The Effect of Medicaid on Management of Depression: Evidence From the Oregon Health Insurance Experiment.

Policy Points: We take advantage of Oregon's Medicaid lottery to gauge the causal effects of Medicaid coverage on mental health care, how effectively it addresses unmet needs, and how those effects differ for those with and without a history of depression. Medicaid coverage reduced the prevalence of undiagnosed depression by almost 50% and untreated depression by more than 60%. It increased use of medications and reduced the share of respondents reporting unmet mental health care needs by almost 40%. There are likely to be substantial mental health consequences of policy decisions about Medicaid coverage for vulnerable populations. CONTEXT: Expanding Medicaid to previously uninsured adults has been shown to increase detection and reduce the prevalence of depression, but the ways that Medicaid affects mental health care, how effectively it addresses unmet needs, and how those effects differ for those with and without a history of depression remain unclear. METHODS: We take advantage of Oregon's Medicaid lottery to gauge the causal effects of Medicaid coverage using a randomized-controlled design, drawing on both primary and administrative data sources. FINDINGS: Medicaid coverage reduced the prevalence of undiagnosed depression by almost 50% and untreated depression by more than 60%. It increased use of medications frequently prescribed to treat depression and related mental health conditions and reduced the share of respondents reporting unmet mental health care needs by almost 40%. The share of respondents screening positive for depression dropped by 9.2 percentage points overall, and by 13.1 for those with preexisting depression diagnoses, with greatest relief in symptoms seen primarily in feeling down or hopeless, feeling tired, and trouble sleeping-consistent with the increase observed not just in medications targeting depression but also in those targeting sleep. CONCLUSIONS: Medicaid coverage had significant effects on the diagnosis, treatment, and outcomes of a population with substantial unmet mental health needs. Coverage increased access to care, reduced the prevalence of untreated and undiagnosed depression, and substantially improved the symptoms of depression. There are likely to be substantial mental health consequences of policy decisions about Medicaid coverage for vulnerable populations.

The Effect of Medicaid on Dental Care of Poor Adults: Evidence from the Oregon Health Insurance Experiment.

OBJECTIVE: To evaluate the effect of Medicaid coverage on dental care outcomes, a major health concern for low-income populations. DATA SOURCES: Primary and secondary data on health care use and outcomes for participants in Oregon's 2008 Medicaid lottery. STUDY DESIGN: We used the lottery's random selection to gauge the causal effects of Medicaid on dental care needs, medication, and emergency department visits for dental care. DATA COLLECTION: Data were collected for lottery participants over 2 years, including mail surveys (N = 23,777) and in-person questionnaires (N = 12,229). Emergency department (ED) records were matched to lottery participants in Portland (N = 24,646). PRINCIPAL FINDINGS: Medicaid coverage significantly reduced the share of respondents who reported needing dental care (-9.8 percentage points, p < .001) or having unmet dental care needs (-13.5 percentage points, p < 0.001). Medicaid doubled the share visiting the ED for dental care (+2.6 percentage points, p = .003) and the use of anti-infective medications often prescribed for dental care, but it had no detectable effect on uncovered dental care or out-of-pocket spending. CONCLUSIONS: Expansion of Medicaid covering emergency dental care substantially reduced unmet need for dental care, increasing ED dental visits and medication use, while not changing patient use of uncovered dental services.

Medicaid increases emergency-department use: evidence from Oregon's Health Insurance Experiment.

In 2008, Oregon initiated a limited expansion of a Medicaid program for uninsured, low-income adults, drawing names from a waiting list by lottery. This lottery created a rare opportunity to study the effects of Medicaid coverage by using a randomized controlled design. By using the randomization provided by the lottery and emergency-department records from Portland-area hospitals, we studied the emergency department use of about 25,000 lottery participants over about 18 months after the lottery. We found that Medicaid coverage significantly increases overall emergency use by 0.41 visits per person, or 40% relative to an average of 1.02 visits per person in the control group. We found increases in emergency-department visits across a broad range of types of visits, conditions, and subgroups, including increases in visits for conditions that may be most readily treatable in primary care settings.

The Oregon experiment--effects of Medicaid on clinical outcomes.

BACKGROUND: Despite the imminent expansion of Medicaid coverage for low-income adults, the effects of expanding coverage are unclear. The 2008 Medicaid expansion in Oregon based on lottery drawings from a waiting list provided an opportunity to evaluate these effects. METHODS: Approximately 2 years after the lottery, we obtained data from 6387 adults who were randomly selected to be able to apply for Medicaid coverage and 5842 adults who were not selected. Measures included blood-pressure, cholesterol, and glycated hemoglobin levels; screening for depression; medication inventories; and self-reported diagnoses, health status, health care utilization, and out-of-pocket spending for such services. We used the random assignment in the lottery to calculate the effect of Medicaid coverage. RESULTS: We found no significant effect of Medicaid coverage on the prevalence or diagnosis of hypertension or high cholesterol levels or on the use of medication for these conditions. Medicaid coverage significantly increased the probability of a diagnosis of diabetes and the use of diabetes medication, but we observed no significant effect on average glycated hemoglobin levels or on the percentage of participants with levels of 6.5% or higher. Medicaid coverage decreased the probability of a positive screening for depression (-9.15 percentage points; 95% confidence interval, -16.70 to -1.60; P=0.02), increased the use of many preventive services, and nearly eliminated catastrophic out-of-pocket medical expenditures. CONCLUSIONS: This randomized, controlled study showed that Medicaid coverage generated no significant improvements in measured physical health outcomes in the first 2 years, but it did increase use of health care services, raise rates of diabetes detection and management, lower rates of depression, and reduce financial strain.

Intervening on risk factors for coronary heart disease: an application of the parametric g-formula.

Estimating the population risk of disease under hypothetical interventions--such as the population risk of coronary heart disease (CHD) were everyone to quit smoking and start exercising or to start exercising if diagnosed with diabetes--may not be possible using standard analytic techniques. The parametric g-formula, which appropriately adjusts for time-varying confounders affected by prior exposures, is especially well suited to estimating effects when the intervention involves multiple factors (joint interventions) or when the intervention involves decisions that depend on the value of evolving time-dependent factors (dynamic interventions). We describe the parametric g-formula, and use it to estimate the effect of various hypothetical lifestyle interventions on the risk of CHD using data from the Nurses' Health Study. Over the period 1982-2002, the 20-year risk of CHD in this cohort was 3.50%. Under a joint intervention of no smoking, increased exercise, improved diet, moderate alcohol consumption and reduced body mass index, the estimated risk was 1.89% (95% confidence interval: 1.46-2.41). We discuss whether the assumptions required for the validity of the parametric g-formula hold in the Nurses' Health Study data. This work represents the first large-scale application of the parametric g-formula in an epidemiologic cohort study.