Factors associated with obtaining employment among opioid use disorder patients enrolled in a therapeutic workplace intervention

2021 ◽  
pp. 108907
Author(s):  
August F. Holtyn ◽  
Forrest Toegel ◽  
Matthew D. Novak ◽  
Kenneth Silverman
Keyword(s):  
Opioid Use Disorder ◽  
Workplace Intervention ◽  
Opioid Use ◽  
Factors Associated ◽  
Therapeutic Workplace

Treatment Persistence Among Insured Patients Newly Starting Buprenorphine/Naloxone for Opioid Use Disorder

2018 ◽  
Vol 52 (5) ◽  
pp. 405-414 ◽  
Author(s):  
Natalia Shcherbakova ◽  
Gary Tereso ◽  
Jacqueline Spain ◽  
Robert J. Roose
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Care Delivery ◽  
Opioid Use Disorder ◽  
Prescription Opioid ◽  
Care Providers ◽  
Opioid Use ◽  
Treatment Persistence ◽  
Factors Associated ◽  
Insured Patients

Background: Persistence with medication-assisted therapy among patients with opioid use disorder has been associated with reduced likelihood of illicit opioid use. Objective: We aimed to describe treatment persistence and identify factors associated with 1-year persistence among insured patients newly initiating buprenorphine-containing pharmacotherapy. Methods: The retrospective observational cohort included employer-sponsored and managed Medicaid patients newly started on buprenorphine-containing therapy between June 30, 2010, and January 1, 2015. Persistence was measured as both a continuous and dichotomous variable (proportion of patients persistent for 1 year). Multivariable logistic regression analysis was used to identify factors associated with 1-year persistence. Results: A total of 302 patients met inclusion criteria. The median [range] number of treatment episodes was 1 [1-4]. Mean number of days on therapy during the first episode was 206 (SD = 152) days, with 40.4% (n = 122) of patients persisting for 1 year. Presence of concomitant fills of prescription opioid analgesics (odds ratio [OR] = 0.25; 95% CI = 0.12-0.51), being in care of an addiction specialist (OR = 0.40; 95% CI = 0.21-0.76), and Medicaid insurance coverage (OR = 0.33; 95% CI = 0.13-0.84) were significantly and negatively associated with 1-year persistence. There was also a strong inverse relationship between persistence and inpatient hospitalization (OR = 0.30; 95% CI = 0.12-0.76). Conclusions: Several health care delivery and use variables were significantly associated with nonpersistence. Concomitant use of prescription opioids is the most easily modifiable risk factor that health care providers and policy makers may act on to improve treatment continuation.

scholarly journals Factors Associated with Prescription Opioid Analgesic Use in the US Population, 2011–2014

Pain Medicine ◽  
2018 ◽  
Vol 20 (7) ◽  
pp. 1338-1346 ◽  
Author(s):  
Steven M Frenk ◽  
Susan L Lukacs ◽  
Qiuping Gu
Keyword(s):  
Opioid Analgesic ◽  
Opioid Analgesics ◽  
Opioid Use Disorder ◽  
Prescription Opioid ◽  
Opioid Use ◽  
Factors Associated ◽  
The Past ◽  
The Us ◽  
Opioid Users ◽  
Analgesic Use

Abstract Objective This study examined factors associated with prescription opioid analgesic use in the US population using data from a nationally representative sample. It focused on factors previously shown to be associated with opioid use disorder or overdose. Variations in the use of different strength opioid analgesics by demographic subgroup were also examined. Methods Data came from respondents aged 16 years and older who participated in the National Health and Nutrition Examination Survey (2011–2014). Respondents were classified as opioid users if they reported using one or more prescription opioid analgesics in the past 30 days. Results Opioid users reported poorer self-perceived health than those not currently using opioids. Compared with those not using opioids, opioid users were more likely to rate their health as being “fair” or “poor” (40.4% [95% confidence interval {CI} = 34.9%–46.2%] compared with 15.6% [95% CI = 14.3%–17.1%]), experienced more days of pain during the past 30 days (mean = 14.3 [95% CI = 12.9–15.8] days compared with 2.3 [95% CI = 2.0–2.7] days), and had depression (22.5% [95% CI = 17.3%–28.7%] compared with 7.1% [95% CI = 6.2%–8.0%]). Among those who reported using opioids during the past 30 days, 18.8% (95% CI = 14.4%–24.1%) reported using benzodiazepine medication during the same period and 5.2% (95% CI = 3.5%–7.7%) reported using an illicit drug during the past six months. When opioid strength was examined, a smaller percentage of adults aged 60 years and older used stronger-than-morphine opioids compared with adults aged 20–39 and 40–59 years. Conclusions Higher percentages of current opioid users than nonusers reported having many of the factors associated with opioid use disorder and overdose.

scholarly journals Sociodemographic and Clinical Characteristics Associated with Improvements in Quality of Life for Participants with Opioid Use Disorder

Healthcare ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 167
Author(s):  
Assaf Gottlieb ◽  
Christine Bakos-Block ◽  
James R. Langabeer ◽  
Tiffany Champagne-Langabeer
Keyword(s):  
Quality Of Life ◽  
Clinical Characteristics ◽  
Opioid Use Disorder ◽  
Opioid Use ◽  
Professional Counseling ◽  
Factors Associated ◽  
Multiple Dimensions ◽  
Average Improvement ◽  
Engagement System

Background: The Houston Emergency Opioid Engagement System was established to create an access pathway into long-term recovery for individuals with opioid use disorder. The program determines effectiveness across multiple dimensions, one of which is by measuring the participant’s reported quality of life (QoL) at the beginning of the program and at successive intervals. Methods: A visual analog scale was used to measure the change in QoL among participants after joining the program. We then identified sociodemographic and clinical characteristics associated with changes in QoL. Results: 71% of the participants (n = 494) experienced an increase in their QoL scores, with an average improvement of 15.8 ± 29 points out of a hundred. We identified 10 factors associated with a significant change in QoL. Participants who relapsed during treatment experienced minor increases in QoL, and participants who attended professional counseling experienced the largest increases in QoL compared with those who did not. Conclusions: Insight into significant factors associated with increases in QoL may inform programs on areas of focus. The inclusion of counseling and other services that address factors such as psychological distress were found to increase participants’ QoL and success in recovery.

scholarly journals Factors associated with opioid cessation: a machine learning approach

2019 ◽  
Author(s):  
Jiayi W. Cox ◽  
Richard M. Sherva ◽  
Kathryn L. Lunetta ◽  
Richard Saitz ◽  
Mark Kon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Drug Use ◽  
Psychiatric Disorders ◽  
Structured Interview ◽  
Opioid Use Disorder ◽  
Support Vector ◽  
Opioid Use ◽  
Factors Associated ◽  
Machine Learning Approach

AbstractBackground and AimsPeople with opioid use disorder (OUD) can stop using opioids on their own, with help from groups and with treatment, but there is limited research on the factors that influence opioid cessation.MethodsWe employed multiple machine learning prediction algorithms (LASSO, random forest, deep neural network, and support vector machine) to assess factors associated with ceasing opioid use in a sample comprised of African Americans (AAs) and European Americans (EAs) who met DSM-5 criteria for mild to severe OUD. Values for several thousand demographic, alcohol and other drug use, general health, and behavioral variables, as well as diagnoses for other psychiatric disorders, were obtained for each participant from a detailed semi-structured interview.ResultsSupport vector machine models performed marginally better on average than those derived using other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression analyses that considered the 83 most highly ranked variables across all methods and models identified less recent cocaine use (p<5×10−8), a shorter duration of opioid use (p<5×10−6), and older age (p<5×10−9) as the strongest independent predictors of opioid cessation. Factors related to drug use comprised about half of the significant independent predictors, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics.ConclusionsThese proof-of-concept findings provide information that can help develop strategies for improving OUD management and the methods we applied provide a framework for personalizing OUD treatment.

scholarly journals Factors Associated with Opioid Use Disorder Diagnosis and Treatment Progress

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Reanne Christina Mathai
Keyword(s):  
Social Relationships ◽  
Small Sample Size ◽  
Opioid Use Disorder ◽  
Small Sample ◽  
Treatment Center ◽  
Opioid Use ◽  
Treatment Progress ◽  
Childhood Experiences ◽  
Factors Associated ◽  
Pain Symptoms

Previous research has shown that various environmental aspects, such as a history of abuse, trauma, and pain can influence the incidence of opioid use disorder (OUD). The aims of this study were to determine risk factors associated specifically with opioid use disorder, and to identify factors that may predict treatment progress for opioid use disorder patients. Three-hundred six patients from an abstinence-based residential treatment center participated in this study. Participants completed a comprehensive battery, which included measures assessing quality of life, craving, abstinence self-efficacy, adverse childhood experiences, trauma exposure, and physical pain symptoms at treatment intake and again after 28 days of treatment. Independent t-test results showed significant differences between patients with and without opioid use disorders in social relationships, confidence abstaining from alcohol and drugs, pain intensity, and drug craving. Multiple regression analyses demonstrated that presence of an opioid use disorder predicted alcohol abstinence, social relationships, and baseline environment. Results revealed shifting attitudes towards substance use and social relationships during the opioid group’s time in treatment. Cravings and urges were identified as important focuses for future treatment of opioid use disorder. Hyperalgesia was seen as an effect of extended opioid use and its impact decreased through drug abstinence. Limitations included a small sample size, a large proportion of wealthy individuals, and age differences between the two groups. 

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