with reduced mortality risk during treatment.2,3 Non-fatal opioid-involved overdoses represent critical opportunities to initiate potentially life-saving interventions, as these events are strong risk factors for subsequent overdose and death.4–10

Current evidence on opioid use disorder (OUD) treatment after opioid-involved overdose consistently shows low MOUD uptake.11–21 The literature on non-medication services is more limited, indicating very low uptake of residential treatment for OUD.21 However, general services are more common, such as health care encounters with OUD11 or substance use disorder diagnoses17 and mental health counseling visits.15 Evidence connecting OUD-specific treatment with risk of subsequent mortality is lacking.

Single-state research to date has found reduced risk of opioid-involved overdose mortality for buprenorphine medication20,21 but not residential OUD treatment.21 Both studies measured medication dispensing at monthly intervals that do not account for briefer gaps in supply when mortality risk is elevated.2,3 Additionally, wide variation in state epidemiological and health system contexts underscores a need for national data to inform tertiary prevention and treatment efforts, particularly for high-risk groups.

Individuals with disabilities have a nearly three-fold higher risk of opioid-involved overdose death than those without functional limitations.22 As the primary source of insurance coverage for adults receiving federal disability benefits due to long-term (>1 year) or terminal conditions causing inability to work,23 Medicare disability beneficiaries (MDBs) constitute a key U.S. health care population in the management of chronic illness. MDBs have elevated rates of chronic pain,24,25 long-term and high-dosage prescription opioid use,25,26 and OUD.27 Though only 14% of enrollees are MDBs,28 they comprise a growing share of opioid-involved overdose hospitalizations29,30 and account for over 80% of opioid-involved overdose deaths in the Medicare population.31

This study examined associations of buprenorphine and OUD-related psychosocial services with risk of opioid-involved overdose death in the year after non-fatal opioid-involved overdose, focusing on the MDB population to generate national-level U.S. data in a priority group for interventions to address the ongoing opioid overdose crisis.

METHODS

This longitudinal, retrospective cohort study used a 20% random sample of national Medicare Part D (prescription drug) beneficiaries.32 Data comprised all prescription drugs; outpatient, inpatient, and emergency department (ED) services; and demographic, enrollment, and eligibility information. Medicare data were linked to National Death Index (NDI) data with dates and causes of death. This study was approved by the Rutgers Institutional Review Board. Reporting follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Study Sample

The cohort included adults aged 18–64 years with Medicare eligibility on the basis of disability with a non-fatal opioid-involved overdose treated in inpatient or ED settings during 2008–2016. Enrollees with any other basis of eligibility (i.e., seniors ≥65 years) were excluded. The sample was restricted to individuals with continuous fee-for-service and Part D enrollment throughout the 180-day baseline period preceding the index opioid-involved overdose and 365-day follow-up period (in the absence of death or censoring) to ensure full availability of treatment data. Index events resulting in death were excluded (Appendix Figure 1).

Measures

Non-fatal opioid-involved overdoses were identified using diagnosis codes from the International Classification of Diseases, 9th (ICD-9) and 10th (ICD-10) Revisions, Clinical Modification (Appendix Table 1).33,34 The first qualifying event per person was analyzed, including consecutive days with opioid-involved poisoning diagnoses in the index event. The follow-up period began on the first date with no opioid-involved poisoning code. Additional index characteristics included involvement of heroin or synthetic opioids other than methadone (e.g., fentanyl), involvement of benzodiazepines, and indicators of medical severity (i.e., hospitalization, mechanical ventilation),4,35 measured using diagnosis, revenue, and procedure codes (Appendix Table 2).

To estimate associations between follow-up OUD treatment and subsequent opioid-involved overdose mortality, time-varying measures were created for buprenorphine medication and psychosocial services across the study period. Buprenorphine was identified using National Drug Codes (NDC) on prescription claims, excluding drugs approved only for pain management (Appendix Table 3), with daily medication availability based on days’ supply. Psychosocial services were identified using procedure codes36,37 selected from the Healthcare Effectiveness Data and Information Set (HEDIS) measure for substance use treatment initiation and engagement (Appendix Table 3)38 and restricted to services with OUD diagnoses to capture treatment specifically for opioid addiction. The time-varying indicator for each psychosocial service remained positive for up to 30 days to account for the intermittent nature of this treatment modality.

The primary outcome was opioid-involved overdose death, identified using ICD-10 cause of death codes in linked NDI data following Centers for Disease Control and Prevention (CDC) methods (Appendix Table 1).

Sociodemographics and clinical covariates were measured in the 180-day baseline period. Sociodemographics included sex (male, female), age (18–29, 30–39, 40–49, 50–59, 60–64 years), race/ethnicity (non-Hispanic white, non-Hispanic Black, Hispanic, American Indian/Alaska Native, Asian/Pacific Islander, other/unknown), U.S. Census region of residence (Northeast, Midwest, South, West), and dual Medicaid eligibility.

Clinical characteristics included baseline comorbidities and health services. Mental health diagnoses included major depressive disorder, anxiety disorders, bipolar disorder, schizophrenia, personality disorder, and any other mental illness (Appendix Table 2). Substance use indicators included diagnoses for opioid, alcohol, cannabis, and sedative use disorders. Medical conditions included diagnoses for asthma, cerebrovascular disease (CVD), chronic pain, chronic obstructive pulmonary disease (COPD), diabetes, heart failure, hepatitis C, human immunodeficiency virus (HIV), hypertension, pneumonia, and sleep apnea. Health service indicators included inpatient, ED, and OUD-related psychosocial services described above. Prescription drugs included buprenorphine, opioids, antidepressants, antipsychotics, mood stabilizers, and sedatives. For buprenorphine and opioids, total days with medication supply were calculated to account for the full extent of baseline use. Benzodiazepines were not measured due to changes in Medicare reimbursement during the study period32 that precluded benzodiazepine coverage prior to 2013.

In the follow-up period, daily indicators of prescription opioid availability and inpatient hospitalizations were used to account for these exposures in estimates of mortality risk.

Statistical Analysis

Unadjusted descriptive statistics with chi-square tests compared groups with and without opioid-involved overdose death in the follow-up year. Descriptive statistics for OUD treatment characterized time-varying follow-up exposures.

Crude and standardized mortality rates were calculated by sex, age, and race/ethnicity and, separately, by follow-up OUD treatment. To minimize bias in mortality rates stratified by OUD treatment, time between the index event and treatment initiation was classified as unexposed.39 Crude mortality rates (CMRs) represent the observed number of deaths per 100,000 person-years of follow-up. Standardized mortality ratios (SMRs) represent the ratio of observed to expected deaths in the sample. Expected deaths were calculated using CDC WONDER40 mortality rates for opioid-involved overdoses defined using cause of death codes described above, limited to the study years, and standardized by sex, age, and race/ethnicity.

Cox proportional hazards regression estimated time to fatal opioid-involved overdose during follow-up, with time-varying indicators for buprenorphine and psychosocial treatment exposures (Appendix Table 4). Individuals contributed person-time to analyses until the death date or censoring date, defined as the last date of the 365-day follow-up period, last date of the study period, or date of death due to other causes. Individuals were also censored on the first naltrexone fill date (n=610, 0.7%) given low use in national MOUD treatment samples (<1%).41 Estimates adjusted for all baseline characteristics and the index year to account for trends over time in opioid-involved overdose mortality. Data management and statistical analyses were performed in 2022 using SAS Enterprise Guide 8.3 and Stata 17, respectively.

To ensure robustness of findings, multiple sensitivity analyses were conducted using alternate exposure (i.e., stratified by treatment modality, restricted to incident treatment in follow-up) or outcome (i.e., excluding deaths early in follow-up) measures and calculating E-values for unmeasured confounding42 (Appendix Methods and Appendix Tables 5–8).

RESULTS

The sample included 81,616 MDBs with at least one non-fatal opioid-involved overdose (Table 1). The sample was mostly female (57.3%), 50 years or older (58.8%), white (80.9%), living in the South (42.7%), and dually eligible for Medicaid at the time of the index overdose (77.0%).

Table 1.

Baseline sample characteristics, stratified by opioid overdose death in the year after non-fatal overdose

Total
(n=81,616)		 No overdose death
(n=80,104)		 Overdose death
(n=1512)		 p-value
Sociodemographic characteristics, n (%)
 Sex
  Male 34,868 (42.7) 34,074 (42.5) 794 (52.5) <0.001
  Female 46,748 (57.3) 46,030 (57.5) 718 (47.5)
 Age
  18–29 3154 (3.9) 3087 (3.9) 67 (4.4) <0.001
  30–39 10,180 (12.5) 9944 (12.4) 236 (15.6)
  40–49 20,254 (24.8) 19,767 (24.7) 487 (32.2)
  50–59 34,049 (41.7) 33,474 (41.8) 575 (38.0)
  60–64 13,979 (17.1) 13,832 (17.3) 147 (9.7)
 Race/ethnicity
  White 65,991 (80.9) 64,682 (80.7) 1309 (86.6) <0.001
  Black 8602 (10.5) 8509 (10.6) 93 (6.2)
  Hispanic 4840 (5.9) 4762 (5.9) 78 (5.2)
  Otherb 2183 (2.7) 2151 (2.7) 32 (2.1)
 Region
  Northeast 14,844 (18.2) 14,500 (18.1) 344 (22.8) <0.001
  Midwest 17,749 (21.7) 17,430 (21.8) 319 (21.1)
  South 34,876 (42.7) 34,298 (42.8) 578 (38.2)
  West 14,147 (17.3) 13,876 (17.3) 271 (17.9)
 Dual Medicaid eligibility 62,853 (77.0) 61,721 (77.1) 1132 (74.9) 0.05
Clinical characteristics, n (%)
 Substance use disorder
  Opioids 16,496 (20.2) 16,038 (20.0) 458 (30.3) <0.001
  Alcohol 10,961 (13.4) 10,692 (13.3) 269 (17.8) <0.001
  Sedatives 3338 (4.1) 3229 (4.0) 109 (7.2) <0.001
  Cannabis 4125 (5.1) 4026 (5.0) 99 (6.5) 0.01
 Mental Health Comorbidities
  Depression 15,934 (19.5) 15,610 (19.5) 324 (21.4) 0.06
  Anxiety 26,403 (32.4) 25,858 (32.3) 545 (36.0) 0.002
  Bipolar disorder 14,583 (17.9) 14,244 (17.8) 339 (22.4) <0.001
  Schizophrenia 4857 (6.0) 4737 (5.9) 120 (7.9) <0.001
  Personality disorder 2695 (3.3) 2627 (3.3) 68 (4.5) 0.01
  Other mental disorder 33,797 (41.4) 33,105 (41.3) 692 (45.8) <0.001
 Medical Comorbidities
  Chronic Pain 47,027 (57.6) 46,183 (57.7) 844 (55.8) 0.15
  Asthma 10,444 (12.8) 10,240 (12.8) 204 (13.5) 0.41
  Cerebrovascular Disease 6654 (8.2) 6567 (8.2) 87 (5.8) <0.001
  COPD 9181 (11.2) 9036 (11.3) 145 (9.6) 0.04
  Diabetes 18,445 (22.6) 18,174 (22.7) 271 (17.9) <0.001
  Heart Failure 7901 (9.7) 7786 (9.7) 115 (7.6) 0.01
  Hepatitis C 7879 (9.7) 7691 (9.6) 188 (12.4) <0.001
  HIV 1452 (1.8) 1421 (1.8) 31 (2.1) 0.42
  Hypertension 31,797 (39.0) 31,239 (39.0) 558 (36.9) 0.10
  Pneumonia 9794 (12.0) 9575 (12.0) 219 (14.5) 0.003
  Sleep Apnea 7601 (9.3) 7495 (9.4) 106 (7.0) 0.002
 Health care utilization
  Inpatient 19,020 (23.3) 18,617 (23.2) 403 (26.7) 0.002
  Emergency department 31,354 (38.4) 30,742 (38.4) 612 (40.5) 0.10
  OUD-related psychosocial services 1164 (1.4) 1131 (1.4) 33 (2.2) 0.01
 Prescription drugs
  Buprenorphine 2230 (2.7) 2164 (2.7) 66 (4.4) <0.001
  Opioids 45,131 (55.3) 44,329 (55.3) 802 (53.0) 0.89
  Antidepressants 37,602 (46.1) 36,908 (46.1) 694 (45.9) 0.89
  Antipsychotics 18,092 (22.2) 17,687 (22.1) 405 (26.8) <0.001
  Mood Stabilizers 25,731 (31.5) 25,224 (31.5) 507 (33.5) 0.09
  Sedatives 12,225 (15.0) 11,990 (15.0) 235 (15.5) 0.54
Index overdose characteristics, n (%)
 Involved heroin or synthetic opioids 9484 (11.6) 9156 (11.4) 328 (21.7) <0.001
 Involved benzodiazepines 19,700 (24.1) 19,291 (24.1) 409 (27.1) 0.01
 Required mechanical ventilation 12,382 (15.2) 12,077 (15.1) 305 (20.2) <0.001
 Required inpatient hospitalization 60,531 (74.2) 59,411 (74.2) 1120 (74.1) 0.93
Fatal overdose characteristics, n (%)
 Involved heroin or synthetic opioids 598 (39.6)
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Note: Boldface indicates statistical significance (p<0.05).

a

p-values represent chi-square comparisons of each baseline characteristic category

b

Other race/ethnicity represents combined statistics for American Indian/Alaska Native, Asian/Pacific Islander, and Other/unknown groups in compliance with the Centers for Medicare and Medicaid Services confidentiality requirements to suppress cell sizes 1 to 10 and any cells that could be used to derive a value of 1 to 10.

COPD, chronic obstructive pulmonary disease; HIV, human immunodeficiency virus; OUD, opioid use disorder.

Over one-tenth of individuals died during follow-up (n=9439; 11.6%; Appendix Figure 2). One-quarter of deaths were drug-related (n=2430; 25.7%), and nearly two-thirds of drug-related deaths involved opioid poisoning (n=1512; 62.2%). Most opioid-involved overdose deaths were unintentional (n=1413; 93.5%) and 40% involved heroin or synthetic opioids other than methadone (n=598).

There were significant differences in unadjusted baseline characteristics between groups with and without subsequent opioid-involved overdose death (Table 1). A greater proportion of those who died were male (p<.001), under 50 years old (p<.001), and white (p<.001). Those who died had more substance use disorder and mental health diagnoses (all p<.01), except depression (p=.06). Those who died also had higher rates of hepatitis C (p<.001) and pneumonia (p=.003), but lower rates of CVD (p<.001), COPD (p=.04), diabetes (p<.001), heart failure (p=.01), and sleep apnea (p=.002). Those who died had higher rates of baseline buprenorphine use (p<.001).

Hospitalization rates during the index event were comparable (p=.93), but index events requiring mechanical ventilation (p<.001), involving heroin or synthetic opioids (p<.001), or involving benzodiazepines (p=.01) were more common among those who died.

The overall unadjusted crude mortality rate was 2174.6 opioid-involved overdose deaths per 100,000 person-years (Table 2). After accounting for the distribution of sex, age, and race/ethnicity, this translated into a mortality rate over 130 times higher than the demographically standardized general U.S. population during the same period (SMR=132.4, 95% CI=129.9, 135.0).

Table 2.

Opioid overdose mortality rates in the year after non-fatal opioid overdose, stratified by demographics

Index opioid overdose
N		 Person-years of follow-up
N		 Opioid overdose deaths
N		 Crude mortality rate
per 100,000 person-years		 Expected deaths
N		 Standardized mortality ratioa
SMR (95% CI)
TOTAL 81,616 69,531.3 1512 2174.6 11.4 132.4 (129.9, 135.0)
Demographics
 Sex
  Male 34,868 29,295.9 794 2710.3 6.2 127.1 (135.5, 139.7)
  Female 46,748 40,235.5 718 1784.5 5.2 138.8 (135.7, 141.9)
 Age
  18–29 3154 2793.6 67 2398.3 0.4 166.4 (163.8, 169.2)
  30–39 10,180 8863.8 236 2662.5 1.8 128.5 (126.5, 130.6)
  40–49 20,254 17,732.6 487 2746.4 3.4 143.7 (141.3, 146.1)
  50–59 34,049 28,730.4 575 2001.4 4.8 119.4 (117.2, 121.6)
  60–64 13,979 11,411.0 147 1288.2 1.0 150.8 (144.5, 157.4)
 Race/ethnicity
  White 65,991 56,406.3 1309 2320.7 10.1 129.4 (127.6, 131.3)
  Black 8602 7149.1 93 1300.9 0.8 113.2 (108.2, 118.6)
  Hispanic 4840 4122.1 78 1892.2 0.3 256.5 (244.1, 270.1)
  American Indian/Alaska Native 1064 910.3 12 1318.2 0.2 68.3 (60.2, 78.4)
  Asian/Pacific Islander 406 346.9 NR NR NR 910.7 (754.6, 1115.2)
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a

SMR is the ratio of observed to expected deaths in the study sample. The number of expected deaths in each group was calculated using CDC WONDER mortality data, standardized by sex, age, and race/ethnicity. Population rates were obtained for 2008–2016 using the CDC definition of opioid overdose deaths.

NR, not reportable; The Centers for Medicare and Medicaid Services require suppression of cell sizes 1 to 10 and any cells that could be used to derive a value of 1 to 10 to protect confidentiality.

SMRs were similar for males (SMR=127.1, 95% CI=135.5, 139.7) and females (SMR=138.8, 95% CI=135.7, 141.9). Young adults 18–29 years comprised the smallest proportion of opioid-involved overdose deaths but had a significantly higher SMR than all other age groups (SMR=166.4, 95% CI=163.8, 169.2). Compared to their white counterparts (SMR=129.4, 95% CI=127.6, 131.3), SMRs were significantly lower for Black (SMR=113.2, 95% CI=108.2, 118.6) and American Indian/Alaska Native (SMR=68.3, 95% CI=60.2, 78.4) groups, but significantly higher for Hispanic (SMR=265.5, 95% CI=244.1, 270.1) and Asian/Pacific Islander (SMR=910.7, 95% CI=754.6, 1115.2) groups.

In adjusted Cox model estimates, male sex (adjusted hazard ratio [aHR]=1.35, 95% CI=1.21, 1.50) and younger age were associated with higher risk of opioid-involved overdose death compared to females and ages 60–64 years, respectively (Appendix Table 4). Compared to white race/ethnicity, Black (aHR=0.59, 95% CI=0.48, 0.74) and Hispanic (aHR=0.72, 95% CI=0.57, 0.91) groups had lower risk of death.

A minority of MDBs had any OUD treatment after the index event (n=5329, 6.5%), with most receiving buprenorphine (n=3774, 70.8%) and less than half (n=2405, 45.1%) receiving psychosocial services (Table 3).

Table 3.

OUD treatment characteristics and opioid overdose mortality in the year after non-fatal opioid overdose

OUD treatment receipt in the year after non-fatal opioid overdose
None Any Buprenorphine Psychosocial
N, % 76,287 (93.5) 5329 (6.5) 3774 (4.6) 2405 (2.9)
Treatment characteristics
 Time to exposure, mean (SD) — 88.8 (103.9) 92.8 (105.9) 97.6 (105.2)
  Median — 40.0 45.0 55.0
  1–30 days, n (%) — 2464 (46.2) 1687 (44.7) 975 (40.5)
  31–90 days, n (%) — 937 (17.6) 658 (17.4) 463 (19.3)
  91–180 days, n (%) — 849 (15.9) 616 (16.3) 429 (17.8)
  181–365 days, n (%) — 1079 (20.2) 813 (21.5) 538 (22.4)
 Days treated, mean (SD) — 51.4% (35.4) 55.0% (35.8) 41.4% (32.8)
  >0–25%, n (%) — 1841 (34.5) 1148 (30.4) 1093 (45.4)
  >25–50%, n (%) — 928 (17.4) 611 (16.2) 494 (20.5)
  >50–75%, n (%) — 703 (13.2) 506 (13.4) 292 (12.1)
  >75%, n (%) — 1857 (34.8) 1509 (40.0) 526 (21.9)
  Any gap >30-days, n (%) — 3599 (67.5) 2228 (59.0) 1838 (76.4)
Mortality rates
  Person-yearsa 64,790.4 3444.6 2425.2 1491.9
  Opioid overdose deaths 1431 81 54 38
  CMRb 2208.7 2351.5 2226.6 2547.1
  SMRc (95% CI) 135.3 (132.7, 138.0) 96.2 (94.7, 97.8) 89.7 (88.3, 91.2) 100.1 (98.5, 101.8)
Hazard ratio (95% CI) d — — 0.38 (0.23, 0.64) 1.18 (0.71, 1.95)
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a

Person-years were calculated based on exposed follow-up time after initiating treatment, excluding time between the index event and treatment initiation to minimize bias in mortality rates

b

CMR represents the rate per 100,000 person-years

c

SMR is the ratio of observed to expected deaths in the study sample. The number of expected deaths in each group was calculated using CDC WONDER mortality data, standardized by sex, age, and race/ethnicity. Population rates were obtained for 2008–2016 using the CDC definition of opioid overdose deaths.

d

Results of multivariable Cox proportional hazards models adjusted for all baseline sociodemographic and clinical characteristics (see Appendix Table 4 for full model results).

OUD, opioid use disorder; CMR, crude mortality rate; SMR, standardized mortality rate ratio; CI, confidence interval; SD, standard deviation.

Among MDBs receiving OUD treatment, average time to exposure was 92.8 days for buprenorphine (median=45.0) and 97.6 days for psychosocial services (median=55.0). Less than half of those receiving buprenorphine (n=1687, 44.7%) or psychosocial services (n=975, 40.5%) had treatment in the first 30 follow-up days. Over 20% had no treatment in the first 6 months of follow-up (buprenorphine n=813, 21.5%; psychosocial n=538, 22.4%).

OUD treatment exposure was inconsistent (Table 3). On average, MDBs with buprenorphine had medication supply on slightly over half of exposed follow-up days (55.0%) and most had at least one treatment gap >30 days (n=2228, 59.0%). On average, those with psychosocial treatment were exposed on 41.4% of follow-up days by the 30-day definition and most had at least one treatment gap >30 days (n=1838, 76.4%).

Overall mortality rates were elevated compared to the standardized reference population (Table 3). However, there were differences by treatment status. MDBs with no follow-up OUD treatment had the highest SMR (SMR=135.3, 95% CI=132.7, 138.0), while SMRs were lower for those with any buprenorphine (SMR=89.7, 95% CI=88.3, 91.2) or any OUD-related psychosocial services (SMR=100.1, 95% CI=98.5, 101.8).

In adjusted Cox model estimates, buprenorphine had the strongest association with subsequent opioid-involved overdose mortality, with significantly lower risk of death (aHR=0.38, 95% CI=0.23, 0.64). OUD-related psychosocial services were not significantly associated with risk of death (aHR=1.18, 95% CI=0.71, 1.95).

Sensitivity results were consistent with primary analyses, and E-values indicated robustness to unmeasured confounding (Appendix Tables 5–8).

DISCUSSION

Buprenorphine was associated with a 62% reduction in risk of opioid-involved overdose death in the year after non-fatal opioid-involved overdose, despite patterns reflecting delayed and inconsistent treatment access or use. The magnitude of this effect is similar to an all-payer study estimating a 69% reduction in opioid-involved overdose mortality risk during buprenorphine treatment,21 suggesting the effectiveness of buprenorphine for MDBs is comparable to the general population.

Yet, buprenorphine uptake was low and indicative of limited access to timely treatment, which could contribute to elevated opioid-involved overdose mortality given buprenorphine is associated with reduced risk of death.2,3,21 For example, 2.1% of the sample received buprenorphine in the first 30 follow-up days, consistent with studies of multi-payer (2.2%)17 and veteran (1.3%)12 samples. Since all individuals presented to acute care settings and 1 in 5 had documented OUD diagnoses prior to presentation, this signals an overwhelming need to improve the health system response to life-threatening events with life-saving treatment. Increased efforts to implement hospital-based MOUD induction and warm hand-offs to community providers43 are potentially critical to reduce opioid-related morbidity and mortality. Despite effectiveness of ED-initiated buprenorphine, uptake may be limited by inadequate training, as few ED physicians report preparedness to treat OUD.44,45 Formal training may facilitate readiness44 by addressing identified gaps in knowledge,45 but clinical decision support may not be sufficient46 to overcome systemic barriers related to a lack of treatment and referral protocols, support staff, and other resources to address logistical challenges in acute care contexts.44,45

In addition to strengthening the initial connection to OUD treatment, interventions that facilitate medication continuity after induction could further reduce risk of adverse opioid-related outcomes.47,48 Most of the sample receiving buprenorphine had sporadic treatment (e.g., minimal follow-up days with medication, substantial gaps in supply), which is linked with increased mortality risk.2,3 Additionally, a higher proportion of those who died had baseline buprenorphine use, possibly signaling OUD severity. While baseline buprenorphine was not significantly associated with mortality in adjusted analyses, sporadic medication access or use could contribute to opioid-related morbidity. Assessing potential risk49 and protective factors50 and ensuring adequate support services are available51 through delivery or referral to specialty care for co-occurring medical and behavioral health problems may promote buprenorphine treatment continuity.

To the authors’ knowledge, this is the first study to examine the relationship of outpatient OUD-specific psychosocial services with subsequent opioid-involved overdose mortality. The low uptake of psychosocial services was concentrated among individuals without buprenorphine, reflecting a substantial gap in evidence-based treatment. Though results were inconclusive due to low treatment exposure leading to uncertainty in estimates, psychosocial services were not significantly associated with opioid-involved overdose mortality risk, consistent with evidence that medication with psychosocial treatment is no more effective at reducing adverse opioid-related outcomes than medication alone.52–54

Overall, 1.9% of MDBs had fatal opioid-involved overdoses in follow-up, aligning with previous estimates for any drug overdose death (2.4%).8 Nonetheless, rates of opioid-involved overdose mortality were markedly elevated compared to the general population. While high mortality rates may be related to factors other than OUD treatment (e.g., type and severity of disability, prevalence of secondary conditions), the findings coincide with national trends.22 Mortality risk was higher for males and younger adults, and similarly high for white and American Indian/Alaska Native groups. Risk was also comparable for Asian/Pacific Islander or Other race/ethnicity, but small samples and uncertainty in estimates preclude definitive interpretations. Although Black and Hispanic groups had lower risk, these relationships may not persist over time given recent acceleration in opioid-involved overdose mortality rates among Black Americans.55 Continued research in large diverse samples could improve understanding of shifting racial/ethnic disparities in overdose risk.

Limitations

Findings should be interpreted in the context of several limitations. First, although the data are generalizable to the Medicare Part D population,32 results may not be representative of all adults with disabilities, such as those with Medicaid coverage based on non-federal disability determinations, those who report living with disability but do not qualify for public insurance, and those with private or no insurance. Also, results may not generalize to non-fatal opioid-involved overdoses that are untreated or treated outside acute care settings or to individuals with no opioid-involved overdose history who could benefit from low-threshold buprenorphine treatment in community-based settings other than conventional health care contexts.56

Second, some exposures and outcomes may have been underestimated. The data do not capture treatment funded by non-Medicare sources (e.g., block grants, other public programs, self-pay, self-help, peer support), including methadone, which is a highly effective medication57 that Medicare did not cover until 2020 but should be examined in future research. The data also preclude measurement of non-prescribed buprenorphine use, which is associated with reduced risk of adverse opioid-related outcomes, including overdose.50,58 While specified drug involvement in cause of death codes has improved over time, opioid-involved overdose fatalities may have been misclassified as non-opioid deaths due to data limitations.59 Thus, findings represent conservative estimates of opioid-involved overdose mortality and the association with OUD treatment.

Alternatively, treatment need and exposures may have been overestimated. Some individuals with non-fatal opioid-involved overdose may not meet criteria for OUD. Additionally, although buprenorphine approved for pain treatment was excluded, Medicare-covered buprenorphine exposures may include off-label prescriptions for pain management,60 which suggests treatment rates could be lower than observed estimates. Also, psychosocial services were defined as 30-day exposures, and the duration of treatment benefits may be shorter. Finally, although models adjusted for a range of individual and treatment characteristics, causal inferences are not possible due to potential residual confounding by unobserved covariates.

CONCLUSIONS

Low buprenorphine treatment after non-fatal opioid-involved overdose highlights the importance of expanding MOUD induction in acute care settings. Buprenorphine substantially reduced risk of subsequent opioid-involved overdose mortality, despite delayed and inconsistent treatment. Disproportionately high opioid-involved overdose mortality rates and low rates of OUD treatment uptake indicate that the disability population is particularly vulnerable to opioid-related morbidity and mortality. In addition to comprising a priority group for prevention and treatment efforts, the disability population has a high concentration of socioeconomic disadvantage61 and efforts to increase treatment engagement and continuity in this group could help address disparities in health care and outcomes.

Supplementary Material

1

Acknowledgements:

This study was supported by funding from the National Institute on Drug Abuse (grant numbers: K01DA049950 [PI: Samples], R01DA047347 [PI: Crystal], K23DA044342 [PI: Williams]) and the National Center for Advancing Translational Sciences (grant number: UL1TR003017). The funding source had no role in the study design; data acquisition, analyses, or interpretation; or in the writing or publication of results.

Dr. Samples has received consulting fees from the American Society of Addiction Medicine. Dr. Williams receives consulting fees, equity, and travel expenses from Ophelia Health, Inc. No other authors have financial disclosures to report.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

CRediT author statement: Hillary Samples: conceptualization; methodology; data curation; formal analysis; validation; visualization; supervision; writing – original draft; writing – review & editing. Molly Nowels: data curation; formal analysis; writing – review & editing. Arthur R. Williams: conceptualization; writing – review & editing. Mark Olfson: conceptualization; methodology; supervision; writing – review & editing. Stephen Crystal: conceptualization; methodology; supervision; writing – review & editing.

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