Treatment access for opioid use disorder in pregnancy among rural and American Indian communities

Pregnancy-Associated Mortality During the Pandemic: Disparities by Rurality

INTRODUCTION

In the U.S., rural areas experience higher rates of adverse maternal health outcomes, but little data exists on rural/urban differences in pregnancy-associated deaths (PAD, all deaths during pregnancy and postpartum) or rural/urban differences in those deaths during the COVID-19 pandemic.

METHODS

Cross-sectional U.S. vital statistics mortality data from 2018 to 2021 was used to identify PAD (analyzed in 2024). PAD ratios (deaths per 100,000 live births) and 95% confidence intervals (CIs) were calculated by year, cause, and rurality (urban, suburban, rural). The percent change in PAD ratios between the prepandemic (2018 and 2019) and pandemic (2020 and 2021) time periods was calculated by rurality.

RESULTS

During the pandemic, rural-compared to suburban and urban-areas had the highest pregnancy-associated death ratios due to obstetric causes (53.9 deaths/100,000 live births, 95% CI: 48.8, 59.4), drug-related causes (19.0, 95% CI: 16.0, 22.4), suicide (4.4., 95% CI: 3.0, 6.2), and other causes (the majority of which are motor vehicle accidents, 16.4, 95% CI: 14.0, 19.6). Rural areas experienced increases in all causes of pregnancy-associated death from prepandemic (2018 and 2019) to pandemic (2020 and 2021) with increases of 48.1% in obstetric deaths, 115.9% in drug-related deaths, 17.8% in homicide, 25.7% in suicide, and 11.6% in other causes. Rural areas experienced the largest (compared to urban and suburban) increase in drug-related deaths, and only rural areas experienced an increase in suicide during the pandemic.

CONCLUSIONS

Rural areas experience a high burden of pregnancy-associated death, and this inequity was exacerbated during the COVID-19 pandemic.

Women and opioid use disorder treatment: A scoping review of experiences, use of patient-reported experience measures, and integration of person-centred care principles

BACKGROUND

Patient-reported experience measures (PREMs) are an important aspect of assessing and improving women's experiences of person-centred care during treatment for Opioid Use Disorder (OUD). This scoping review aimed to 1) examine the extent, type, and characteristics of evidence regarding women's OUD treatment experiences, and 2) describe the extent to which PREMs and person-centred care principles are incorporated within research methods.

METHODS

Following Joanna Briggs Institute guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), we conducted a scoping review to identify peer-reviewed articles on women's OUD treatment experiences. Data were extracted from 39 included studies and synthesised based on study design, method of assessment/analysis (including use of PREMs), key findings, and the integration of person-centred care principles.

RESULTS

Analysis of included studies revealed a predominance of qualitative research focused on women's experiences of pharmacological OUD treatment (methadone and/or buprenorphine) in Western countries. Women in these studies reported predominantly negative or mixed experiences of treatment. Few studies used validated PREMs and there was a lack of direct assessment or focus on recognised person-centred care principles. However, common categories of outcomes/findings identified in results across studies broadly aligned with person-centred care principles (e.g., fast access to reliable healthcare, effective treatment by trusted professionals), emphasising their applicability to women's experiences of treatment.

CONCLUSIONS

Although there has been an increased focus on women's experiences of treatment for OUD in recent years, results highlighted room for improvement regarding the systematic and comprehensive assessment of women's experiences across different contexts. Given the often negative or mixed experiences reported by women, an increased focus on assessing service provision through a person-centred care lens (including utilising PREMs) may allow for service improvements or adaptations targeted towards the needs and experiences of women.

Referral of patients from rural primary care clinics to telemedicine vendors for opioid use disorder treatment: A mixed-methods study

INTRODUCTION

Rural primary care clinics can expand their medication treatment for opioid use disorder (MOUD) capacity by coordinating care with external telemedicine (TM) vendors specializing in addiction medicine. This study used mixed methods to identify factors that influence patient referrals from rural primary care clinics to TM vendors for MOUD.

METHODS

Between July/August 2020 and January/February 2021, 582 patients with OUD were identified across six primary care sites; that included 68 referred to an external TM vendor to receive MOUD. Mixed effects logistic regression identified individual and site-level factors associated with being referred to the TM vendor. Clinic providers and staff participated in in-depth interviews and focus groups to discuss their considerations for referring patients to the TM vendor.

RESULTS

Patient referrals were positively associated with local household broadband coverage (OR = 2.55, p < 0.001) and negatively associated with local population density (OR = 0.01, p  =  0.003) and the number of buprenorphine prescribers in the county (OR = 0.85, p < 0.001). Clinic personnel expressed appreciation for psychiatric expertise and the flexibility to access MOUD brought by the TM vendor. Perceived concerns about TM referral included a lack of trust with external providers, uncertainty about TM service quality, workflow delays, and patients' technological and insurance challenges.

CONCLUSION

This study revealed several clinic-level factors that may potentially influence patient referral to TM vendor services for MOUD. To facilitate the referral process and utilization of TM vendors, efforts should be made to foster open communication and trust between clinic providers and TM vendors, streamline workflows, and improve Internet access for patients.

Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature

Introduction

Medications such as buprenorphine and methadone are effective for treating opioid use disorder (OUD), but many patients face barriers related to treatment and access. We analyzed two sources of data-social media and published literature-to categorize and quantify such barriers.

Methods

In this mixed methods study, we analyzed social media (Reddit) posts from three OUD-related forums (subreddits): r/suboxone, r/Methadone, and r/naltrexone. We applied natural language processing to identify posts relevant to treatment barriers, categorized them into insurance- and non-insurance-related, and manually subcategorized them into fine-grained topics. For comparison, we used substance use-, OUD- and barrier-related keywords to identify relevant articles from PubMed published between 2006 and 2022. We searched publications for language expressing fear of barriers, and hesitation or disinterest in medication treatment because of barriers, paying particular attention to the affected population groups described.

Results

On social media, the top three insurance-related barriers included having no insurance (22.5%), insurance not covering OUD treatment (24.7%), and general difficulties of using insurance for OUD treatment (38.2%); while the top two non-insurance-related barriers included stigma (47.6%), and financial difficulties (26.2%). For published literature, stigma was the most prominently reported barrier, occurring in 78.9% of the publications reviewed, followed by financial and/or logistical issues to receiving medication treatment (73.7%), gender-specific barriers (36.8%), and fear (31.5%).

Conclusion

The stigma associated with OUD and/or seeking treatment and insurance/cost are the two most common types of barriers reported in the two sources combined. Harm reduction efforts addressing barriers to recovery may benefit from leveraging multiple data sources.