Literature Collection

Introduction: There are limited studies to date on telemedicine treatment outcomes for opioid use disorder (OUD) among rural populations. Methods: This was a retrospective cohort study of rural adults enrolled in telemedicine OUD treatment. Study outcomes were percent retained in care and adherence to buprenorphine assessed by urine drug screens at 1, 3, and 6 months. Results: From April 1, 2020, through January 31, 2022, 1,816 rural patients across 14 states attended an initial telemedicine visit and received a clinical diagnosis of OUD. Participants had the following characteristics: mean age 37.7 years (±8.6); 52.4% female; and 66.7% Medicaid. At 1, 3, and 6 months, 74.8%, 61.5%, and 52.3% of participants were retained in care, and 69.0%, 56.0%, and 49.2% of participants were adherent, respectively. Conclusions: Telemedicine is an effective approach for treating OUD in rural populations, with retention comparable to in-person treatment.

BACKGROUND: Opioid substitution therapy (OST) is evidence-based treatment for opioid use disorders and, when taken as maintenance therapy, has proven health and social benefits. The benefits of OST are achieved through the retention of service users in the treatment programme. AIM: To identify factors that affected retention of service users who had OST interrupted in less than 6 months of being in an OST programme. SETTING: This qualitative study was conducted with 19 service users from eight Community-Oriented Substance Use Programme (COSUP) sites in the City of Tshwane, Gauteng, South Africa. METHODS: Participants were COSUP service users who had interrupted OST in less than 6 months since initiation and were purposefully selected from all COSUP sites. Demographic information was obtained and four focus group discussions covered challenges of OST retention. Discussions were recorded, transcribed and qualitatively analysed using Attride-Stirling's thematic networks framework. RESULTS: The 19 participants were all male, mostly black African, with a mean age of 26 years. Facilitators of retention in OST were individual readiness to change OST accessibility, positive family and peer support, treatment monitoring, understanding and managing expectations of service users, contribution in society and meaningful opportunities for engagement. Barriers were the cost of OST, bureaucracy within the programme, inability to communicate challenges timeously and effectively to treatment providers, boredom, cravings and poverty. CONCLUSION: Opioid substitution therapy programmes can ensure a holistic approach to prevent and treat harms related to illicit opioid use if they remain person-centred and are well-funded.Contribution: Understanding the barriers to, and facilitators of retention on OST can contribute to improved community-based service delivery.

AIMS: American deaths from opioid overdose now approach 50,000 annually. While evidence shows that medications for addiction treatment (MAT) save lives, retaining patients in MAT programs is challenging. The U.S. Agency for Healthcare Research and Quality, on behalf of the U.S. Department of Health and Human Services, commissioned a rapid evidence review on the effectiveness of interventions to promote a broader understanding of the published literature on MAT retention among adults with opioid use disorder (OUD). METHODS: We searched MEDLINE and the Cochrane Library from February 12, 2009, through June 16, 2019, for systematic reviews (SRs) and randomized controlled trials (RCTs). We summarized evidence for six retention intervention types: care settings/services/logistical support, contingency management, health information technology (IT), extended-release (XR) medication-based treatment, psychosocial support, and financial support. Our primary outcome was retention, defined as continued medication engagement for at least 3 months after MAT initiation. Secondary outcomes included mortality and harms. FINDINGS: Key findings from 2 SRs and 39 primary studies include: 1. Most studies of MAT for OUD do not focus on retention as the primary outcome, are small (e.g., one to two trials per intervention), and have design flaws. 2. Care setting interventions that initiated MAT in soon-to-be-released incarcerated patients improved retention following release. 3. Contingency management improved retention when combined with antagonist MAT, but not with agonist forms of MAT. Applicability, however, may be limited due to implementation challenges. 4. Preliminary trials suggest that retention in MAT supported with health IT approaches may be no worse than in-person approaches. 5. Early studies suggest no difference in retention with XR-buprenorphine in either injectable or implant formulations compared with daily buprenorphine. There were conflicting results with XR-naltrexone injection compared with daily buprenorphine. 6. The addition of psychosocial interventions did not improve retention; however, many studies included some form of counseling in the control groups, potentially obscuring evidence of effectiveness. Harms were infrequently reported across studies except in studies of XR formulations. Similarly, few studies reported whether participant characteristics influenced retention. CONCLUSIONS: While patients who receive longer-term treatment with MAT have improved outcomes, fewer than half of the identified studies measured treatment retention as a primary outcome. Limited evidence suggests criminal justice prerelease MAT initiation and the use of contingency management for patients on antagonist forms of MAT may aid retention. XR and daily buprenorphine formulations appear to be equivalent for treatment retention and comparisons of XR-naltrexone versus daily buprenorphine showed conflicting results. Integrating MAT treatment with medical and social services and the use of health IT did not change retention. Some studies were conducted outside of the United States, where policies and practices differ, focused on highly selected populations and/or conditions that are not fully representative of the spectrum of OUD, or were studied in situations that may not be easily implemented in real-world conditions. There is a critical need for studies that use standardized definitions of retention, include measures of harms as well as benefits, and reflect the full spectrum of real-life conditions.

This conceptual policy analysis examines the persistent gap between population health frameworks and their implementation in practice, using pediatric immunizations as a case example. Declining vaccine coverage and widening geographic disparities illustrate how broad definitions of population health may lack the operational structure needed to guide coordinated governance and delivery. Informed by a structured narrative review of peer-reviewed literature, policy reports, and national surveillance data, the Rainbow Model of Integrated Care is applied to analyze how clinical, professional, organizational, system, functional, and normative domains shape immunization performance across preventive care systems. The analysis identifies policy-relevant levers, including interoperable data infrastructure, alignment of exemption governance, integration of equity-focused payment incentives, community-partnered outreach, and transparent performance monitoring. For each domain, implementation considerations, authority structures, privacy safeguards, resourcing implications, and potential political and ethical trade-offs are examined. Illustrative measurable indicators are proposed to operationalize integration and support accountability. Although grounded primarily in the United States context, the challenges described and structural considerations discussed are relevant to other decentralized health systems. This analysis suggests that structured integration frameworks may assist policymakers in translating population health principles into coordinated and ethically grounded implementation strategies for immunization systems.

INTRODUCTION: Electronic health records-based disease surveillance can be used to efficiently estimate incidence of health conditions, but limitations between using claims and membership-based information need to be evaluated. To examine the impact of membership-based and utilisation-based (ie, healthcare encounter-based) definitions on population composition and diabetes incidence estimates in 2021. METHODS: We included between 1.4 and 1.6 million members 18 to <45 years of age in Kaiser Permanente Southern California without a diabetes diagnosis prior to 2021, applying membership criteria (continuous membership; membership in 1 and 2 years prior) and, separately, utilisation criteria (≥1 healthcare encounter in 2021 and ≥1 healthcare encounter in the 2 years prior; ≥1 healthcare encounter in 2021 only) to determine at-risk populations for diabetes. Incidence was determined by any diabetes-related diagnosis code in 2021. Population characteristics were calculated for and compared across membership and utilisation definitions. Unadjusted and age, sex and race and ethnicity-adjusted incidence rates per 1000 persons were calculated overall and by diabetes type. RESULTS: Utilisation-based cohorts at risk for diabetes were older (36.8%-37.5% aged 35 to <45 years) and had a higher proportion female (54.6%-56.8%) compared with membership-based cohorts (35.8%-35.9% aged 35 to <45 years; 51.6%-51.9% female). After adjusting for demographics, incidence rates applying membership criteria were lower compared with applying utilisation criteria across all age, sex, and race and ethnicity groups, but followed similar patterns. The highest adjusted incidence rates were observed for adults 35 to <45 years (range: 7.65-10.61 per 1000), males (range: 3.78-5.91 per 1000), and Hispanic individuals (range: 5.03-7.09 per 1000) within all cohorts. CONCLUSIONS: Requiring multiple encounters in utilisation-defined denominator populations resulted in estimates of diabetes incidences that approximated those identified using more restrictive membership definitions. These findings suggest that diabetes incidence estimates can be harmonised using utilisation definitions across diverse health systems with different levels of granularity in data capture.