Association between treatment setting and outcomes among oregon medicaid patients with opioid use disorder: a retrospective cohort study

Risk of Relapse Following Discharge from Non-Hospital Residential Opioid Use Disorder Treatment: A Systematic Review of Studies Published from 2018 to 2022

Relapsing on opioids after residential treatment may involve fatal outcomes, considering the potential for reduced tolerance and the potency of fentanyl in the illicit opioid market. The present paper examines recent literature on the risk of relapse among adults with opioid use disorder after discharge from residential treatment. We searched for published studies from 2018 to 2022 through database searches, including CINAHL, PsychINFO, PubMed, and Scopus. Across the N=10 studies included in this review, returning to substance use after residential treatment was captured differently, including self-report, hair samples, and urine samples. Follow-up relapse data after discharging from treatment was also captured across different time periods of included studies ranging from one month to six months. Variability was also identified in the percentage of individuals who relapsed after treatment, ranging from 0% to 95%. Considering the potential for a fatal overdose in the current fentanyl era, it is imperative to provide resources during residential treatment that can reduce the risk of relapse after discharge.

Buprenorphine discontinuation and utilization of psychosocial services: a national study in the Veterans Health Administration

BACKGROUND

Longer duration of treatment with medication for opioid use disorder (MOUD) is associated with improved outcomes, but long-term retention remains a challenge. Research is needed to identify psychosocial interventions that support MOUD retention. To address this gap, we examined associations between a wide range of psychosocial services and buprenorphine treatment discontinuation across 18 months among a large cohort of Veterans initiating buprenorphine nationwide.

METHODS

We identified a cohort of patients with new buprenorphine initiation in 2017-2018 in Veterans Health Administration electronic health record data (N = 11,704). We examined prescription fills for up to 18 months after initiation. The primary outcome was first discontinuation of buprenorphine. We examined a variety of services, including psychotherapy in specialty substance use disorder (SUD) and mental health clinics, other healthcare services, and residential programs. To examine time-varying associations between psychosocial services and risk of discontinuation, we fit extended Cox regression models for each service separately and simultaneously.

RESULTS

Overall, 80.5% of patients discontinued buprenorphine at least once within 18 months. Risk of discontinuation was 18% (HR: 0.82, 95% CI: 0.77, 0.87) relatively lower following SUD psychotherapy and 26% (HR: 1.26, 95% CI: 1.15,1.39) higher following residential treatment.

CONCLUSIONS

Several services, including residential treatment, were associated with greater risk of subsequent buprenorphine discontinuation, whereas only SUD psychotherapy was consistently associated with lower risk of later discontinuation. These findings emphasize the need for future studies to increase understandings of beneficial and disruptive components of psychosocial services to improve treatment retention among patients receiving MOUD.

Test-Retest Reliability of a Timeline Follow-back Method to Assess Opioid Use and Treatment

BACKGROUND

Calendar-based timeline follow-back (TLFB) instruments have been used to assess alcohol use, smoking, and other behaviors. We assessed test-retest reliability of an adapted TLFB addressing opioid-related outcomes over 120 days among opioid overdose survivors using nonprescribed opioids.

METHODS

The Repeated-dose Behavioral intervention to reduce Opioid Overdose Trial utilized a TLFB that collected data over the preceding 120 days. A subset of participants was administered a retest TLFB 3-21 days after their TLFB assessment. The test and retest assessed days of opioid and medication for opioid use disorder (MOUD) use, hospitalization, residential substance use disorder (SUD) treatment, incarceration, and overdose during overlapping time periods. For outcomes reported by ≥15% of the sample, intraclass correlation coefficients (ICC) were calculated between test and retest. ICC > 0.9 was considered "very high" reliability. For outcomes reported by <15%, frequencies were described; statistical tests were not conducted.

RESULTS

Seventy-seven participants completed a retest. On the test/retest, most participants reported opioid (87%/83%) and MOUD (58%/60%) use. Median (IQR) number of days of opioid and MOUD use on the test/retest was 71 (25-117)/86 (23-108) and 4 (0-72)/5 (0-79) days. ICC between test and retest was >0.9 for both opioid and MOUD use. On test/retest, few participants reported hospitalization (8%/9%), residential SUD treatment (3%/3%), incarceration (5%/7%), or overdose (4%/3%).

DISCUSSION

The adapted TLFB had very high reliability for self-reported opioid and MOUD use over 120 days. For less frequent outcomes, including overdose, a higher frequency or larger sample size is needed to assess reliability.

Predictors of persistent opioid use in Australian primary care: A retrospective cohort study, 2018-2022

OBJECTIVE

To examine the predictors of persistent opioid use ('persistence') in people initiating opioids for non-cancer pain in Australian primary care.

DESIGN

A retrospective cohort study.

SETTING

Australian primary care.

SUBJECTS

People prescribed opioid analgesics between 2018-2022, identified through the Population Level Analysis and Reporting (POLAR) database.

METHODS

Persistence was defined as receiving opioid prescriptions for at least 90 days with a gap of less than 60 days between subsequent prescriptions. Multivariable logistic regression was used to examine the predictors of persistent opioid use.

RESULTS

The sample consisted of 343,023 people initiating opioids for non-cancer pain; of these, 16,527 (4.8%) developed persistent opioid use. Predictors of persistence included older age (≥75 vs 15-44 years: Adjusted odds ratio: 1.67, 95% CI: 1.58-1.78), concessional beneficiary status (1.78, 1.71-1.86), diagnosis of substance use disorder (1.44, 1.22-1.71) and chronic pain (2.05, 1.85-2.27), initiation of opioid therapy with buprenorphine (1.95, 1.73-2.20) and long-acting opioids (2.07, 1.90-2.25), provision of higher quantity of opioids prescribed at initiation (total OME of ≥ 750mg vs < 100mg: 7.75, 6.89-8.72), provision of repeat/refill opioid prescriptions at initiation (2.94, 2.77-3.12), and prescription of gabapentinoids (1.59, 1.50-1.68), benzodiazepines (1.43, 1.38-1.50) and z-drugs (e.g., zopiclone, zolpidem; 1.61, 1.46-1.78).

CONCLUSIONS

These findings add to the limited evidence of individual-level factors associated with persistent opioid use. Further research is needed to understand the clinical outcomes of persistent opioid use in people with these risk factors to support the safe and effective prescribing of opioids.

Trajectories of prescription opioid tapering in patients with chronic non-cancer pain: a retrospective cohort study, 2015-2020

OBJECTIVE

To identify common opioid tapering trajectories among patients commencing opioid taper from long-term opioid therapy for chronic non-cancer pain and to examine patient-level characteristics associated with these different trajectories.

DESIGN

A retrospective cohort study.

SETTING

Australian primary care.

SUBJECTS

Patients prescribed opioid analgesics between 2015 and 2020.

METHODS

Group-based trajectory modeling and multinomial logistic regression analysis were conducted to determine tapering trajectories and to examine demographic and clinical factors associated with the different trajectories.

RESULTS

A total of 3369 patients commenced a taper from long-term opioid therapy. Six distinct opioid tapering trajectories were identified: low dose / completed taper (12.9%), medium dose / faster taper (12.2%), medium dose / gradual taper (6.5%), low dose / noncompleted taper (21.3%), medium dose / noncompleted taper (30.4%), and high dose / noncompleted taper (16.7%). A completed tapering trajectory from a high opioid dose was not identified. Among patients prescribed medium opioid doses, those who completed their taper were more likely to have higher geographically derived socioeconomic status (relative risk ratio [RRR], 1.067; 95% confidence interval [CI], 1.001-1.137) and less likely to have sleep disorders (RRR, 0.661; 95% CI, 0.463-0.945) than were those who didn't complete their taper. Patients who didn't complete their taper were more likely to be prescribed strong opioids (eg, morphine, oxycodone), regardless of whether they were tapered from low (RRR, 1.444; 95% CI, 1.138-1.831) or high (RRR, 1.344; 95% CI, 1.027-1.760) doses.

CONCLUSIONS

Those prescribed strong opioids and high doses appear to be less likely to complete tapering. Further studies are needed to evaluate the clinical outcomes associated with the identified trajectories.

Adolescent Residential Addiction Treatment In The US: Uneven Access, Waitlists, And High Costs

Drug overdose deaths among adolescents are increasing in the United States. Residential treatment facilities are one treatment option for adolescents with substance use disorders, yet little is known about their accessibility or cost. Using the Substance Abuse and Mental Health Services Administration's treatment locator and search engine advertising data, we identified 160 residential addiction treatment facilities that treated adolescents with opioid use disorder as of December 2022. We called facilities while role-playing as the aunt or uncle of a sixteen-year-old child with a recent nonfatal overdose, to inquire about policies and costs. Eighty-seven facilities (54.4 percent) had a bed immediately available. Among sites with a waitlist, the mean wait time for a bed was 28.4 days. Of facilities providing cost information, the mean cost of treatment per day was $878. Daily costs among for-profit facilities were triple those of nonprofit facilities. Half of facilities required up-front payment by self-pay patients. The mean up-front cost was $28,731. We were unable to identify any facilities for adolescents in ten states or Washington, D.C. Access to adolescent residential addiction treatment centers in the United States is limited and costly.

Treatment setting among individuals with opioid use and criminal legal involvement, housing instability, or Medicaid insurance, 2015-2021

Background

Individuals with criminal legal involvement (CLI), housing instability, or Medicaid insurance may experience barriers accessing substance use treatment in certain settings. Previous research has found individuals in these groups are less likely to receive medications for opioid use disorder (MOUD), but the role treatment setting may play in low rates of MOUD is unclear.

Methods

We conducted a cross-sectional study using nationally representative survey data from 2015 to 2021. We estimated the proportion of individuals who had CLI, housing instability, or Medicaid insurance who received substance use treatment in a variety of settings. We used multivariable logistic regressions to estimate the associations between group and the receipt of MOUD across treatment settings.

Results

Individuals with CLI, housing instability, or Medicaid insurance were more likely to receive substance use treatment in hospitals, rehabilitation, and mental health facilities compared with individuals not in these groups. However, all groups accessed substance use treatment in doctors' offices at similar rates. Treatment at a doctor's office was associated with the highest likelihood of receiving MOUD (aOR 4.73 [95% CI: 2.2.15-10.43]). Across multiple treatment settings, Individuals with CLI or housing instability were less likely to receive MOUD.

Conclusions

Individuals with CLI, housing instability, or Medicaid insurance are more likely to access substance use treatment at locations associated with lower rates of MOUD use. MOUD access across treatment settings is needed to improve engagement and retention in treatment for patients experiencing structural disadvantage or who have low incomes.

Use of Telehealth for Opioid Use Disorder Treatment in Safety Net Primary Care Settings: A Mixed-Methods Study

Background: The COVID-19 pandemic resulted in a marked increase in telehealth for the provision of primary care-based opioid use disorder (OUD) treatment. This mixed methods study examines characteristics associated with having the majority of OUD-related visits via telehealth versus in-person, and changes in mode of delivery (in-person, telephone, video) over time. Methods: Logistic regression was performed using electronic health record data from patients with ≥1 visit with an OUD diagnosis to ≥1 of the two study clinics (Rural Health Clinic; urban Federally Qualified Health Center) and ≥1 OUD medication ordered from 3/8/2020-9/1/2021, with >50% of OUD visits via telehealth (vs. >50% in-person) as the dependent variable and patient characteristics as independent variables. Changes in visit type over time were also examined. Inductive coding was used to analyze data from interviews with clinical team members (n = 10) who provide OUD care to understand decision-making around visit type. Results: New patients (vs. returning; OR = 0.47;95%CI:0.27-0.83), those with ≥1 psychiatric diagnosis (vs. none; OR = 0.49,95%CI:0.29-0.82), and rural clinic patients (vs. urban; OR = 0.05; 95%CI:0.03-0.08) had lower odds of having the majority of visits via telehealth than in-person. Patterns of visit type varied over time by clinic, with the majority of telehealth visits delivered via telephone. Team members described flexibility for patients as a key telehealth benefit, but described in-person visits as more conducive to building rapport with new patients and those with increased psychological burden. Conclusion: Understanding how and why telehealth is used for OUD treatment is critical for ensuring access to care and informing OUD-related policy decisions.

Prevention of 90-day inpatient detoxification readmission for opioid use disorder by a community-based life-changing individualized medically assisted evidence-based treatment (C.L.I.M.B.) program: A quasi-experimental study

BACKGROUND

Evidence for community-based strategies to reduce inpatient detoxification readmission for opioid use disorder (OUD) is scant. A pilot program was designed to provide individualized structured treatment plans, including addressing prolonged withdrawal symptoms, family/systems assessment, and contingency management, to reduce readmission after the index inpatient detoxification.

METHODS

A non-randomized quasi-experimental design was used to compare the pilot facilities (treatment) and comparison facilities before and after the program started, i.e., a simple difference-in-differences (DID) strategy. Adults 18 years and older who met the Diagnostic and Statistical Manual of Mental Disorders version 5 criteria for OUD and had an inpatient detoxification admission at any OUD treatment facility in two study periods between 7/2016 and 3/2020 were included. Readmission for inpatient detoxification in 90-days after the index stay was the primary outcome, and partial hospitalization, intensive outpatient care, outpatient services, and medications for OUD were the secondary outcomes. Six statistical estimation methods were used to triangulate evidence and adjust for potential confounding factors between treatment and comparison groups.

RESULTS

A total of 2,320 unique patients in the pilot and comparison facilities with 2,443 index inpatient detoxification admissions in the pre- and post-periods were included. Compared with patients in comparison facilities, patients in the C.L.I.M.B. facilities had higher readmission in the pre-period (unadjusted readmission 17.0% vs. 10.6%), but similar rates in the post-period (12.3% vs. 10.6%) after the implementation of the pilot program. For 90-day readmission, all DID estimates were not statistically significant (adjusted estimates ranged from 6 to 9 percentage points difference favoring the C.L.I.M.B. program). There was no significant improvement in the secondary outcomes of utilizations in lower level of care and medications for OUD in C.L.I.M.B. facilities.

CONCLUSIONS

We found a reduction in readmission in the pilot facilities between the two periods, but the results were not statistically significant compared with the comparison facilities and the utilization of lower level of care services remained low. Even though providers in the pilot OUD treatment facilities actively worked with health plans to standardize care for patients with OUD, more strategies are needed to improve treatment engagement and retention after an inpatient detoxification.