Receipt and duration of buprenorphine treatment during pregnancy and postpartum periods in a national privately-insured cohort.

Background: Research gaps exist on the use of medications for opioid use disorder (OUD) among birthing people. Methods: This retrospective cohort study included people who underwent childbirth deliveries during 2017-2020 and had a diagnosis of OUD identified from a national private insurance claims database. Buprenorphine prescriptions received during the year before childbirth and the year after childbirth were obtained from pharmacy claims. Logistic regressions were used to estimate associations between receipt of buprenorphine and individual and state-level factors. Results: Among a sample of 1,523 birthing people diagnosed with OUD, 540 (35.5 %) received buprenorphine during the pregnancy or postpartum periods. About half (51.5 %) of new recipients of buprenorphine received treatment for at least six months and, of those, one-third experienced a treatment interruption. The buprenorphine receipt rate differed significantly by race and ethnicity: 28.8 % of non-Hispanic Black birthing people with OUD and 22.8 % of Hispanic birthing people with OUD received buprenorphine treatment in contrast to 37.7 % of non-Hispanic white birthing people (aOR 0.53 [95 % CI 0.35-0.81] and 0.59 [95 % CI 0.37-0.96], respectively). The buprenorphine use rate increased over time from 29.7 % in 2017 to 42.9 % in 2020. Birthing people living in states with punitive policies related to substance use in pregnancy had the lowest buprenorphine use rate of 22.7 % as compared to 43.0 % in states with least restrictive policies. Conclusion: In this national sample of privately-insured individuals, by 2020, 42.9 % of birthing people with OUD received buprenorphine treatment. Treatment discontinuation and interruptions were common in the period surrounding childbirth.

Underinsurance Among Children With Special Health Care Needs in the United States.

Importance: A rise in pediatric underinsurance during the last decade among households with children with special health care needs (CSHCN) requires a better understanding of which households, by health care burden or income level, have been most impacted. Objective: To examine the prevalence of underinsurance across categories of child medical complexity and the variation in underinsurance within these categories across different levels of household income. Design, Setting, and Participants: This cross-sectional study used data from the National Survey of Children's Health and included 218 621 US children from 2016 to 2021. All children included did not reside in any type of institution (eg, correctional institutions, juvenile facilities, orphanages, long-term care facilities). Data were analyzed from January 2016 to December 2021. Exposures: The primary exposure is a categorization of child health care needs constructed using parent-reported child physical and behavioral health conditions, as well as the presence of functional limitations. Main Outcomes and Measures: The primary outcome variable is underinsurance, defined as absence of consistent or adequate health insurance. Models were adjusted for demographic and socioeconomic characteristics and stratified by household income. Multivariate logistic regression analysis of pooled cross-sectional survey data across multiple years (2016 to 2021) adjusted for complex survey design (weights). Results: In a total sample of 218 621 children who were not in institutions and were aged 0 to 17 years from 2016 to 2021 (105 478 [48.9%] female; 113 143 [51.1%] male; 13 571 [13.0%] non-Hispanic Black children; 149 706 [51.2%] non-Hispanic White children), underinsurance prevalence was higher among the children who had complex physical conditions (3316 [37.0%]), mental or behavioral conditions (5432 [38.1%]), or complex physical conditions and functional limitations (1407 [40.7%]) or mental or behavioral conditions with limitations (3442 [41.1%]), compared with healthy children (ie, children without special health care needs or limitations) (52 429 [31.2%]). The association between underinsurance and complexity of child health care needs varied by household income. In households earning 200% to 399% federal poverty level (FPL), underinsurance was associated with children having complex physical conditions and limitations (OR, 2.74; 95% CI, 2.13-3.51) and mental or behavioral conditions and limitations (OR, 2.21; 95% CI, 1.87-2.62), compared with healthy children. In households earning 400% or more above FPL, children's mental or behavioral conditions and limitations were associated with underinsurance (OR, 3.31; 95% CI, 2.82-3.88) compared with healthy children. Conclusions and relevance: In this cross-sectional study, the odds of being underinsured were not uniform among CSHCN. Both medical complexity and daily functional limitations led to increased odds of being underinsured. The concentration of underinsurance among middle-income households underpinned the challenge of health care financing for families of CSHCN whose incomes surpassed eligibility thresholds for dependent Medicaid insurance.

Issue at the Heart of Advancing the De-Adoption of Low-Value Care. Proceedings from an expert roundtable.

Identifying and paying for value has become a recurrent theme of health care reforms. Its corollary, reducing the prevalence of, and resources directed to, ineffective or marginally effective care, has received far less attention. In July 2016, the University of Pennsylvania's Leonard Davis Institute of Health Economics (LDI) convened a diverse set of national leaders and stakeholders representing industry, think-tanks, provider and patient groups, and academic experts to tackle how health systems, payers, and providers can spur the 'de-adoption' of medical practices and technologies no longer considered valuable. While the roundtable of experts unanimously supports the need for de-adoption and current efforts to curb the use of low-value practices or technologies, they identified four specific polarities at the heart of the debate about how best to build the momentum around deadoption, and move it forward. They are: 1) value (targeting ineffective, even harmful, care or expanding efforts to address care of limited value); 2) resource allocation (spending less or redirecting spending); 3) quality improvement (a subset of QI or a distinct process); 4) level of intervention (policy, payment, provider, or organization). In addition to these polarities, several key questions emerged that form practical next steps for advancing de-adoption activities. With an eye toward advancing de-adoption, this brief summarizes the polarities and questions that suggest priorities for a future research agenda and policy-relevant action steps.