That one-quarter of Medicare spending in the United States occurs in the last year of life is commonly interpreted as waste. But this interpretation presumes knowledge of who will die and when. Here ...we analyze how spending is distributed by predicted mortality, based on a machine-learning model of annual mortality risk built using Medicare claims. Death is highly unpredictable. Less than 5% of spending is accounted for by individuals with predicted mortality above 50%. The simple fact that we spend more on the sick-both on those who recover and those who die-accounts for 30 to 50% of the concentration of spending on the dead. Our results suggest that spending on the ex post dead does not necessarily mean that we spend on the ex ante "hopeless."
Beyond Causality ALSAN, MARCELLA; FINKELSTEIN, AMY N.
The Milbank quarterly,
December 2021, Letnik:
99, Številka:
4
Journal Article
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Policy Points
Policymakers at federal and state agencies, health systems, payers, and providers need rigorous evidence for strategies to improve health care delivery and population health. This is ...all the more urgent now, during the COVID‐19 pandemic and its aftermath, especially among low‐income communities and communities of color.
Randomized controlled trials (RCTs) are known for their ability to produce credible causal impact estimates, which is why they are used to evaluate the safety and efficacy of drugs and, increasingly, to evaluate health care delivery and policy. But RCTs provide other benefits, allowing policymakers and researchers to: 1) design studies to answer the question they want to answer, 2) test theory and mechanisms to help enrich understanding beyond the results of a single study, 3) examine potentially subtle, indirect effects of a program or policy, and 4) collaborate closely to generate policy‐relevant findings.
Illustrating each of these points with examples of recent RCTs in health care, we demonstrate how policymakers can utilize RCTs to solve pressing challenges.
We provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection. We ...then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance. Such variation, together with quantity data, allows us to estimate the demand for insurance. The same variation, together with cost data, allows us to estimate how insurers' costs vary as market participants endogenously respond to price. The slope of this estimated cost curve provides a direct test for both the existence and the nature of selection, and the combination of demand and cost curves can be used to estimate welfare.We illustrate our approach by applying it to data on employer-provided health insurance from one specific company. We detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small, in both absolute and relative terms.
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.
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.
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.
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.
A large literature in empirical public finance relies on “bunching” to identify a behavioral response to non-linear incentives and to translate this response into an economic object to be used ...counterfactually. We conduct this type of analysis in the context of prescription drug insurance for the elderly in Medicare Part D, where a kink in the individual's budget set generates substantial bunching in annual drug expenditure around the famous “donut hole.” We show that different alternative economic models can match the basic bunching pattern, but have very different quantitative implications for the counterfactual spending response to alternative insurance contracts. These findings illustrate the importance of modeling choices in mapping a compelling reduced form pattern into an economic object of interest.
There is widespread concern over the health risks and healthcare costs from potentially inappropriate high-cost imaging. As a result, the Centers for Medicare and Medicaid Services (CMS) will soon ...require high-cost imaging orders to be accompanied by Clinical Decision Support (CDS): software that provides appropriateness information at the time orders are placed via a best practice alert for targeted (i.e. likely inappropriate) imaging orders, although the impacts of CDS in this context are unclear. In this randomized trial of 3,511 healthcare providers at Aurora Health Care, we study the impacts of CDS on the ordering behavior of providers. We find that CDS reduced targeted imaging orders by a statistically significant 6%, however there was no statistically significant change in the total number of high-cost scans or of low-cost scans. The results suggest that the impending CMS mandate requiring healthcare systems to adopt CDS may modestly increase the appropriateness of high-cost imaging.
We analyze the extent to which individuals'choices over five employerprovided insurance coverage decisions and one 401 (k) investment decision exhibit systematic patterns, as would be implied by a ...general utility component of risk preferences. We provide evidence consistent with an important domain-general component that operates across all insurance choices. We find a considerably weaker relationship between one's insurance decisions and 401 (k) asset allocation, although this relationship appears larger for more if financially sophisticated" individuals. Estimates from a stylized coverage choice model suggest that up to 30 percent of our sample makes choices that may be consistent across all 6 domains.
We estimate how the marginal utility of consumption varies with health. To do so, we develop a simple model in which the impact of health on the marginal utility of consumption can be estimated from ...data on permanent income, health, and utility proxies. We estimate the model using the Health and Retirement Study's panel data on the elderly and near-elderly, and proxy for utility with measures of subjective well-being. Across a wide range of alternative specifications and assumptions, we find that the marginal utility of consumption declines as health deteriorates, and we are able to clearly reject the null of no state dependence. Our point estimates indicate that a one-standard-deviation increase in the number of chronic diseases is associated with a 10%—25% decline in the marginal utility of consumption relative to this marginal utility when the individual has no chronic diseases. We present some simple, illustrative calibration results that suggest that state dependence of the magnitude we estimate can have a substantial effect on important economic problems such as the optimal level of health insurance benefits and the optimal level of life-cycle savings.
Oregon's 2008 Medicaid expansion significantly increased the use of prescription medications in 2009-10.There are major barriers in access to prescription medications for the uninsured,1 particularly ...people with chronic conditions, substance abuse, or mental health issues.2,3 In 2012 uninsured adults were four times more likely than the insured to report not filling a prescription due to cost.1 There is some evidence of higher prescription drug use among Medicaid enrollees than among the uninsured,4 but isolating the causal effect of the program is difficult given that the uninsured differ from people with insurance in many ways that may affect care.We took advantage of a natural experiment in coverage expansion-the Oregon Medicaid lottery-to assess the impact of Medicaid on the use of medications. Using a randomized controlled design, we found that Medicaid coverage significantly increased the use of medications related to the management of several serious conditions (Exhibit 1) and substantially reduced the use of medications that were originally prescribed to someone else, a key proxy for medication safety.5,6With the future of Medicaid coverage uncertain, information on how the program affects medication use is a critical input for policy makers, patients, and health care providers alike.
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