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Development of an integrated digital health intervention to promote engagement in and adherence to medication for opioid use disorder.

ABSTRACT: BACKGROUND:Buprenorphine-naloxone is an evidence-based treatment for Opioid Use Disorder. However, despite its efficacy, nearly half of participants are unsuccessful in achieving stabilization (i.e., period of time following medication induction in which medication dose is adjusted to be effective in reducing cravings/withdrawal, minimize potential side effects, and eliminate illicit substance use). This paper presents the study design and protocol for a digital health intervention designed to promote engagement in and adherence to buprenorphine treatment, offered through an outpatient addiction treatment center, through motivational enhancement and distress tolerance skills training. Personalized feedback interventions represent a promising method to effectively motivate engagement in and adherence to buprenorphine treatment. These interventions are generally brief, individually tailored, and have the potential to be delivered via mobile platforms. Distress tolerance, a transdiagnostic vulnerability factor, has been implicated in the development and maintenance of substance use. Targeting distress tolerance may improve substance use treatment outcomes by promoting the ability to persist in goal-directed activity even when experiencing physical or emotional distress. METHODS:The study aims are to: (1) develop and refine an interactive computer- and text message-delivered personalized feedback intervention that incorporates distress tolerance skills training for persons who have elected to initiate outpatient buprenorphine treatment (iCOPE); (2) examine the feasibility, acceptability, and preliminary efficacy of iCOPE for increasing abstinence, adherence, and retention in treatment compared to a treatment as usual comparison condition; and, (3) examine potential mechanisms that may underlie the efficacy of iCOPE in improving outcomes, including motivation, distress tolerance, self-regulation, and negative affect. DISCUSSION:Results of this study will be used to determine whether to proceed with further testing through a large-scale trial. This work has the potential to improve treatment outcomes by reducing illicit opioid use, increasing adherence/retention, and preventing future overdose and other complications of illicit opioid use. Trial Registration NCT03842384.

SUBMITTER: Langdon KJ

PROVIDER: S-EPMC7191734 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Development of an integrated digital health intervention to promote engagement in and adherence to medication for opioid use disorder.

Langdon Kirsten J KJ Ramsey Susan S Scherzer Caroline C Carey Kate K Ranney Megan L ML Rich Josiah J

Addiction science & clinical practice 20200429 1

<h4>Background</h4>Buprenorphine-naloxone is an evidence-based treatment for Opioid Use Disorder. However, despite its efficacy, nearly half of participants are unsuccessful in achieving stabilization (i.e., period of time following medication induction in which medication dose is adjusted to be effective in reducing cravings/withdrawal, minimize potential side effects, and eliminate illicit substance use). This paper presents the study design and protocol for a digital health intervention desig ...[more]

PMID: 32349790

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Project description:BackgroundOpioid Use Disorder (OUD) and opioid overdose (OD) impose huge social and economic burdens on society and health care systems. Research suggests that Medication for Opioid Use Disorder (MOUD) is effective in the treatment of OUD. We use machine learning to investigate the association between patient's adherence to prescribed MOUD along with other risk factors in patients diagnosed with OUD and potential OD following the treatment.MethodsWe used longitudinal Medicaid claims for two selected US states to subset a total of 26,685 patients with OUD diagnosis and appropriate Medicaid coverage between 2015 and 2018. We considered patient age, sex, region level socio-economic data, past comorbidities, MOUD prescription type and other selected prescribed medications along with the Proportion of Days Covered (PDC) as a proxy for adherence to MOUD as predictive variables for our model, and overdose events as the dependent variable. We applied four different machine learning classifiers and compared their performance, focusing on the importance and effect of PDC as a variable. We also calculated results based on risk stratification, where our models separate high risk individuals from low risk, to assess usefulness in clinical decision-making.ResultsAmong the selected classifiers, the XGBoost classifier has the highest AUC (0.77) closely followed by the Logistic Regression (LR). The LR has the best stratification result: patients in the top 10% of risk scores account for 35.37% of overdose events over the next 12 month observation period. PDC score calculated over the treatment window is one of the most important features, with better PDC lowering risk of OD, as expected. In terms of risk stratification results, of the 35.37% of overdose events that the predictive model could detect within the top 10% of risk scores, 72.3% of these cases were non-adherent in terms of their medication (PDC <0.8). Targeting the top 10% outcome of the predictive model could decrease the total number of OD events by 10.4%.ConclusionsThe best performing models allow identification of, and focus on, those at high risk of opioid overdose. With MOUD being included for the first time as a factor of interest, and being identified as a significant factor, outreach activities related to MOUD can be targeted at those at highest risk.

Project description:BackgroundNon-prescribed opioid use is illegal in Vietnam. People who are apprehended for use of non-prescribed opioids may be arrested and incarcerated or sent to compulsory rehabilitation centers. For those on medication to treat opioid use disorder (MOUD), incarceration in either setting may disrupt treatment. This study estimates the effects of incarceration and compulsory rehabilitation on MOUD and HIV treatment outcomes in Vietnam.MethodsData are from a clinical trial testing the effects of MOUD on HIV viral suppression in six Vietnamese HIV clinics. Participants were assessed quarterly for 12 months. We assessed the associations between incarceration or compulsory rehabilitation during months 0-9 and study outcomes of receipt of MOUD, HIV clinic engagement, and antiretroviral therapy prescription during months 9-12, among those who were released by month 9 of the study, using logistic regression and zero-inflated negative binomial models.ResultsAt nine months, 25 of 258 participants (9.7%) were incarcerated or sent to compulsory rehabilitation at least once and completed the month 9 assessment. Of those, 19 (76.0%) did not receive MOUD in months 9 through 12. Both incarceration and compulsory rehabilitation were negatively associated with subsequent receipt of MOUD (aOR = 0.05, 95% CI = (0.01, 0.24); 0.14 (0.04, 0.50), respectively) and HIV clinic engagement (aOR = 0.13, 95% CI = (0.03, 0.71); 0.09 (0.02, 0.39), respectively). In the final three months of the study, participants who were incarcerated had 42.5 fewer days of MOUD (95% CI = 23.1, 61.9), and participants in compulsory rehabilitation had 46.1 fewer days of MOUD (95% CI = 33.8, 58.4) than those not incarcerated or in compulsory rehabilitation.ConclusionOur findings suggest that both incarceration and compulsory rehabilitation disrupt MOUD and HIV treatment among people with HIV and Opioid Use Disorder in Vietnam. Prioritization of evidence-based strategies to support engagement in care for people who use drugs could potentially expand HIV and Opioid Use Disorder treatment access and curb substance use more effectively than reliance on incarceration or compulsory rehabilitation.

Project description:Objective(s)To understand how contraception method use differed between women prescribed and not prescribed medications for opioid use disorder (MOUD) among commercially-insured and Medicaid-insured women.Study designIBM Watson Health MarketScan Commercial Claims and Encounters database and the Multi-State Medicaid database were used to calculate the (1) crude prevalence, and (2) adjusted odds ratios (adjusted for demographic characteristics) of using long-acting reversible or short-acting hormonal contraception methods or female sterilization compared with none of these methods (no method) in 2018 by MOUD status among women with OUD, aged 20 to 49 years, with continuous health insurance coverage through commercial insurance or Medicaid for ≥6 years. Claims data was used to define contraception use. Fisher exact test or χ2 test with a P-value ≤ 0.0001, based on the Holm-Bonferroni method, and 95% confidence intervals were used to determine statistically significant differences for prevalence estimates and adjusted odds ratios, respectively.ResultsOnly 41% of commercially-insured and Medicaid-insured women with OUD were prescribed MOUD. Medicaid-insured women with OUD prescribed MOUD had a significantly lower crude prevalence of using no method (71.1% vs 79.0%) and higher odds of using female sterilization (aOR, 1.33; 95% CI: 1.06-1.67 vs no method) than those not prescribed MOUD. Among commercially-insured women there were no differences in contraceptive use by MOUD status and 66% used no method.ConclusionsAmong women with ≥ 6 years of continuous insurance coverage, contraceptive use differed by MOUD status and insurance. Prescribing MOUD for women with OUD can be improved to ensure quality care.ImplicationsOnly two in five women with OUD had evidence of being prescribed MOUD, and majority did not use prescription contraception or female sterilization. Our findings support opportunities to improve prescribing for MOUD and integrate contraception and MOUD services to improve clinical care among women with OUD.

Project description:BackgroundThe United States has been grappling with the opioid epidemic, which has resulted in over 75,000 opioid-related deaths between April 2020 and 2021. Evidence-based pharmaceutical interventions (buprenorphine, methadone, and naltrexone) are available to reduce opioid-related overdoses and deaths. However, adoption of these medications for opioid use disorder has been stifled due to individual- and system-level barriers. External facilitation is an evidence-based implementation intervention that has been used to increase access to medication for opioid use disorder (MOUD), but the implementation costs of external facilitation have not been assessed. We sought to measure the facility-level direct costs of implementing an external facilitation intervention for MOUD to provide decision makers with estimates of the resources needed to implement this evidence-based program.MethodsWe performed a cost analysis of the pre-implementation and implementation phases, including an itemization of external facilitation team and local site labor costs. We used labor estimates from the Bureau of Labor and Statistics, and sensitivity analyses were performed using labor estimates from the Veterans Health Administration (VHA) Financial Management System general ledger data.ResultsThe average total costs for implementing an external facilitation intervention for MOUD per site was $18,847 (SD 6717) and ranged between $11,320 and $31,592. This translates to approximately $48 per patient with OUD. Sites with more encounters and participants with higher salaries in attendance had higher costs. This was driven mostly by the labor involved in planning and implementation activities. The average total cost of the pre-implementation and implementation activities were $1031 and $17,816 per site, respectively. In the sensitivity analysis, costs for VHA were higher than BLS estimates likely due to higher wages.ConclusionsImplementing external facilitation to increase MOUD prescribing may be affordable depending on the payer's budget constraints. Our study reported that there were variations in the time invested at each phase of implementation and the number and type of participants involved with implementing an external facilitation intervention. Participant composition played an important role in total implementation costs, and decision makers will need to identify the most efficient and optimal number of stakeholders to involve in their implementation plans.

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Development of an integrated digital health intervention to promote engagement in and adherence to medication for opioid use disorder.

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Development of an integrated digital health intervention to promote engagement in and adherence to medication for opioid use disorder.

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