Employees and beneficiaries of public health insurance programs often have to switch involuntarily to another health plan, when a contract with their insurer is not renewed. I study the effects of such involuntary switches using plans' exit after a lost bid in Medicaid Managed Care, comparing enrollees forced to switch to enrollees in remaining plans. I find that switching plans disrupts medical care: switchers have fewer visits to primary-care physicians and more visits to emergency departments; their utilization of prescription drugs decreases, including patients using drugs for chronic conditions; children and non-whites also have more preventable hospital admissions. At the year after the exit, insurers' spending on switchers is 10% lower than the pre-exit baseline, comparing to beneficiaries in remaining plans, and Medicaid's total spending is lower by 4%. Exploring possible mechanisms, I find that loss of access to familiar primary care physicians, changes in the network of providers, and changes in drug formularies - all may play a role in disrupting care after a switch. Plans' effect on utilization may also partly explain the results.
Medicaid spends 40\% of its total spending on disabled beneficiaries, a sum that amounts to 6\% of the U.S. national health expenditure. Over the last two decades, states have shifted the provision of Medicaid to the disabled from their public fee-for-service system to private managed care plans. To study such transitions, we use an administrative database to identify county-level mandates that lead to a sharp increase in managed care enrollment. We exploit these mandates as an instrument for individuals' enrollment in managed care plans. We find that a transition to managed care eventually increases Medicaid's fiscal spending. Although spending mostly doesn't change at the first year after the transition, it increases by 0.5\% to 30\% of the baseline mean in the years after that, compared to the public program. Our results suggest that spending tends to increase more in states that have lower pre-mandate payment rates to providers.
Risk adjustment systems, that reallocate funds among competing health insurers, often use risk adjustors that are based on utilization documented in medical claims. The level of utilization that triggers an adjustor, i.e. the utilization threshold, is frequently chosen implicitly and uniformly. I empirically study utilization thresholds in the setting of the U.S. Marketplaces. Simulating alternative levels of thresholds for adjustors, I find thresholds that improve the prediction fit, by up to 9.6% in some disease groups. Using newly-defined measures for the incentives to game the system, I show that for some thresholds a tradeoff between fit and gaming-incentives does not exist. To guide a choice of multiple utilization thresholds, I employ a regression tree algorithm that considers both fit and gaming incentives.
Low socioeconomic status (SES) is often associated with excess morbidity and premature mortality. Such health disparities claim a steep economic cost: Possibly-preventable poor health outcomes harm societal welfare, impair the domestic product, and increase health care expenditures. We estimate the economic costs of health inequalities associated with socioeconomic status in Israel.
The monetary cost of health inequalities is estimated relative to a counterfactual with a more equal outcome, in which the submedian SES group achieves the average health outcome of the above-median group. We use three SES measures: the socioeceonmic ranking of localities, individuals’ income, and individuals’ education level. We examine costs related to the often-worse health outcomes in submedian SES groups, mainly: The welfare and product loss from excess mortality, the product loss from excess morbidity among workers and working-age adults, the costs of excess medical care provided, and the excess government expenditure on disability benefits. We use data from the Central Bureau of Statistics’ (CBS) surveys and socio-health profile of localities, from the National Insurance Institute, from the Ministry of Health, and from the Israel Tax Authority. All costs are adjusted to 2014 terms.
The annual welfare loss due to higher mortality in socioeconomically submedian localities is estimated at about 1.1–3.1 billion USD. Excess absenteeism and joblessness occasioned by illness among low-income and poorly educated workers are associated with 1.4 billion USD in lost product every year. Low SES is associated with overuse of inpatient care and underuse of community care, with a net annual cost of about 80 million USD a year. The government bears additional cost of 450 million USD a year, mainly due to extra outlays for disability benefits. We estimate the total cost of the estimated health disparities at a sum equal to 0.7–1.6% of Israel’s GDP.
Our estimates underline the substantial economic impact of SES-related health disparities in Israel. The descriptive evidence presented in this paper highlights possible benefits to the economy from policies that will improve health outcomes of low SES groups.
We estimate the effect of legislated tax changes on revenues in Israel from 1991 to 2012. We exploit numerical revenue forecasts, prepared alongside the proposed tax changes, to control for the information policy makers had. Estimating an error-correction model, we find that the average tax change ultimately yields about 70 percent of its static revenue effect. The dynamic offset is consistent with a large tax multiplier. The steady state estimated collection rate is 90 percent for a change in the corporate income tax, 65 percent for the personal income tax, and 58 percent for indirect taxes.