IMPORTANCE Medications for opioid use disorder, including buprenorphine hydrochloride and methadone hydrochloride, are highly effective at improving outcomes for individuals with the disorder. For pregnant women, use of these medications also improves pregnancy outcomes, including the risk of preterm birth. Despite the known benefits of medications for opioid use disorder, many pregnant and nonpregnant women with the disorder are not receiving them. OBJECTIVE To determine whether pregnancy and insurance status are associated with a woman's ability to obtain an appointment with an opioid use disorder treatment clinician. DESIGN, SETTING, AND PARTICIPANTS In this cross-sectional study with random assignment of clinicians and simulated-patient callers (performed in "secret shopper" format), outpatient clinics that provide buprenorphine and methadone were randomly selected from publicly available treatment lists in 10 US states (selected for variability in opioid-related outcomes and policies) from March 7 to September 5, 2019. Pregnant vs nonpregnant woman and private vs public insurance assigned randomly to callers to create unique patient profiles. Simulated patients called the clinics posing as pregnant or nonpregnant women to obtain an initial appointment with a clinician. MAIN OUTCOMES AND MEASURES Appointment scheduling, wait time, and out-of-pocket costs. RESULTS A total of 10 871 unique patient profiles were assigned to 6324 clinicians. Among all women, 2312 of 3420 (67.6%) received an appointment with a clinician who prescribed buprenorphine, with lower rates among pregnant vs nonpregnant callers (1055 of 1718 [61.4%] vs 1257 of 1702 [73.9%]; relative risk, 0.83; 95% CI, 0.79-0.87). For clinicians who prescribed methadone, there was no difference in appointment access for pregnant vs nonpregnant callers (240 of 271 [88.6%] vs 237 of 265 [89.4%]; relative risk, 0.99; 95% CI, 0.93-1.05). Insurance was frequently not accepted, with 894 of 3420 buprenorphine-waivered prescribers (26.1%) and 174 of 536 opioid treatment programs (32.5%) granting appointments only when patients agreed to pay cash. Median wait times did not differ between pregnant and nonpregnant callers among buprenorphine prescribers (3 days [interquartile range, 1-7 days] vs 3 days [interquartile range, 1-7 days]; P = .43) but did differ among methadone prescribers (1 day [interquartile range, 1-4 days] vs 2 days [interquartile range, 1-6 days]; P = .049).

ObjectivesTo determine what thresholds are most often cited in the cost-effectiveness literature for low- and middle-income countries (LMICs), given various recommendations proposed and used in the literature to date, and thereafter to assess whether studies appropriately justified their use of threshold values.MethodsWe reviewed the contents of the Tufts Medical Center Global Health Cost-Effectiveness Analysis Registry, a repository of all English language cost-per-disability-adjusted life-year averted studies indexed in PubMed. Our review included all catalogued cost-per-disability-adjusted life-year studies published from 2000 through 2015. We restricted attention to studies that investigated interventions in LMICs.ResultsOur analysis identified 381 studies (80%) focused on LMICs. Of these studies, 250 (66%) cited the World Health Organization’s 1 to 3 times gross domestic product per capita threshold. A full-text review of 60 (24%) of these articles (randomly selected) revealed that none justified use of this threshold in the particular country or countries studied beyond citing (generic) guideline documents.ConclusionsCost-effectiveness analysis can help inform health care spending, but its value depends on incorporating assumptions that are valid for the applicable setting. Rather than rely on commonly used, generic economic thresholds, we encourage authors to use context-specific thresholds that reflect local preferences.

Cost-effectiveness (CE) thresholds are being discussed more frequently and there have been many new developments in this area; however, there is a lack of understanding about what thresholds mean and their implications. This paper provides an overview of the CE threshold literature. First, the meaning of a CE threshold and the key assumptions involved (perfect divisibility, marginal increments in budget, etc.) are highlighted using a hypothetical example, and the use of historic/heuristic estimates of the threshold is noted along with their limitations. Recent endeavours to estimate the empirical value of the thresholds, both from the supply side and the demand side, are then presented. The impact on CE thresholds of future directions for the field, such as thresholds across sectors and the incorporation of multiple criteria beyond quality-adjusted life-years as a measure of 'value', are highlighted. Finally, a number of common issues and misconceptions associated with CE thresholds are addressed.

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