Explore the vast range of titles available.

ABSTRACTObjectivesTo investigate whether health insurance generated improvements in cardiovascular risk factors (blood pressure and hemoglobin A1c (HbA1c) levels) for identifiable subpopulations, and using machine learning to identify characteristics of people predicted to benefit highly.DesignSecondary analysis of randomized controlled trial.SettingMedicaid insurance coverage in 2008 for adults on low incomes (defined as lower than the federal-defined poverty line) in Oregon who were uninsured. Participants12 134 participants from the Oregon Health Insurance Experiment with in-person data for health outcomes for both treatment and control groups.InterventionsHealth insurance (Medicaid) coverage.Main outcomes and measuresThe conditional local average treatment effects of Medicaid coverage on systolic blood pressure and HbA1c using a machine learning causal forest algorithm (with instrumental variables). Characteristics of individuals with positive predicted benefits of Medicaid coverage based on the algorithm were compared with the characteristics of others. The effect of Medicaid coverage was calculated on blood pressure and HbA1c among individuals with high predicted benefits.ResultsIn the in-person interview survey, mean systolic blood pressure was 119 (standard deviation 17) mmHg and mean HbA1c concentrations was 5.3% (standard deviation 0.6%). Our causal forest model showed heterogeneity in the effect of Medicaid coverage on systolic blood pressure. Individuals with lower baseline healthcare charges, for example, had higher predicted benefits from gaining Medicaid coverage. Medicaid coverage significantly lowered systolic blood pressure (−2.93 mmHg (95% confidence interval −5.82 to −0.32)) for people predicted to benefit highly. No evidence showed that Medicaid coverage lowered HbA1c for people with high predicted benefits.ConclusionsAlthough Medicaid coverage did not improve cardiovascular risk factors on average, improvements were noted in blood pressure among a subset of individuals with higher predicted benefits. These individuals were more likely to have no or low prior healthcare charges, for example. The findings suggest that Medicaid coverage leads to improved blood pressure for some people, but those benefits may be diluted by individuals who did not benefit. Although the effect size may be of limited clinical significance for any individual, at a broad population level that includes individuals who are both hypertensive and normotensive, the findings may be of public health importance for policy interventions.

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. 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. 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. Appointment scheduling, wait time, and out-of-pocket costs. 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). For patients agreeing to pay cash, the median out-of-pocket costs for initial appointments were $250 (interquartile range, $155-$300) at buprenorphine prescribers and $34 (interquartile range, $15-$120) at methadone prescribers. In this cross-sectional study with random assignment of clinicians and simulated-patient callers, many women, especially pregnant women, faced barriers to accessing treatment. Given the high out-of-pocket costs and lack of acceptance of insurance among many clinicians, access to affordable opioid use disorder treatment is a significant concern.

Efforts to reduce the ranks of the uninsured hinge on take-up of available programs and subsidies, but take-up of even free insurance is often less than complete. The evidence of the effectiveness of policies aiming to increase take-up is limited. We used a randomized controlled design to evaluate the impact of improved communication and behaviorally informed ?nudges? designed to increase Medicaid take-up among eligible populations. Fielding randomized interventions in two different study populations in Oregon, we found that even very low-cost interventions substantially increased enrollment. Effects were larger in a population whose members had already expressed interest in obtaining coverage, but the effects were more persistent in low-income populations whose members were already enrolled in other state assistance programs but had not expressed interest in health insurance. The effects were similar across different demographic groups. Our results suggest that improving the design of enrollment processes and using low-cost mass-outreach efforts have the potential to substantially increase insurance coverage of vulnerable populations.

In Lao People's Democratic Republic (PDR), community-based health insurance (CBHI) is the only voluntary insurance scheme; it typically targets self-employed people, most of whom reside in rural areas and are dependent on agricultural activities for subsistence. However, until very recently, the enrollment rate has fallen short and failed to reach a large percentage of the target group. To promote the CBHI scheme and increase demand, some supporting components should be considered for inclusion together with the health infrastructure component. This paper provides empirical evidence that the benefit package components of hypothetical CBHI schemes have causal effects on enrollment probabilities. Furthermore, we examine the distribution of willingness to pay (WTP) in response to policy changes based on a sample of 5,800 observations. A randomized conjoint experiment is conducted in rural villages in Savannakhet Province, Lao PDR, to elicit stated preference data. Each respondent ranks three options-two hypothetical alternatives and the CBHI status quo scheme. The levels of seven attributes-insurance coverage for medical consultations, hospitalizations, traffic accidents, pharmaceuticals and transportation; premiums; and prepaid discounts-are randomly and simultaneously assigned to the two alternatives. The findings suggest that the average WTP is at least as large as 10.9% of the per capita income of those who live in rural areas, which is higher than the WTP for health insurance averaged across low- and middle-income countries (LMICs) in the literature. The component of round-trip transportation insurance coverage has a significant effect on WTP distribution, particularly increasing the share of the highest bin. Therefore, the low CBHI scheme enrollment rate in Lao PDR does not necessarily imply low demand among the targeted population, as the finding from the WTP analysis illustrates potential demand for the CBHI scheme. Specifically, if transportation is addressed, enrollment is likely to significantly increase.

The Affordable Care Act (ACA) dramatically expanded the use of regulated marketplaces in health insurance, but consumers often fail to shop for plans during open enrollment periods. Typically these consumers are automatically reenrolled in their old plans, which potentially exposes them to unexpected increases in their insurance premiums and cost sharing. We conducted a randomized intervention to encourage enrollees in an ACA Marketplace to shop for plans. We tested the effect of letters and e-mails with personalized information about the savings on insurance premiums that they could realize from switching plans and the effect of generic communications that simply emphasized the possibility of saving. The personalized and generic messages both increased shopping on the Marketplace's website by 23 percent, but neither type of message had a significant effect on plan switching. These findings show that simple \"nudges\" with even generic information can promote shopping in health insurance marketplaces, but whether they can lead to switching remains an open question.

Background Despite the availability of evidence-based treatment, there is a substantial gap between the number of individuals in need of mental health care and those who receive treatment. The aim of this study was to assess changes in treatment coverage and barriers to mental health care among adults with depression and alcohol use disorder (AUD) before and after implementation of a district mental health care plan (MHCP) in Nepal. Methods The repeat population-based cross-sectional community survey was conducted with randomly selected adults in the baseline ( N  = 1983) and the follow-up ( N  = 1499) surveys, 3 years and 6 months apart. The Patient Health Questionnaire and Alcohol Use Disorder Identification Test were used to screen people with probable depression and AUD. Barriers to seeking mental health care were assessed by using a standardized tool, the Barriers to Care Evaluation Scale (BACE). Results The proportion of the participants receiving treatment for depression increased by 3.7 points (from 8.1% in the baseline to 11.8% in the follow-up) and for AUD by 5.2 points (from 5.1% in the baseline to 10.3% in the follow-up study), however, these changes were not statistically significant. There was no significant reduction in the overall BACE score in both unadjusted and adjusted models for both depression and AUD. The possible reasons for non-significant changes in treatment coverage and barriers to care could be that (i) the method of repeat population level surveys with a random sample was too distal to the intervention to be able to register a change and (ii) the study was underpowered to detect such changes. Conclusion The study found non-significant trends for improvements in treatment coverage and barriers to mental health care following implementation of the district mental health care plan. The key areas for improvement in the current strategy to improve treatment coverage and barriers to mental health care included change in the content of the existing community sensitization program, particularly for changing attitude and intention of people with mental illness for seeking care.

Starting in 2017, all state and federal health insurance exchanges will present quality data on health plans in addition to cost information. We analyzed variations in the current design of information on state exchanges to identify presentation approaches that encourage consumers to take quality as well as cost into account when selecting a health plan. Using an online sample of 1,025 adults, we randomly assigned participants to view the same comparative information on health plans, displayed in different ways. We found that consumers were much more likely to select a high-value plan when cost information was summarized instead of detailed, when quality stars were displayed adjacent to cost information, when consumers understood that quality stars signified the quality of medical care, and when high-value plans were highlighted with a check mark or blue ribbon. These approaches, which were equally effective for participants with higher and lower numeracy, can inform the development of future displays of plan information in the exchanges.

Latinos have the highest US childhood uninsurance rate of any race/ethnicity, but little is known about effective ways to eliminate this disparity. We evaluated the effects of parent mentors-Latino parents with children covered by Medicaid or the Children's Health Insurance Program-on insuring Latino children in a randomized, controlled, community-based trial of 155 uninsured children conducted in the period 2011-15. Parent mentors were trained to assist families in getting insurance coverage, accessing health care, and addressing social determinants of health. We found that parent mentors were more effective than traditional methods in insuring children (95 percent versus 69 percent), achieving faster coverage and greater parental satisfaction, reducing unmet health care needs, providing children with primary care providers, and improving the quality of well-child and subspecialty care. Children in the parent-mentor group had higher quality of overall and specialty care, lower out-of-pocket spending, and higher rates of coverage two years after the end of the intervention (100 percent versus 70 percent). Parent mentors are highly effective in insuring uninsured Latino children and eliminating disparities.

PurposeTo assess public attitudes towards fertility treatment coverage and whether attitudes are influenced by infertility labels.MethodsCross-sectional, web survey-based experiment using a national sample of 1226 United States adults. Participants read identical descriptions about infertility, with the exception of random assignment to infertility being labeled as a “condition,” “disease,” or “disability.” Participants then responded to questions measuring their beliefs and attitudes towards policies related to the diagnosis and treatment of infertility. We measured public support for infertility policies, public preference for infertility labels, and whether support differed by the randomly assigned label used. We also queried associations between demographic data and support for infertility policies.ResultsSupport was higher for insurance coverage of infertility treatments (p=.014) and fertility preservation (p=.017), and infertility public assistance programs (p=.036) when infertility was described as a “disease” or “disability” compared to “condition.” Participants who were younger, were planning or trying to conceive, had a family member or friend with infertility, and/or had a more liberal political outlook were more likely to support infertility policies. A majority of participants (78%) felt the term “condition” was the best label to describe infertility, followed by “disability” (12%). The least popular label was “disease” (10%). Those preferring “condition” were older (p<.001), more likely to be non-Hispanic White (p=.046), and less likely to have an infertility diagnosis (p<.001).ConclusionWhile less commonly identified as the best descriptors of infertility, labeling infertility as a “disease” or “disability” may increase support for policies that improve access to infertility care

BACKGROUND:Arkansas and Iowa received waivers from the federal government in 2014 to use federal Medicaid expansion funding to enroll beneficiaries in commercial insurance plans on the Marketplaces. One key hypothesis of these “private option” or “premium assistance” programs was that Medicaid beneficiaries would experience increased access to care. In this study, we compare new patient primary care appointment availability and wait-times for beneficiaries of traditional Medicaid and premium assistance Medicaid. METHODS:Trained field staff posing as patients, randomized to traditional Medicaid or Marketplace plans, called primary care practices seeking new patient appointments in Arkansas and Iowa in May to July 2014. All calls were made to offices that previously indicated being in-network for the plan. Offices were drawn randomly, within insurance type, based on the county proportion of the population with each insurance type. We calculated appointment rates and wait-times for new patients for traditional Medicaid and Marketplace plans. RESULTS:In Arkansas, Marketplace appointment rates were 27.2 percentage points higher than traditional Medicaid appointment rates (83.2% compared with 55.5%, P<0.001), while in Iowa, Marketplace appointment rates were 12.0 percentage points higher (86.3% compared with 74.3%, P<0.001). Conditional on receiving an appointment, median wait-times were roughly 1 week in each state without significant differences by insurance type. CONCLUSIONS:The experiences of Arkansas and Iowa suggest that enrolling Medicaid beneficiaries into Marketplace plans may lead to higher primary care appointment availability for new patients at participating providers. Further research is needed on whether premium assistance programs affect quality and continuity of care, and at what cost.