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Policymakers often prefer decentralized regulation to central planning because decentralization allows them to better reflect the views of local residents, encourage experimentation, and evaluate various regulatory approaches. These advantages can be undermined, however, when the regulations of one government are affected by those of another. To examine the implications of such externalities, we consider the case of state certificate of need laws (CON), which require providers within the state to obtain licenses before adopting various types of health care technology. In particular, we analyze the cross-border effects of these laws on the number and location of magnetic resonance imaging providers. We find a large effect on the location of providers near borders between unregulated and regulated states. These results provide examples of some of the limitations of using states as policy laboratories as well as the ability of states to use state laws to reflect their local preferences. The results may also help explain conflicting studies on whether and why CON regulation may have failed to control costs and quantity.
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We develop a formal model to show how integration solves task allocation problems between organizations and test the predictions of the model, using a large and rich patient-level dataset on hospital discharges to nursing homes and home health care. As predicted by the theory, we find that vertical integration allows hospitals to shift patient recovery tasks downstream to lower cost delivery systems by discharging patients earlier and in poorer health, and integration leads to greater post-hospitalization service intensity. While integration facilitates a shift in the allocation of tasks, health outcomes are no worse when patients receive care from an integrated provider. The evidence suggests that by improving the allocation of tasks, integration solves coordination problems that arise in market exchange.
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We study spillover effects of the largest ever increase in Medicaid primary care reimbursement rates on behavioral health and healthcare outcomes; mental illness, substance use disorders, and tobacco product use. Much of the variation in Medicaid reimbursement rates we leverage is attributable to a large federally mandated increase between 2013 and 2014 through the Affordable Care Act. We apply differences-in-differences models to survey data specifically designed to measure behavioral health outcomes over the period 2010 to 2016. We find that higher primary care Medicaid reimbursement rates improve behavioral health outcomes among enrollees. We find no evidence that behavioral healthcare service use is altered. Previous economic research shows that the mandated boost increased office visits. Thus our results suggest that primary care providers are efficient in improving behavioral health outcomes among Medicaid enrollees. Given established shortages of behavioral health providers, these findings are important from a healthcare workforce and policy perspective.
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Certificate of Need Laws (CON), state laws requiring providers to obtain licenses before adopting healthcare technology, have been controversial. The effect of CON on technology supply has not been well established. In part this is because analyses have focused on state-level supply effects, which may reflect either the consequence of CON regulation on supply or the cause for its adoption or retention. Instead, we focus on the cross-border effects of CON. We compare the number and location of magnetic resonance imaging providers in counties that border states with a different regulatory regime to: 1) counties in the interior of states, 2) counties on state borders with the same regulatory regime on both sides, and 3) counties on borders with different regulatory regimes, but with a large river on the border. We find there are 6.4 fewer MRIs per million people in regulated counties that border counties in unregulated states than in unregulated counties that border regulated counties. This statistically significant finding that regulatory spillover can be sizable should be accounted for in future research on state-based health technology regulation. In addition, it suggests state experiences may not accurately predict the effects of CON if it were implemented nationally.
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