Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This ...analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial.
This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD).
Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42).
trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.
The μ-opioid receptor (MOR) is the primary target of methadone and buprenorphine. The primary neuronal transcript of the OPRM1 gene, MOR-1, contains a ~13 kb 3' untranslated region with five common ...haplotypes in European-Americans. We analyzed the effects of these haplotypes on the percentage of opioid positive urine tests in European-Americans (n=582) during a 24-week, randomized, open-label trial of methadone or buprenorphine/naloxone (Suboxone) for the treatment of opioid dependence. A single haplotype, tagged by rs10485058, was significantly associated with patient urinalysis data in the methadone treatment group. Methadone patients with the A/A genotype at rs10485058 were less likely to have opioid-positive urine drug screens than those in the combined A/G and G/G genotypes group (relative risk=0.76, 95% confidence intervals=0.73-0.80, P=0.0064). Genotype at rs10485058 also predicted self-reported relapse rates in an independent population of Australian patients of European descent (n=1215) who were receiving opioid substitution therapy (P=0.003). In silico analysis predicted that miR-95-3p would interact with the G, but not the A allele of rs10485058. Luciferase assays indicated miR-95-3p decreased reporter activity of constructs containing the G, but not the A allele of rs10485058, suggesting a potential mechanism for the observed pharmacogenetic effect. These findings suggest that selection of a medication for opioid dependence based on rs10485058 genotype might improve outcomes in this ethnic group.
The prevalence and associated overdose death rates from opioid use disorder (OUD) have dramatically increased in the last decade. Despite more available treatments than 20 years ago, treatment access ...and high discontinuation rates are challenges, as are personalized medication dosing and making timely treatment changes when treatments fail. In other fields such as depression, brief measures to address these tasks combined with an action plan-so-called measurement-based care (MBC)-have been associated with better outcomes. This workgroup aimed to determine whether brief measures can be identified for using MBC for optimizing dosing or informing treatment decisions in OUD.
The National Institute on Drug Abuse Center for the Clinical Trials Network (NIDA CCTN) in 2022 convened a small workgroup to develop consensus about clinically usable measures to improve the quality of treatment delivery with MBC methods for OUD. Two clinical tasks were addressed: (1) to identify the optimal dose of medications for OUD for each patient and (2) to estimate the effectiveness of a treatment for a particular patient once implemented, in a more granular fashion than the binary categories of early or sustained remission or no remission found in The Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5).
Five parameters were recommended to personalize medication dose adjustment: withdrawal symptoms, opioid use, magnitude (severity and duration) of the subjective effects when opioids are used, craving, and side effects. A brief rating of each OUD-specific parameter to adjust dosing and a global assessment or verbal question for side-effects was viewed as sufficient. Whether these ratings produce better outcomes (e.g., treatment engagement and retention) in practice deserves study. There was consensus that core signs and symptoms of OUD based on some of the 5 DSM-5 domains (e.g., craving, withdrawal) should be the basis for assessing treatment outcome. No existing brief measure was found to meet all the consensus recommendations. Next steps would be to select, adapt or develop de novo items/brief scales to inform clinical decision-making about dose and treatment effectiveness. Psychometric testing, assessment of acceptability and whether the use of such scales produces better symptom control, quality of life (QoL), daily function or better prognosis as compared to treatment as usual deserves investigation.
In the United States, methamphetamine-related overdoses have tripled from 2015 to 2020 and continue to rise. However, efficacious treatments such as contingency management (CM) are often unavailable ...in health systems.
We conducted a single-arm pilot study to evaluate the feasibility, engagement, and usability of a fully remotely delivered mobile health CM program offered to adult outpatients who used methamphetamine and were receiving health care within a large university health system.
Participants were referred by primary care or behavioral health clinicians between September 2021 and July 2022. Eligibility criteria screening was conducted by telephone and included self-reported methamphetamine use on ≥5 out of the past 30 days and a goal of reducing or abstaining from methamphetamine use. Eligible participants who agreed to take part then completed an initial welcome phase that included 2 videoconference calls to register for and learn about the CM program and 2 "practice" saliva-based substance tests prompted by a smartphone app. Participants who completed these welcome phase activities could then receive the remotely delivered CM intervention for 12 consecutive weeks. The intervention included approximately 24 randomly scheduled smartphone alerts requesting a video recording of themselves taking a saliva-based substance test to verify recent methamphetamine abstinence, 12 weekly calls with a CM guide, 35 self-paced cognitive behavioral therapy modules, and multiple surveys. Financial incentives were disbursed via reloadable debit cards. An intervention usability questionnaire was completed at the midpoint.
Overall, 37 patients completed telephone screenings, with 28 (76%) meeting the eligibility criteria and consenting to participate. Most participants who completed a baseline questionnaire (21/24, 88%) self-reported symptoms consistent with severe methamphetamine use disorder, and most had other co-occurring non-methamphetamine substance use disorders (22/28, 79%) and co-occurring mental health disorders (25/28, 89%) according to existing electronic health records. Overall, 54% (15/28) of participants successfully completed the welcome phase and were able to receive the CM intervention. Among these participants, engagement with substance testing, calls with CM guides, and cognitive behavioral therapy modules varied. Rates of verified methamphetamine abstinence in substance testing were generally low but varied considerably across participants. Participants reported positive opinions about the intervention's ease of use and satisfaction with the intervention.
Fully remote CM can be feasibly delivered within health care settings lacking existing CM programs. Although remote delivery may help reduce barriers to treatment access, many patients who use methamphetamine may struggle to engage with initial onboarding. High rates of co-occurring psychiatric conditions in the patient population may also contribute to uptake and engagement challenges. Future efforts could leverage greater human-to-human connection, more streamlined onboarding procedures, larger incentives, longer durations, and the incentivization of non-abstinence-based recovery goals to increase uptake and engagement with fully remote mobile health-based CM.
Strengths and Success Ryan, Saxon J.; Mosher, Gretchen A.
The Journal of technology studies,
10/2021, Volume:
47, Issue:
2
Journal Article
Peer reviewed
Strengths have been hypothesized to play a role in how a person approaches leadership and problem-solving. The Clifton StrengthsFinder (CSF) is a common way to identify and measure an individual’s ...strengths. This research examined the role of CSF strengths in the academic success of engineering and technology students within a large, midwestern, research-intensive, land-grant university. The purpose of this research was to identify how students use their CSF strengths and to identify if students perceive a connection between strengths and their success. This research utilized semi-structured interviews with students to gather detailed qualitative information on student perceptions of success and CSF strengths. The survey collected information on student perceptions of how useful strengths are in various scenarios and if there is a connection between student success and CSF strengths. Students perceived that there were a set of strengths that make some students more successful than others, but they were not able to identify what those strengths were. Primarily, students perceived CSF strengths were useful in group academic tasks but were not useful in individual academic tasks. Based on the responses from these interviews, students are not aware of all the scenarios in which they can use their strengths.
•The BAM-R is widely recommended for measurement-based care of substance use.•We aimed to shorten the BAM-R to increase administration feasibility.•No BAM-R items predicted 90-day SUD treatment ...retention or 12-month mortality.•We identified 5 BAM-R items with sensitivity to change and clinical utility.
The Brief Addiction Monitor-Revised (BAM-R) is a widely used, 17-item assessment of substance use, risk, and protective factors associated with recovery from substance use disorders. Despite wide adoption in the U.S. Department of Veterans Affairs (VA) and recommendations for use in measurement-based care (MBC), administration may not be feasible in many MBC settings due to time constraints. The purpose of this study was to derive a shortened version of the BAM-R for use in fast-paced healthcare settings.
BAM-R data from 32,002 Veterans were obtained through the VA's Corporate Data Warehouse. We used logistic regression models to identify items for removal based on prediction of two clinical outcomes (90-day substance use disorder (SUD) treatment retention and 12-month mortality) and item-level sensitivity to change during substance use treatment.
Although no intake BAM-R items predicted SUD treatment retention or mortality, effect sizes for item-level sensitivity to change during substance use treatment varied from small to large. Seven items were judged as relevant for MBC of SUD. Among all BAM-R items, Heavy Alcohol Use, Self-Help, Drug Use, Craving, and Mood items demonstrated the greatest magnitude of sensitivity to change.
Although additional research is recommended before a shortened BAM-R can be implemented in non-specialty MBC settings, we identified 5 BAM-R items with perceived clinical utility and scores that demonstrated evidence of sensitivity to change. Shortening the BAM-R increases feasibility of use, though more work is needed to optimize measurement for SUD MBC.
The liver plays an important role in the balance between hemostasis and thrombosis. Hepatic resection, particularly when performed in the presence of underlying parenchymal liver disease, can cause ...perturbation of this balance. This review summarizes the changes that occur in normal hemostasis and thrombosis before, during, and after nontransplant hepatic resection and, wherever possible, provides strategies for the perioperative management of bleeding and thrombosis.
Abstract Purpose To examine the prevalence of comorbid chronic pain among patients with opioid use disorder (OUD) and to compare other comorbidities (substance use disorder (SUD), mental health ...disorders, health/disease conditions) among patients in four categories: no chronic pain (No Pain), OUD prior to pain (OUD First), OUD and pain at the same time (Same Time), or pain condition prior to OUD (Pain First). Methods Using an electronic health record (EHR) database from 2006–2015, the study assessed 5307 adult patients with OUD in a large healthcare system; 35.6% were No Pain, 9.7% were OUD First, 14.9% were Same Time, and 39.8% were Pain First. Results Most OUD patients (64.4%) had chronic pain conditions, and among them 61.8% had chronic pain before their first OUD diagnosis. Other SUDs occurred more frequently among OUD First patients than among other groups in terms of alcohol (33.4% vs. 25.4% for No Pain, 20.7% for Same Time, and 20.3% for Pain First), cocaine (19.0%, vs. 13.8%, 9.4%, 7.1%), and alcohol or drug-induced disorders. OUD First patients also had the highest rates of HIV (4.7%) and hepatitis C virus (HCV; 28.2%) among the four groups. Pain First patients had the highest rates of mental disorder (81.7%), heart disease (72.0%), respiratory disease (68.4%), sleep disorder (41.8%), cancer (23.4%), and diabetes (19.3%). Conclusions The alarming high rates of chronic pain conditions occurring before OUD and the associated severe mental health and physical health conditions require better models of assessment and coordinated care plans to address these complex medical conditions.
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