Cost‐benefit analysis, as a tool of general use in policy analysis or as a mandated analytical process in some rulemaking, provides protocols for assessing the relative efficiency of policy ...alternatives. However, inconsistent and apparently irrational decisions by consumers in some situations call into question the validity of inferring the values that consumers place on outcomes from their observed choices. It also opens the door for “nudges” that change the architecture of choice to promote more “rational” consumer choice. Differences between decision utility and experience utility and the willingness of consumers to pay for reductions in temptation provide conceptual bases for thinking about the efficiency of nudges. However, assessment of nudges and their role in behavioral public administration should also recognize that heterogeneous preferences can result in increases in utility for some and decreases for others. Therefore, nudges require systematic assessment like other policy instruments.
Abstract Background Alzheimer's disease (AD) is a progressive neurodegenerative disease that places substantial burdens on those who provide support for family members with declining cognitive and ...functional abilities. Many AD patients eventually require formal long-term care services because of the absence, exhaustion, or inability of family members to provide care. The costs of long-term care, and especially nursing home care, often deplete private financial resources, placing a substantial burden on state Medicaid programs. Current evidence suggests that pharmacological treatments and caregiver interventions can delay entry into nursing homes and potentially reduce Medicaid costs. However, these cost savings are not being realized because many patients with AD are either not diagnosed or diagnosed at late stages of the disease, and have no access to Medicare-funded caregiver support programs. Methods and Results A Monte Carlo cost-benefit analysis, based on estimates of parameters available in the medical literature, suggests that the early identification and treatment of AD have the potential to result in large, positive net social benefits as well as positive net savings for states and the federal government. Conclusions These findings indicate that the early diagnosis and treatment of AD are not only socially desirable in terms of increasing economic efficiency, but also fiscally attractive from both state and federal perspectives. These findings also suggest that failure to fund effective caregiver interventions may be fiscally unsound.
The adequacy of provider networks for plans sold through insurance Marketplaces established under the Affordable Care Act has received much scrutiny recently. Various studies have established that ...networks are generally narrow. To learn more about network adequacy and access to care, we investigated two questions. First, no matter the nominal size of a network, can patients gain access to primary care services from providers of their choice in a timely manner? Second, how does access compare to plans sold outside insurance Marketplaces? We conducted a "secret shopper" survey of 743 primary care providers from five of California's nineteen insurance Marketplace pricing regions in the summer of 2015. Our findings indicate that obtaining access to primary care providers was generally equally challenging both inside and outside insurance Marketplaces. In less than 30 percent of cases were consumers able to schedule an appointment with an initially selected physician provider. Information about provider networks was often inaccurate. Problems accessing services for patients with acute conditions were particularly troubling. Effectively addressing issues of network adequacy requires more accurate provider information.
Narrow Networks and the Affordable Care Act Haeder, Simon F; Weimer, David L; Mukamel, Dana B
JAMA : the journal of the American Medical Association,
2015-Aug-18, Letnik:
314, Številka:
7
Journal Article
The Patient Protection and Affordable Care Act (ACA) of 2010 has been one of the most controversial laws in decades. The ACA relies extensively on the cooperation of states for its implementation, ...offering opportunities for both local adaptation and political roadblocks. Health insurance exchanges are one of the most important components of the for achieving its goal of near-universal coverage. Despite significant financial support from the federal government, many governors and legislatures have taken actions that have blocked or delayed significant progress in developing their exchanges. However, many state commissioners of insurance have played constructive roles in moving states forward in exchange planning through their expertise, leadership, and pragmatism, sometimes in spite of strong political opposition to the from governors and legislatures.
Do insurance plans offered through the Marketplace implemented by the State of California under the Affordable Care Act restrict consumers' access to hospitals relative to plans offered on the ...commercial market? And are the hospitals included in Marketplace networks of lower quality compared to those included in the commercial plans? To answer these questions, we analyzed differences in hospital networks across similar plan types offered both in the Marketplace and commercially, by region and insurer. We found that the common belief that Marketplace plans have narrower networks than their commercial counterparts appears empirically valid. However, there does not appear to be a substantive difference in geographic access as measured by the percentage of people residing in at least one hospital market area. More surprisingly, depending on the measure of hospital quality employed, the Marketplace plans have networks with comparable or even higher average quality than the networks of their commercial counterparts.
Whose costs and benefits should count in cost‐benefit analysis (CBA)? This is an important practical question requiring answers for analysts because most government agencies offer only permissive or ...vague guidance. Drawing primarily on foundational CBA principles, we present a conceptual framework for specifying standing to answer three important boundary questions: Where? Who? What? First, a standing framework requires a definition of jurisdictional boundaries (the “where” question), whether national, subnational, or supranational. Second, a framework should be clear about which persons within the jurisdiction have standing (the “who” question). For example, should undocumented residents have standing? Third, the framework requires clarity on the standing of certain individual preferences (the “what” question), such as for harmfully addictive private or public goods that express “moral sentiments,” or when choices do not maximize the value of consumption. We seek to provide guidance for CBA practice within this framework.
Policy analysis often demands quantitative prediction—especially cost‐benefit analysis, which requires the comprehensive quantification and monetization of all valued impacts. Using parameter ...estimates and their precisions, analysts can apply Monte Carlo simulation to create distributions of net benefits that convey the levels of certainty about the fundamental question of interest: Will net benefits be positive if the policy is adopted? An inappropriate focus on hypothesis testing of parameters rather than prediction sometimes leads analysts to treat statistically insignificant coefficients as if they, and their standard errors, are zero. One alternative method is to use all estimates and their standard errors whether or not the estimates are statistically significant. Another alternative is to use all estimates but to shrink them toward zero and adjust their standard errors in an effort to guard against regression to the mean. Comparing the three methods (only use statistically significant estimates and their standard errors, use all estimates and their standard errors, use shrunk estimates and adjusted standard errors) in Monte Carlo simulation suggests that treating statistically insignificant coefficients as zero rarely minimizes the mean squared error of prediction. Using shrunk estimates appears to provide a more robust minimization of the mean squared error of prediction. The simulations presented here suggest that routinely shrinking estimates is a robust approach if one believes that there is a substantial probability that the true value of the parameter is near zero.
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