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Objective: To describe a learning health care system research process designed to increase buprenorphine prescribing for the treatment of opioid use disorder (OUD) in rural primary care settings within U.S. Department of Veterans Affairs (VA) treatment facilities. Data Sources and Study Setting: Using national administrative data from the VA Corporate Data Warehouse, we identified six rural VA health care systems that had improved their rate of buprenorphine prescribing within primary care from 2015 to 2020 (positive deviants). We conducted qualitative interviews with leaders, clinicians, and staff involved in buprenorphine prescribing within primary care from these sites to inform the design of an implementation strategy. Study Design: Qualitative interviews to inform implementation strategy development. Data Collection/Extraction Methods: Interviews were audio‐recorded, transcribed verbatim, and coded by a primary coder and secondary reviewer. Analysis utilized a mixed inductive/deductive approach. To develop an implementation strategy, we matched clinical needs identified within interviews with resources and strategies participants had utilized to address these needs in their own sites. Principal Findings: Interview participants (n = 30) identified key clinical needs and strategies for implementing buprenorphine in rural, primary care settings. Common suggestions included the need for clinical mentorship or a consult service, buprenorphine training, and educational resources. Building upon interview findings and in partnership with a clinical team, we developed an implementation strategy composed of an engaging case‐based training, an audit and feedback process, and educational resources (e.g., Buprenorphine Frequently Asked Questions, Rural Care Model Infographic). Conclusions: We describe a learning health care system research process that leveraged national administrative data, health care provider interviews, and clinical partnership to develop an implementation strategy to encourage buprenorphine prescribing in rural primary care settings. [ABSTRACT FROM AUTHOR]

Background Despite the increased availability of evidence-based treatments for chronic pain, many patients in rural areas experience poor access to services. Patients receiving care through the VA may also need to navigate multiple systems of care. Objective To examine the effectiveness of a remotely delivered collaborative care intervention for improving pain interference among veterans with high-impact chronic pain living in rural areas. Design We will conduct a four-site pragmatic effectiveness trial of remotely delivered collaborative care for high-impact chronic pain. Participants (n  = 608) will be randomized to the Tele-Collaborative Outreach to Rural Patients (CORPs) intervention or to minimally enhanced usual care (MEUC). Participants randomized to CORPs will complete a biopsychosocial assessment and five follow-up sessions with a nurse care manager (NCM), who will collaborate with a consulting clinician to provide personalized recommendations and care management. CORP participants will also be invited to a virtual 6-session pain education group class. Participants randomized to MEUC will receive a one-time education session with the NCM to review available pain services. All participants will complete quarterly research assessments for one year. The primary study outcome is pain interference. This trial will oversample veterans of female birth sex and minoritized race or ethnicity to test heterogeneity of treatment effects across these patient characteristics. We will conduct an implementation process evaluation and incremental cost-effectiveness analysis. Discussion This pragmatic trial will test the real-world effectiveness of a remotely delivered collaborative care intervention for chronic pain. Study findings will inform future implementation efforts to support potential uptake of the intervention. [ABSTRACT FROM AUTHOR]

The article focuses on monitoring and reporting adverse events (AEs) in pragmatic clinical trials (PCTs) testing nonpharmacological pain management interventions. Topics discussed include the challenges of AE data collection and reporting in PCTs, the variability of monitoring methods across trials, and recommendations to improve AE reporting and consistency in pain-focused PCTs.

Background Best practices for clinical trials stipulate that statistical analysis plans (SAPs) need to be finalized before initiation of any analysis. However, there is limited guidance about when changes to SAPs are acceptable and how these changes should be incorporated into the research plan with appropriate documentation. Methods We conducted a survey of 12 pragmatic clinical trials (PCTs) in the Pain Management Collaboratory that evaluated nonpharmacological interventions for pain to assess the following SAP information: (1) location of statistical analysis details, (2) types of statistical analyses planned, (3) sponsor requirements, (4) templates used for development, (5) publication plan, (6) changes since trial launch, (7) process of documenting changes, and (8) process of updating the trial registry. Results All 12 PCTs provided details of their SAPs for the primary outcomes in the institutional review board–approved trial protocol; 8 included plans for secondary outcomes, and 6 included plans for tertiary/exploratory outcomes. Most PCTs made SAP changes after trial initiation, many as a result of COVID-19–related issues. Eleven of the PCTs were actively recruiting participants. Changes were made to sample size, study design, study arms, and analytical methods, all before the data lock/unblinding. In all cases, justification for the changes was documented in the trial protocol or SAP, signed off by the trial biostatistician and principal investigator, and reviewed/approved by an institutional review board, data and safety monitoring board, or sponsor. Conclusions We recommend that SAP changes can be acceptable up to the time of data lock/unblinding. To maintain full transparency and necessary rigor, clear documentation of such changes should include details, rationale, date(s) such changes were implemented, and evidence of approval by relevant oversight bodies. [ABSTRACT FROM AUTHOR]

Prescription opioids are used for managing pain in persons with cancer, however, there are socioeconomic and racial disparities in medication access. Cannabis is increasingly used for cancer symptom management and as an opioid alternative. Limited data are available about patterns of opioid and cannabis use among patients with cancer. We used survey data from 4 National Cancer Institute-designated cancer centers in 3 states (n = 1220) to assess perceptions, use of cannabis and opioids for pain, their substitution, and racial and ethnic differences in each outcome. Compared with White patients, Black patients were less likely to use opioids for pain (odds ratio [OR] = 0.66; P = .035) and more likely to report that cannabis was more effective than opioids (OR = 2.46; P = .03). Race effects were mitigated (P > .05) after controlling for socioeconomic factors. Further research is needed to understand cannabis and opioid use patterns and how overlapping social determinants of health create a disadvantage in cancer symptom management for Black patients., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Context: Cannabis use for symptom management among individuals with cancer is increasingly common., Objectives: We sought to describe the (1) prevalence and characteristics of cannabis use, (2) perceived therapeutic benefits of cannabis use, and (3) examine how use of cannabis was associated with self-reported pain, mood, and general health outcomes in a representative sample of patients treated at a National Cancer Institute (NCI)-designated Oregon Health and Science University Knight Cancer Institute., Methods: We conducted a population-based, cross-sectional survey developed in conjunction with 11 other NCI-designated cancer centers and distributed to eligible individuals. The survey inquired about characteristics of cannabis use, perception of therapeutic benefits, pain, mood, and general health. Responses were population weighted. We examined the association of cannabis use with self-reported pain, mood, and general health using logistic regression controlling for relevant sociodemographic and clinical characteristics., Results: A total of 523 individuals were included in our analytic sample. A total of 54% endorsed using cannabis at any time since their cancer diagnosis and 42% endorsed using cannabis during active treatment. The most commonly endorsed reasons for use included the following: sleep disturbance (54.7%), pain (47.1%), and mood (42.6%). We found that moderate pain was associated with more than a twofold (odds ratio = 2.4 [95% confidence interval = 1.3-4.6], p = 0.002) greater likelihood of self-reported cannabis use. Depressed mood and general health were not associated with cannabis use., Conclusions: In a state that had early adoption of medical and recreational cannabis legislation, a high number of cancer survivors report cannabis use. Moderate or more severe pain was associated with an increased likelihood to use cannabis, while mood and general health were not associated. Oncologists should be aware of these trends and assess use of cannabis when managing long-term symptoms of cancer and its treatments., (© The Author(s) 2024. Published by Mary Ann Liebert, Inc.)

Sleep-wake disturbances frequently present in Veterans with mild traumatic brain injury (mTBI). These TBI-related sleep impairments confer significant burden and commonly exacerbate other functional impairments. Therapies to improve sleep following mTBI are limited and studies in Veterans are even more scarce. In our previous pilot work, morning bright light therapy (MBLT) was found to be a feasible behavioral sleep intervention in Veterans with a history of mTBI; however, this was single-arm, open-label, and non-randomized, and therefore was not intended to establish efficacy. The present study, LION (light vs ion therapy) extends this preliminary work as a fully powered, sham-controlled, participant-masked randomized controlled trial (NCT03968874), implemented as fully remote within the VA (target n=120 complete). Randomization at 2:1 allocation ratio to: 1) active: MBLT (n=80), and 2) sham: deactivated negative ion generator (n=40); each with identical engagement parameters (60-min duration; within 2-hrs of waking; daily over 28-day duration). Participant masking via deception balanced expectancy assumptions across arms. Outcome measures were assessed following a 14-day baseline (pre-intervention), following 28-days of device engagement (post-intervention), and 28-days after the post-intervention assessment (follow-up). Primary outcomes were sleep measures, including continuous wrist-based actigraphy, self-report, and daily sleep dairy entries. Secondary/exploratory outcomes included cognition, mood, quality of life, circadian rhythm via dim light melatonin onset, and biofluid-based biomarkers. Participant drop out occurred in <10% of those enrolled, incomplete/missing data was present in <15% of key outcome variables, and overall fidelity adherence to the intervention was >85%, collectively establishing feasibility and acceptability for MBLT in Veterans with mTBI.