Several states have expanded Medicaid eligibility for adults in the past decade, and the Affordable Care Act allows states to expand Medicaid dramatically in 2014. Yet the effect of such changes on adults' health remains unclear. We examined whether Medicaid expansions were associated with changes in mortality and other health-related measures.
Risk sharing arrangements between hospitals and payers together with penalties imposed by the Centers for Medicare and Medicaid (CMS) are driving an interest in decreasing early readmissions. There are a number of published risk models predicting 30 day readmissions for particular patient populations, however they often exhibit poor predictive performance and would be unsuitable for use in a clinical setting. In this work we describe and compare several predictive models, some of which have never been applied to this task and which outperform the regression methods that are typically applied in the healthcare literature. In addition, we apply methods from deep learning to the five conditions CMS is using to penalize hospitals, and offer a simple framework for determining which conditions are most cost effective to target.
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.
Decisions by states about whether to expand Medicaid under the Affordable Care Act (ACA) have implications for hospitals' financial health. We hypothesized that Medicaid expansion of eligibility for childless adults prevents hospital closures because increased Medicaid coverage for previously uninsured people reduces uncompensated care expenditures and strengthens hospitals' financial position. We tested this hypothesis using data for the period 2008-16 on hospital closures and financial performance. We found that the ACA’s Medicaid expansion was associated with improved hospital financial performance and substantially lower likelihoods of closure, especially in rural markets and counties with large numbers of uninsured adults before Medicaid expansion. Future congressional efforts to reform Medicaid policy should consider the strong relationship between Medicaid coverage levels and the financial viability of hospitals. Our results imply that reverting to pre-ACA eligibility levels would lead to particularly large increases in rural hospital closures. Such closures could lead to reduced access to care and a loss of highly skilled jobs, which could have detrimental impacts on local economies.
PURPOSE Under health care reform, states will have the opportunity to expand Medicaid to millions of uninsured US adults. Information regarding this population is vital to physicians as they prepare for more patients with coverage. Our objective was to describe demographic and health characteristics of potentially eligible Medicaid beneficiaries. METHODS We performed a cross-sectional study using data from the National Health and Nutrition Examination Survey (2007-2010) to identify and compare adult US citizens potentially eligible for Medicaid under provisions of the Patient Protection and Affordable Care Act (ACA) with current adult Medicaid beneficiaries. We compared demographic characteristics (age, sex, race/ethnicity, education) and health measures (self-reported health status; measured body mass index, hemoglobin A1c level, systolic and diastolic blood pressure, depression screen [9-item Patient Health Questionnaire], tobacco smoking, and alcohol use). RESULTS Analyses were based on an estimated 13.8 million current adult non-elderly Medicaid beneficiaries and 13.6 million nonelderly adults potentially eligible for Medicaid. Potentially eligible individuals are expected to be more likely male (49.2% potentially eligible vs 33.3% current beneficiaries; P <.001), to be more likely white and less likely black (58.8% white, 20.0% black vs 49.9% white, 25.2% black; P = .02), and to be statistically indistinguishable in terms of educational attainment. Overall, potentially eligible adults are expected to have better health status (34.8% "excellent" or "very good," 40.4% "good") than current beneficiaries (33.5% "excellent" or "very good," 31.6% "good"; P <.001). The proportions obese (34.5% vs 42.9%; P = .008) and with depression (15.5% vs 22.3%; P = .003) among potentially eligible individuals are significantly lower than those for current beneficiaries, while there are no significant differences in the expected prevalence of diabetes or hypertension. Current tobacco smoking (49.2% vs 38.0%; P = .002), and moderate and heavier alcohol use (21.6% vs 16.0% and 16.5% vs 9.8%; P <.001, respectively) are more common among the potentially eligible population than among current beneficiaries. CONCLUSIONS Under the ACA, physicians can anticipate a potentially eligible Medicaid population with equal if not better current health status and lower prevalence of obesity and depression than current Medicaid beneficiaries. Federal Medicaid expenditures for newly covered beneficiaries therefore may not be as high as anticipated in the short term. Given the higher prevalence of tobacco smoking and alcohol use, however, broad enrollment and engagement of this potentially eligible population is needed to address their higher prevalence of modifiable risk factors for future chronic disease.
Background From 2011 through 2014, the Federally Qualified Health Center Advanced Primary Care Practice Demonstration provided care management fees and technical assistance to a nationwide sample of 503 federally qualified health centers to help them achieve the highest (level 3) medical-home recognition by the National Committee for Quality Assurance, a designation that requires the implementation of processes to improve access, continuity, and coordination. Methods We examined the achievement of medical-home recognition and used Medicare claims and beneficiary surveys to measure utilization of services, quality of care, patients' experiences, and Medicare expenditures in demonstration sites versus comparison sites. Using difference-in-differences analyses, we compared changes in outcomes in the two groups of sites during a 3-year period. Results Level 3 medical-home recognition was awarded to 70% of demonstration sites and to 11% of comparison sites. Although the number of visits to federally qualified health centers decreased in the two groups, smaller reductions among demonstration sites than among comparison sites led to a relative increase of 83 visits per 1000 beneficiaries per year at demonstration sites (P<0.001). Similar trends explained the higher performance of demonstration sites with respect to annual eye examinations and nephropathy tests (P<0.001 for both comparisons); there were no significant differences with respect to three other process measures. Demonstration sites had larger increases than comparison sites in emergency department visits (30.3 more per 1000 beneficiaries per year, P<0.001), inpatient admissions (5.7 more per 1000 beneficiaries per year, P=0.02), and Medicare Part B expenditures ($37 more per beneficiary per year, P=0.02). Demonstration-site participation was not associated with relative improvements in most measures of patients' experiences. Conclusions Demonstration sites had higher rates of medical-home recognition and smaller decreases in the number of patients' visits to federally qualified health centers than did comparison sites, findings that may reflect better access to primary care relative to comparison sites. Demonstration sites had larger increases in emergency department visits, inpatient admissions, and Medicare Part B expenditures. (Funded by the Centers for Medicare and Medicaid Services.).
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 using a randomized controlled design. Using the randomization provided by the lottery and emergency-department records from Portland-area hospitals, we study the emergency-department use of about 25,000 lottery participants over approximately 18 months after the lottery. We find that Medicaid coverage significantly increases overall emergency use by 0.41 visits per person, or 40 percent relative to an average of 1.02 visits per person in the control group. We find 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.
A growing body of literature describes how the Affordable Care Act (ACA) has expanded health insurance coverage. What is less well known is how these coverage gains have affected populations that are at risk for high health spending. To investigate this issue, we used prescription transaction data for a panel of 6.7 million prescription drug users to compare changes in coverage, prescription fills, plan spending, and out-of-pocket spending before and after the implementation of the ACA’s coverage expansion. We found a 30 percent reduction in the proportion of this population that was uninsured in 2014 compared to 2013. Uninsured people who gained private coverage filled, on average, 28 percent more prescriptions and had 29 percent less out-of-pocket spending per prescription in 2014 compared to 2013. Those who gained Medicaid coverage had larger increases in fill rates (79 percent) and reductions in out-of-pocket spending per prescription (58 percent). People who gained coverage who had at least one of the chronic conditions detailed in our study saw larger decreases in out-of-pocket spending compared to those who did not have at least one condition. These results demonstrate that by reducing financial barriers to care, the ACA has increased treatment rates while reducing out-of-pocket spending, particularly for people with chronic conditions.
After the US Food and Drug Administration (FDA) approved computer-aided detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid Services (CMS) provided increased payment in 2002, CAD technology disseminated rapidly. Despite sparse evidence that CAD improves accuracy of mammographic interpretations and costs over $400 million a year, CAD is currently used for most screening mammograms in the United States.
Under the Physician Payments Sunshine Act, drug and device manufacturers and group purchasing organizations will report to the Centers for Medicare and Medicaid Services payments made to physicians and teaching hospitals, and the data will be posted on a public website.