Firearm-Related Injuries and the US Opioid and Other Substance Use Epidemic: A Nationwide Evaluation of Emergency Department Encounters.

INTRODUCTION: There has been a sharp climb in the Unites States' death rate among opioid and other substance abuse patients, as well as an increased prevalence in gun violence. We aimed to investigate the association between substance abuse and gun violence in a national sample of patients presenting to US emergency departments (EDs). METHODS: We queried the 2018-2019 Nationwide Emergency Department Sample for patients ≥18 years with substance abuse disorders (opioid and other) using International Classification of Diseases, 10th Revision, Clinical Modification codes. Within this sample, we analyzed characteristics and outcomes of patients with firearm-related injuries. The primary outcome was mortality; secondary outcomes were ED charges and length of stay. RESULTS: Among the 25.2 million substance use disorder (SUD) patients in our analysis, 35,306 (0.14%) had a firearm-related diagnosis. Compared to other SUD patients, firearm-SUD patients were younger (33.3 versus 44.7 years, P < 0.001), primarily male (88.6% versus 54.2%, P < 0.001), of lower-income status (0-25th percentile income: 56.4% versus 40.5%, P < 0.001), and more likely to be insured by Medicaid or self-pay (71.6% versus 53.2%, P < 0.001). Firearm-SUD patients had higher mortality (1.4% versus 0.4%, P < 0.001), longer lengths of stay (6.5 versus 4.9 days, P < 0.001), and higher ED charges ($9269 versus $5,164, P < 0.001). Firearm-SUD patients had a 60.3% rate of psychiatric diagnoses. Firearm-SUD patients had 5.5 times greater odds of mortality in adjusted analyses (adjusted odds ratio: 5.5, P < 0.001). CONCLUSIONS: Opioid-substance abuse patients with firearm injuries have higher mortality rates and costs among these groups, with limited discharge to postacute care resources. All these factors together point to the urgent need for improved screening and treatment for this vulnerable group of patients.

Patients' willingness to pay for naloxone: A national cross-sectional survey of prescription opioid users with chronic pain in the United States.

BACKGROUND: Millions of U.S. people have been heavily affected by opioids. In March 2023, the Food and Drug Administration approved naloxone as an over-the-counter medication. This has allowed more access to patients at high risk of opioid overdose. However, the patient's willingness to pay for naloxone at the pharmacy counter has not been assessed. OBJECTIVES: This study aimed to characterize factors associated with the willingness to pay for naloxone among the patient group. METHODS: A cross-sectional Qualtrics online panel survey instrument was developed. This survey was distributed to patients in the United States, aged ≥ 18 years, with any chronic pain and taking opioids. The survey included demographics, and clinical characteristics (pain assessment, opioid use, and knowledge of naloxone). In addition, willingness to pay was assessed using a 7-point Likert scale ranging from strongly disagree to strongly agree. An ordinal logistic regression model was used to examine demographic and clinical characteristics. RESULTS: A total of 549 subjects completed the survey (women [53.01%], white or Caucasian (83.61%), age mean [SD] 44 [13]). Women were associated with less willingness to pay (adjusted odds ratio [aOR] 0.685 [95% CI 0.478-0.983], P = 0.0403). Compared with the high household income group (≥ $150,000), low household income ≤ $25,000 (aOR 0.326 [95% CI 0.160-0.662], P = 0.0020) or income between $25,000 and 74,999 (aOR 0.369 [95% CI 0.207-0.657], P = 0.0007) was associated with less likelihood of willing to pay. Patients with a previous diagnosis of obstructive sleep apnea were associated with a higher likelihood of willingness to pay (aOR 1.685 [95% CI 1.138-2.496], P = 0.0092). Each unit increase in pain was also associated with a higher likelihood of willingness to pay (aOR 1.247 [95% CI 1.139-1.365], P < 0.0001). CONCLUSIONS: Demographics and clinical factors were associated with willingness to pay for naloxone. This study's findings are useful in the development of interventions to address pharmacy-based naloxone distribution programs.

Association Between Cost Sharing and Naloxone Prescription Dispensing.

Importance: Increasing access to naloxone (an opioid antagonist that can reverse overdose) could slow the US opioid epidemic. Prior studies suggest cost sharing may be a barrier to dispensing of naloxone prescriptions, but these studies were limited by their cross-sectional designs and use of databases that do not capture prescriptions that are not filled (abandoned). Objective: To evaluate the association between cost sharing and naloxone prescription abandonment (nondispensing of naloxone prescriptions). Design, Setting, and Participants: This cross-sectional, regression discontinuity analysis exploited the fact that deductibles typically reset at the beginning of the year in commercial and Medicare plans. The included data were derived from the 2020-2021 IQVIA Formulary Impact Analyzer (a pharmacy transactions database that represents 63% of prescriptions at US pharmacies). The analysis included claims for naloxone nasal spray among commercially insured patients and Medicare patients that occurred during the 60 days before January 1, 2021, through 59 days after January 1, 2021. Exposure: Cost sharing, which is defined as the amount patients would have to pay to fill prescriptions. Main Outcomes and Measures: Local linear regression models were used to assess for abrupt changes in cost sharing and the probability of prescription abandonment on January 1, 2021. To estimate the association between cost sharing and prescription abandonment, a fuzzy regression discontinuity analysis was conducted. Results: These analyses included naloxone claims for 71 306 commercially insured patients and 101 706 Medicare patients (40 019 [56.1%] and 61 410 [60.4%], respectively, were female). The commercially insured patients and Medicare patients accounted for 73 311 and 106 076 naloxone claims, respectively. On January 1, 2021, the mean cost sharing per claim increased by $15.0 (95% CI, $13.8-$16.2) for commercially insured patients and increased by $12.3 (95% CI, $10.9-$13.6) for Medicare patients and the probability of abandonment increased by 4.7 (95% CI, 3.2-6.2) percentage points and 2.8 (95% CI, 1.6-4.1) percentage points, respectively. The results from the fuzzy regression discontinuity analysis suggest a decision by commercial and Medicare plans to increase naloxone cost sharing by $10 would be associated with percentage-point increases of 3.1 (95% CI, 2.2-4.1) and 2.3 (95% CI, 1.4-3.2), respectively, in the probability of abandonment. Conclusions: The elimination of cost sharing might be associated with increased naloxone dispensing to commercially insured and Medicare patients.

Variation in Initiation, Engagement, and Retention on Medications for Opioid Use Disorder Based on Health Insurance Plan Design.

BACKGROUND: The association between cost-sharing and receipt of medication for opioid use disorder (MOUD) is unknown. METHODS: We constructed a cohort of 10,513 commercially insured individuals with a new diagnosis of opioid use disorder and information on insurance cost-sharing in a large national deidentified claims database. We examined 4 cost-sharing measures: (1) pharmacy deductible; (2) medical service deductible; (3) pharmacy medication copay; and (4) medical office copay. We measured MOUD (naltrexone, buprenorphine, or methadone) initiation (within 14 d of diagnosis), engagement (second receipt within 34 d of first), and 6-month retention (continuous receipt without 14-d gap). We used multivariable logistic regression to assess the association between cost-sharing and MOUD initiation, engagement, and retention. We calculated total out-of-pocket costs in the 30 days following MOUD initiation for each type of MOUD. RESULTS: Of 10,513 individuals with incident opioid use disorder, 1202 (11%) initiated MOUD, 742 (7%) engaged, and 253 (2%) were retained in MOUD at 6 months. A high ($1000+) medical deductible was associated with a lower odds of initiation compared with no deductible (odds ratio: 0.85, 95% confidence interval: 0.74-0.98). We found no significant associations between other cost-sharing measures for initiation, engagement, or retention. Median initial 30-day out-of-pocket costs ranged from $100 for methadone to $710 for extended-release naltrexone. CONCLUSIONS: Among insurance plan cost-sharing measures, only medical services deductible showed an association with decreased MOUD initiation. Policy and benefit design should consider ways to reduce cost barriers to initiation and retention in MOUD.

Association Between Changes in Postoperative Opioid Utilization and Long-Term Health Care Spending Among Surgical Patients With Chronic Opioid Utilization.

BACKGROUND: There is growing interest in identifying and developing interventions aimed at reducing the risk of increased, long-term opioid use among surgical patients. While understanding how these interventions impact health care spending has important policy implications and may facilitate the widespread adoption of these interventions, the extent to which they may impact health care spending among surgical patients who utilize opioids chronically is unknown. METHODS: This study was a retrospective analysis of administrative health care claims data for privately insured patients. We identified 53,847 patients undergoing 1 of 10 procedures between January 1, 2004, and September 30, 2018 (total knee arthroplasty, total hip arthroplasty, laparoscopic cholecystectomy, open cholecystectomy, laparoscopic appendectomy, open appendectomy, cesarean delivery, functional endoscopic sinus surgery, transurethral resection of the prostate, or simple mastectomy) who had chronic opioid utilization (≥10 prescriptions or ≥120-day supply in the year before surgery). Patients were classified into 3 groups based on differences in opioid utilization, measured in average daily oral morphine milligram equivalents (MMEs), between the first postoperative year and the year before surgery: "stable" (<20% change), "increasing" (≥20% increase), or "decreasing" (≥20% decrease). We then examined the association between these 3 groups and health care spending during the first postoperative year, using a multivariable regression to adjust for observable confounders, such as patient demographics, medical comorbidities, and preoperative health care utilization. RESULTS: The average age of the sample was 62.0 (standard deviation [SD] 13.1) years, and there were 35,715 (66.3%) women. Based on the change in average daily MME between the first postoperative year and the year before surgery, 16,961 (31.5%) patients were classified as "stable," 15,463 (28.7%) were classified as "increasing," and 21,423 (39.8%) patients were classified as "decreasing." After adjusting for potential confounders, "increasing" patients had higher health care spending ($37,437) than "stable" patients ($31,061), a difference that was statistically significant ($6377; 95% confidence interval [CI], $5669-$7084; P < .001), while "decreasing" patients had lower health care spending ($29,990), a difference (-$1070) that was also statistically significant (95% CI, -$1679 to -$462; P = .001). These results were generally consistent across an array of subgroup and sensitivity analyses. CONCLUSIONS: Among patients with chronic opioid utilization before surgery, subsequent increases in opioid utilization during the first postoperative year were associated with increased health care spending during that timeframe, while subsequent decreases in opioid utilization were associated with decreased health care spending.

Associations Between Copays, Coverage Limits for Opioid Use Disorder Medications, and Prescribing in Medicaid, 2018.

BACKGROUND: Opioid use disorder (OUD) affects millions of Americans, but only a fraction receive treatment. Many patients with OUD are enrolled in Medicaid, but elements of different state Medicaid programs' drug benefit designs may impact patients' access to life-saving care. OBJECTIVE: To describe medication for OUD (mOUD) use in Medicaid and examine the relationship between mOUD use and state drug benefit design plans. DESIGN/SUBJECTS: Cross-sectional study using Medicaid State Drug Utilization Data from 2018 to quantify office-based mOUD and the Medicaid Behavioral Health Services Database to extract copay amounts and coverage limits for mOUD. We excluded states with <5% coverage and assessed for associations between copays or coverage limits and mOUD dispensing using simple linear regression. MEASURES: Proportion of mOUD prescriptions relative to all prescriptions, opioid prescriptions, and the state-level prevalence of pain reliever use disorder and association between copays, coverage limits and these proportions. RESULTS: There was substantial variability in mOUD use. Although state Medicaid drug benefit designs also varied, we found no significant relationship between copay requirements (yes/no), coverage limits (yes/no), copay amount ($0-$0.99 vs. $1 or more), and mOUD utilization measures. CONCLUSIONS: Substantial state-level variation exists in mOUD use, but we did not find a significant association between copays or coverage limits and use in Medicaid. Further research is needed to assess other potential impacts of mOUD drug benefit design elements in Medicaid.

State-Level Economic Costs of Opioid Use Disorder and Fatal Opioid Overdose - United States, 2017.

Approximately 47,000 persons in the United States died from an opioid-involved overdose in 2018 (1), and 2.0 million persons met the diagnostic criteria for an opioid use disorder in 2017 (2). The economic cost of the U.S. opioid epidemic in 2017 was estimated at $1,021 billion, including cost of opioid use disorder estimated at $471 billion and cost of fatal opioid overdose estimated at $550 billion (3). CDC used national-level cost estimates to estimate the state-level economic cost of opioid use disorder and fatal opioid overdose during 2017. Cases and costs of state-level opioid use disorder and fatal opioid overdose and per capita costs were calculated for each of the 38 states and the District of Columbia (DC) that met drug specificity requirements for mortality data (4). Combined costs of opioid use disorder and fatal opioid overdose (combined costs) varied substantially, ranging from $985 million in Wyoming to $72,583 million in Ohio. Per capita combined costs also varied considerably, ranging from $1,204 in Hawaii to $7,247 in West Virginia. States with high per capita combined costs were mainly in two regions: the Ohio Valley and New England. Federal and state public health agencies can use these data to help guide decisions regarding research, prevention and response activities, and resource allocation.

Cost-Effectiveness of an Opioid Abuse-Prevention Program Using the Narcotics Information Management System in South Korea.

OBJECTIVES: To assess the cost-effectiveness of an opioid abuse-prevention program embedded in the Narcotics Information Management System ("the Network System to Prevent Doctor-Shopping for Narcotics") in South Korea. METHODS: Using a Markov model with a 1-year cycle length and 30-year time horizon, we estimated the incremental cost-utility ratio (ICUR) of implementing an opioid abuse-prevention program in patients prescribed outpatient opioids from a Korean healthcare payer's perspective. The model has 6 health states: no opioid use, therapeutic opioid use, opioid abuse, overdose, overdose death, and all-cause death. Patient characteristics, healthcare costs, and transition probabilities were estimated from national population-based data and published literature. Age- and sex-specific utilities of the general Korean population were used for the no-use state, whereas the other health-state utilities were obtained from published studies. Costs (in 2019 US dollars) included the expenses of the program, opioids, and overdoses. An annual 5% discount rate was applied to the costs and quality-adjusted life-years (QALYs). Parameter uncertainties were explored via deterministic and probabilistic sensitivity analyses. RESULTS: The program was associated with 2.27 fewer overdoses per 100 000 person-years, with an ICUR of $227/QALY. The ICURs were generally robust to parameter changes, although the program's effect on abuse reduction was the most influential parameter. Probabilistic sensitivity analysis showed that the program reached a 100% probability of cost-effectiveness at a willingness-to-pay threshold of $900/QALY. CONCLUSIONS: The opioid abuse-prevention program appears to be cost-effective in South Korea. Mandatory use of the program should be considered to maximize clinical and economic benefits of the program.

Economic Evaluation in Opioid Modeling: Systematic Review.

OBJECTIVES: The rapid increase in opioid overdose and opioid use disorder (OUD) over the past 20 years is a complex problem associated with significant economic costs for healthcare systems and society. Simulation models have been developed to capture and identify ways to manage this complexity and to evaluate the potential costs of different strategies to reduce overdoses and OUD. A review of simulation-based economic evaluations is warranted to fully characterize this set of literature. METHODS: A systematic review of simulation-based economic evaluation (SBEE) studies in opioid research was initiated by searches in PubMed, EMBASE, and EbscoHOST. Extraction of a predefined set of items and a quality assessment were performed for each study. RESULTS: The screening process resulted in 23 SBEE studies ranging by year of publication from 1999 to 2019. Methodological quality of the cost analyses was moderately high. The most frequently evaluated strategies were methadone and buprenorphine maintenance treatments; the only harm reduction strategy explored was naloxone distribution. These strategies were consistently found to be cost-effective, especially naloxone distribution and methadone maintenance. Prevention strategies were limited to abuse-deterrent opioid formulations. Less than half (39%) of analyses adopted a societal perspective in their estimation of costs and effects from an opioid-related intervention. Prevention strategies and studies' accounting for patient and physician preference, changing costs, or result stratification were largely ignored in these SBEEs. CONCLUSION: The review shows consistently favorable cost analysis findings for naloxone distribution strategies and opioid agonist treatments and identifies major gaps for future research.

Changes in For-Profit Medication-Assisted Therapy Clinics in an Appalachian City.

OBJECTIVES: This study is a follow-up to previous research regarding buprenorphine medication-assisted therapy (MAT) in Johnson City, Tennessee. For-profit MAT clinics were surveyed to determine changes in tapering practice patterns and insurance coverage during the last 3 years. METHODS: Johnson City for-profit MAT clinics; also called office based opioid treatment centers, were surveyed by telephone. Clinic representatives were asked questions regarding patient costs for therapy, insurance coverage, counseling offered onsite, and opportunities for tapering while pregnant. RESULTS: All of the MAT clinics representatives indicated that tapering in pregnancy could be considered even though tapering in pregnancy is contrary to current national guidelines. Forty-three percent of the clinics now accept insurance as compared with 0% in the 2016 study. The average weekly cost per visit remained consistent. CONCLUSIONS: The concept of tapering buprenorphine during pregnancy appears to have become a standard of care for this community, as representatives state it is offered at all of the clinics that were contacted. Representatives from three clinics stated the clinics require tapering, even though national organizations such as the American College of Obstetricians and Gynecologists and the American Society of Addiction Medicine do not recommend this approach. Although patients who have government or other insurance are now able to obtain buprenorphine with no expense at numerous clinics, the high cost for uninsured patients continues to create an environment conducive to buprenorphine diversion.

Trends in Morbidity, Mortality, and Cost of Hospitalizations Associated With Infectious Disease Sequelae of the Opioid Epidemic.

BACKGROUND: Increases in fatal drug poisonings and hepatitis C infections associated with the opioid epidemic are relatively well defined, because passive surveillance systems for these conditions exist. Less described is the association between the opioid epidemic and skin, soft-tissue, and venous infections (SSTVIs), endocarditis, sepsis, and osteomyelitis. METHODS: Michigan hospitalizations between 2016 and 2018 that included an International Classification of Diseases, Tenth Revision, Clinical Modification, code indicating substance use were examined for codes indicative of infectious conditions associated with injecting drugs. Trends in these hospitalizations were examined, as were demographic characteristics, discharge disposition, payer, and cost data. RESULTS: Among hospitalized patients with a substance use diagnosis code, endocarditis, osteomyelitis, sepsis, and SSTVI hospitalizations increased by 33%, 35%, 24%, and 12%, respectively between 2016 and 2018. During this time frame, 1257 patients died or were discharged to hospice. All SSTVI hospitalizations resulted in >$1.3 billion in healthcare costs. Public insurance accounted for more than two-thirds of all hospitalization costs. CONCLUSIONS: This study describes a method for performing surveillance for infection-related sequelae of injection drug use. Endocarditis, osteomyelitis, sepsis, and SSTVI hospitalizations have increased year over year between 2016 and 2018. These hospitalizations result in significant morbidity, mortality, and healthcare costs and should be a focus of future surveillance and prevention efforts.

Healthcare Access and Utilization Among Persons Who Inject Drugs in Medicaid Expansion and Nonexpansion States: 22 United States Cities, 2018.

BACKGROUND: Medicaid expansion under the Affordable Care Act increased insurance coverage, access to healthcare, and substance use disorder treatment, for many Americans. We assessed differences in healthcare access and utilization among persons who inject drugs (PWID) by state Medicaid expansion status. METHODS: In 2018, PWID were interviewed in 22 US cities for National HIV Behavioral Surveillance. We analyzed data from PWID aged 18-64 years who reported illicit use of opioids (n = 9957) in the past 12 months. Poisson regression models with robust standard errors were used to estimate adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) were used to examine differences by Medicaid expansion status in indicators of healthcare access and utilization. RESULTS: Persons who inject drugs in Medicaid expansion states were more likely to have insurance (87% vs 36%; aPR, 2.3; 95% CI, 2.0-2.6), a usual source of healthcare (53% vs 34%; aPR, 1.5; 95% CI, 1.3-1.9), and have used medication-assisted treatment (61% vs 36%; aPR, 1.4; 95% CI, 1.1-1.7), and they were less likely to have an unmet need for care (21% vs 39%; aPR, 0.6; 95% CI, 0.4-0.7) than those in nonexpansion states. CONCLUSIONS: Low insurance coverage, healthcare access, and medication-assisted treatment utilization among PWID in some areas could hinder efforts to end the intertwined human immunodeficiency virus and opioid overdose epidemics.

Disparities in United States hospitalizations for serious infections in patients with and without opioid use disorder: A nationwide observational study.

BACKGROUND: Patients with opioid use disorder (OUD) who are hospitalized for serious infections requiring prolonged intravenous antibiotics may face barriers to discharge, which could prolong hospital length of stay (LOS) and increase financial burden. We investigated differences in LOS, discharge disposition, and charges between hospitalizations for serious infections in patients with and without OUD. METHODS AND FINDINGS: We utilized the 2016 National Inpatient Sample-a nationally representative database of all discharges from US acute care hospitals. The population of interest was all hospitalizations for infective endocarditis, epidural abscess, septic arthritis, or osteomyelitis. The exposure was OUD, and the primary outcome was LOS until discharge, assessed by using a competing risks analysis to estimate adjusted hazard ratios (aHRs). Adjusted odds ratio (aOR) of discharge disposition and adjusted differences in hospital charges were also reported. Of 95,470 estimated hospitalizations for serious infections (infective endocarditis, epidural abscess, septic arthritis, and osteomyelitis), the mean age was 49 years and 35% were female. 46% had Medicare (government-based insurance coverage for people age 65+ years), and 70% were non-Hispanic white. After adjustment for potential confounders, OUD was associated with a lower probability of discharge at any given LOS (aHR 0.61; 95% CI 0.59-0.63; p < 0.001). OUD was also associated with lower odds of discharge to home (aOR 0.38; 95% CI 0.33-0.43; p < 0.001) and higher odds of discharge to a post-acute care facility (aOR 1.85; 95% CI 1.57-2.17; p < 0.001) or patient-directed discharge (also referred to as "discharge against medical advice") (aOR 3.47; 95% CI 2.80-4.29; p < 0.001). There was no significant difference in average total hospital charges, though daily hospital charges were significantly lower for patients with OUD. Limitations include the potential for unmeasured confounders and the use of billing codes to identify cohorts. CONCLUSIONS: Our findings suggest that among hospitalizations for some serious infections, those involving patients with OUD were associated with longer LOS, higher odds of discharge to post-acute care facilities or patient-directed discharge, and similar total hospital charges, despite lower daily charges. These findings highlight opportunities to improve care for patients with OUD hospitalized with serious infections, and to reduce the growing associated costs.

Economic burden and clinical impact of preoperative opioid dependence for patients undergoing lower extremity bypass surgery.

OBJECTIVE: Surgeons' prescription practices and the opioid epidemic have received significant attention in the media. Limited data exist, however, on the impact of prior or coexistent opioid use on vascular surgery outcomes. This study aimed to quantify the incidence, economic burden, and clinical impact of pre-existing opioid dependency in patients undergoing lower extremity bypass (LEB) surgery. METHODS: Data were collected from 1,132,645 weighted (230,858 unweighted) patient admissions for LEB in the National Inpatient Sample for the years 2002 to 2015. Patients with a concomitant diagnosis of opioid abuse or dependency were identified using International Classification of Diseases, Ninth Revision codes. Matched cohorts of patients with (n = 606 unweighted) and without (n = 32,343 unweighted) opioid dependence were created using coarsened exact matching to control for patient demographics. Linear regression was used to control for hospital-level factors and to identify differential outcomes for patients with opioid dependency. Our primary end points were hospital cost and length of stay. Our secondary end points were surgical complications and in-hospital mortality. RESULTS: There were 1,132,645 (230,858 unweighted) patient admissions for LEB in the National Inpatient Sample during 2002 to 2015. There were 3190 (0.3%) patients (643 unweighted) who had a diagnosis of pre-existing opioid dependency. The incidence of opioid dependency rose over time (2002, 0.13%; 2015, 0.63%; R2 = 0.90; P < .001). Before matching, opioid-dependent patients were younger (53.9 ± 12.3 years vs 66.7 ± 12.1 years; P < .001) and more likely to be male (65.2% vs 61.9%; P < .001), to be nonwhite (37.9% vs 24.1%; P < .001), to pay with Medicaid (29.6% vs 7.4%; P < .001), and to fall in the lowest income quartile based on ZIP code (39.6% vs 27.5%; P < .001). After matching, opioid-dependent patients (n = 606 unweighted vs n = 32,343 unweighted nonopioid-dependent patients) were at increased risk of surgical site infections (odds ratio [OR], 1.61; P = .006), major bleeding (OR, 1.56; P = .04), acute kidney injury (OR, 1.46; P = .02), and deep venous thrombosis (OR, 2.53; P = .005). Linear regression of matched cohorts revealed that opioid-dependent patients had an increased length of hospital stay (11.76 days vs 9.80 days; P < .001) and an increased mean inflation-adjusted in-hospital cost of U.S. $7032 ($37,522 vs $30,490; P < .001). CONCLUSIONS: The incidence of pre-existing opioid dependency in patients undergoing LEB continues to rise. Patients with opioid use disorder undergoing LEB surgery have substantial increases in length of hospital stay and costs. These findings highlight the importance of early preoperative recognition of this disorder in vascular surgery patients and open the opportunity for early intervention in that cohort.

Relative Cost Differences of Initial Treatment Strategies for Newly Diagnosed Opioid Use Disorder: A Cohort Study.

BACKGROUND: Relative costs of care among treatment options for opioid use disorder (OUD) are unknown. METHODS: We identified a cohort of 40,885 individuals with a new diagnosis of OUD in a large national de-identified claims database covering commercially insured and Medicare Advantage enrollees. We assigned individuals to 1 of 6 mutually exclusive initial treatment pathways: (1) Inpatient Detox/Rehabilitation Treatment Center; (2) Behavioral Health Intensive, intensive outpatient or Partial Hospitalization Services; (3) Methadone or Buprenorphine; (4) Naltrexone; (5) Behavioral Health Outpatient Services, or; (6) No Treatment. We assessed total costs of care in the initial 90 day treatment period for each strategy using a differences in differences approach controlling for baseline costs. RESULTS: Within 90 days of diagnosis, 94.8% of individuals received treatment, with the initial treatments being: 15.8% for Inpatient Detox/Rehabilitation Treatment Center, 4.8% for Behavioral Health Intensive, Intensive Outpatient or Partial Hospitalization Services, 12.5% for buprenorphine/methadone, 2.4% for naltrexone, and 59.3% for Behavioral Health Outpatient Services. Average unadjusted costs increased from $3250 per member per month (SD $7846) at baseline to $5047 per member per month (SD $11,856) in the 90 day follow-up period. Compared with no treatment, initial 90 day costs were lower for buprenorphine/methadone [Adjusted Difference in Differences Cost Ratio (ADIDCR) 0.65; 95% confidence interval (CI), 0.52-0.80], naltrexone (ADIDCR 0.53; 95% CI, 0.42-0.67), and behavioral health outpatient (ADIDCR 0.54; 95% CI, 0.44-0.66). Costs were higher for inpatient detox (ADIDCR 2.30; 95% CI, 1.88-2.83). CONCLUSION: Improving health system capacity and insurance coverage and incentives for outpatient management of OUD may reduce health care costs.

The Effect of Opioid Dependence on Firearm Injury Treatment Outcomes: A Nationwide Analysis.

BACKGROUND: Both the opioid and gun violence epidemics are recurrent public health issues in the United States. We sought to determine the effect of opioid dependence on gunshot injury treatment outcomes. MATERIALS AND METHODS: Using the 2016 National Readmission Database, patients were included if they had a principal diagnosis of firearm injury. Opioid dependence was identified using appropriate International Classification of Diseases, 10th Revision, Clinical Modification codes. The primary outcome was 30-day all-cause readmission. Secondary outcomes were in-hospital and 1-year mortality, resource utilization, and most common reasons for admission and readmission. Confounders were adjusted for using multivariate regression analysis. RESULTS: A total of 31,303 patients were included, 695 of whom were opioid dependent. Opioid-dependent patients were more likely to be young (35.1 y, range: 33.4-36.7 y) and male (89.9%) compared with patients without opioid dependence. Opioid dependence was associated with higher 30-day readmission rates (adjusted odds ratio [aOR]: 1.67, 95% confidence interval [CI]: 1.12-2.50, P = 0.01). However, opioid dependence was associated with lower in-hospital (aOR: 0.16, CI: 0.07-0.38, P < 0.01) and 1-year (aOR: 0.15, CI: 0.06-0.38, P < 0.01) mortality, longer mean length of stay (adjusted mean difference [aMD]: 2.09 d, CI: 0.43-3.76, P = 0.03), and total hospitalization costs (aMD: $6,318, CI: $ 257-$12,380, P = 0.04). Both groups had similar total hospitalization charges (aMD: $$10,491, CI: -$12,618-$33,600, P-value = 0.37). CONCLUSIONS: Opioid dependence leads to higher rates of 30-day readmission and resource utilization among patients with firearm injuries. However, the in-hospital and 1-year mortality rates are lower among patients with opioid dependence secondary to lower injury acuity.

Cost-Effectiveness of Intranasal Naloxone Distribution to High-Risk Prescription Opioid Users.

OBJECTIVES: To determine the cost-effectiveness of pharmacy-based intranasal naloxone distribution to high-risk prescription opioid (RxO) users. METHODS: We developed a Markov model with an attached tree for pharmacy-based naloxone distribution to high-risk RxO users using 2 approaches: one-time and biannual follow-up distribution. The Markov structure had 6 health states: high-risk RxO use, low-risk RxO use, no RxO use, illicit opioid use, no illicit opioid use, and death. The tree modeled the probability of an overdose happening, the overdose being witnessed, naloxone being available, and the overdose resulting in death. High-risk RxO users were defined as individuals with prescription opioid doses greater than or equal to 90 morphine milligram equivalents (MME) per day. We used a monthly cycle length, lifetime horizon, and US healthcare perspective. Costs (2018) and quality-adjusted life-years (QALYs) were discounted 3% annually. Microsimulation was performed with 100 000 individual trials. Deterministic and probabilistic sensitivity analyses were conducted. RESULTS: One-time distribution of naloxone prevented 14 additional overdose deaths per 100 000 persons, with an incremental cost-effectiveness ratio (ICER) of $56 699 per QALY. Biannual follow-up distribution led to 107 additional lives being saved with an ICER of $84 799 per QALY compared with one-time distribution. Probabilistic sensitivity analyses showed that a biannual follow-up approach would be cost-effective 50% of the time at a willingness-to-pay (WTP) threshold of $100 000 per QALY. Naloxone effectiveness and proportion of overdoses witnessed were the 2 most influential parameters for biannual distribution. CONCLUSION: Both one-time and biannual follow-up naloxone distribution in community pharmacies would modestly reduce opioid overdose deaths and be cost-effective at a WTP of $100 000 per QALY.

Financing Buprenorphine Treatment in Primary Care: A Microsimulation Model.

PURPOSE: We sought to determine the financial impact to primary care practices of alternative strategies for offering buprenorphine-based treatment for opioid use disorder. METHODS: We interviewed 20 practice managers and identified 4 approaches to delivering buprenorphine-based treatment via primary care practice that differed in physician and nurse responsibilities. We used a microsimulation model to estimate how practice variations in patient type, payer, revenue, and cost across primary care practices nationwide would affect cost and revenue implications for each approach for the following types of practices: federally qualified health centers (FQHCs), non-FQHCs in urban high-poverty areas, non-FQHCs in rural high-poverty areas, and practices outside of high-poverty areas. RESULTS: The 4 approaches to buprenorphine-based treatment included physician-led visits with nurse-led logistical support; nurse-led visits with physician oversight; shared visits; and solo prescribing by physician alone. Net practice revenues would be expected to increase after introduction of any of the 4 approaches by $18,000 to $70,000 per full-time physician in the first year across practice type. Yet physician-led visits and shared medical appointments, both of which relied on nurse care managers, consistently produced the greatest net revenues ($29,000-$70,000 per physician in the first year). To ensure positive net revenues with any approach, providers would need to maintain at least 9 patients in treatment, with a no-show rate of <34%. CONCLUSIONS: Using a simulation model, we estimate that many types of primary care practices could financially sustain buprenorphine-based treatment if demand and no-show rate requirements are met, but a nurse care manager-based approach might be the most sustainable.

Correlates of Expressed Emotion Among Family Members of Individuals Who Sought Treatment for Opioid Use.

Expressed emotion has been robustly associated with negative mental health outcomes. Understanding correlates of expressed emotion by family members of individuals with opioid use disorder is important, as this group faces high levels of stress and can play an important role in their loved ones' treatment. Thus, immediate family members of individuals who sought treatment for opioid problems (N = 195) completed a web-based survey that included measures of expressed emotion, self-stigma, social support, and demographic characteristics. Multiple linear regression analyses were conducted to examine correlates of two types of expressed emotion-criticism and emotional overinvolvement. Results indicated that higher self-stigma and lower social support were significantly associated with higher emotional overinvolvement. Higher self-stigma and having experienced debt related to a family member's opioid use were associated with higher criticism. Thus, self-stigma and financial burden may exacerbate likelihood of expressed emotion, whereas social support may buffer against expressed emotion.

Cost-Effectiveness of Buprenorphine-Naloxone Versus Extended-Release Naltrexone to Prevent Opioid Relapse.

Background: Not enough evidence exists to compare buprenorphine-naloxone with extended-release naltrexone for treating opioid use disorder. Objective: To evaluate the cost-effectiveness of buprenorphine-naloxone versus extended-release naltrexone. Design: Cost-effectiveness analysis alongside a previously reported randomized clinical trial of 570 adults in 8 U.S. inpatient or residential treatment programs. Data Sources: Study instruments. Target Population: Adults with opioid use disorder. Time Horizon: 24-week intervention with an additional 12 weeks of observation. Perspective: Health care sector and societal. Interventions: Buprenorphine-naloxone and extended-release naltrexone. Outcome Measures: Incremental costs combined with incremental quality-adjusted life-years (QALYs) and incremental time abstinent from opioids. Results of Base-Case Analysis: Use of the health care sector perspective and a willingness-to-pay threshold of $100 000 per QALY showed buprenorphine-naloxone to be preferable to extended-release naltrexone in 97% of bootstrap replications at 24 weeks and in 85% at 36 weeks. Similar results were obtained with incremental time abstinent from opioids as an outcome and with use of the societal perspective. Results of Sensitivity Analysis: The base-case results were sensitive to the cost of the 2 treatments and the success of randomized treatment initiation. Limitation: Relatively short follow-up for a chronic condition, substantial missing data, no information on patient out-of-pocket and social service costs. Conclusion: Buprenorphine-naloxone is preferred to extended-release naltrexone as first-line treatment when both options are clinically appropriate and patients require detoxification before initiating extended-release naltrexone. Primary Funding Source: National Institute on Drug Abuse, National Institutes of Health.