Innovation is a primary source of economic growth, and is accordingly the target of substantial academic and government attention. Grants are a key tool in the government’s arsenal of tools to promote innovation, but legal academic studies of that arsenal have given them short shrift. While patents, prizes, and regulator-enforced exclusivity are each the subject of a substantial literature, grants are typically addressed briefly, if at all. According to the conventional story, grants may be the only feasible tool to drive basic research, as opposed to applied research, but they are a blunt tool for that task.
Three critiques of grants underlie this narrative: grants are allocated by government bureaucrats who lack much of the relevant information for optimal decision-making; grants are purely ex ante funding mechanisms and therefore lack accountability; and grants misallocate risk by saddling the government all the downside risk and giving the innovator all the upside. These critiques are largely wrong. Focusing on grants awarded by the National Institutes of Health, the largest public funder of biomedical research, this Article delves deeply into how grants actually work. It shows that grants are awarded not by uninformed bureaucrats, but by panels of knowledgeable peer scientists with the benefit of extensive disclosures from applicants. It finds that grants provide accountability through repeated interactions over time. And it argues that the upside of grant-investments to the government is much greater than the lack of direct profits would suggest.
Grants also have two marked comparative strengths as innovation levers: they can support innovation where social value exceeds appropriable market value, and they can directly support innovation enablers — the people, institutions, processes, and infrastructure that shape and generate innovation. Where markets undervalue some socially important innovations, like cures for diseases of the poor, grants can help. Grants can also enable innovation by supporting its inputs: young or exceptional scientists, new institutions, research networks, and large datasets. Taken as a whole, grants do not form a monolithic, blunt innovation lever; instead, they provide a varied and nuanced set of policy options, and we should recognize and develop their usefulness in promoting major social goals.
This paper explores the use of bundling to reduce adverse selection in insurance mar-kets and its application to social health insurance programs. When the choice to buy health insurance is made at the household level, bundling the insurance policies of household mem-bers eliminates the eﬀect of adverse selection within a household since the household can no longer select only sick members to enroll. However, this can exacerbate adverse selection across households, as healthier households might choose to drop out of the insurance market. The net eﬀect of this trade-oﬀ depends on the characteristics of the household demand for medical care and risk preferences. I explore this issue using individual survey data on insur-ance enrollment and medical spending in Vietnam that contain detailed information about the structure of the household. The reduced-form evidence suggests that income, own-price and cross-member substitution eﬀects play important roles in the demand for medical care, which aﬀects a household’s selection of members into insurance. I then develop and estimate a model of household insurance bundle choice and medical utilization that accounts for these features. The results suggest that much of the adverse selection is concentrated within the household. Counterfactual analysis reveals that under optimal pricing, household bundling yields signiﬁcantly higher consumer surplus and insurance enrollment than individual pur-chase. Furthermore, the insurance market is less susceptible to complete unraveling under household bundling.
We ascertain the degree of service-level selection in Medicare Advantage (MA) using individual level data on the 100 most frequent HCC’s or combination of HCC’s from two national insurers in 2012-2013. We find differences in the distribution of beneficiaries across HCC’s between TM and MA, principally in the smaller share of MA enrollees with no coded HCC, consistent with greater coding intensity in MA. Among those with an HCC code, absolute differences between MA and TM shares of beneficiaries are small, consistent with little service-level selection. Variation in HCC margins does not predict differences between an HCC’s share of MA and TM enrollees, although one cannot a priori sign a relationship between margin and service-level selection. Margins are negatively associated with the importance of post-acute care in the HCC. Margins among common chronic disease classes amenable to medical management and typically managed by primary care physicians are larger than among diseases typically managed by specialists. These margin differences by disease are robust against a test for coding effects and suggest that the average technical efficiency of MA relative to TM may vary by diagnosis. If so, service-level selection on the basis of relative technical efficiency could be welfare enhancing.
The United States devotes a lot more of its economic resources to health care than any other nation, and yet its health care outcomes aren’t better for it.
That hasn’t always been the case. America was in the realm of other countries in per-capita health spending through about 1980. Then it diverged.
It’s the same story with health spending as a fraction of gross domestic product. Likewise, life expectancy. In 1980, the U.S. was right in the middle of the pack of peer nations in life expectancy at birth. But by the mid-2000s, we were at the bottom of the pack.
Health care spending rarely follows an ordinary, rational model. Yet even in that context, prescription drug prices are rising at a puzzling rate. What is causing the phenomenon? Quite simply, incentives percolating throughout the prescription drug market push players toward higher prices. At the center, lies the highly secretive and concentrated PBM industry — middle players who negotiate between drug companies and health insurers, arranging for rebates and establishing coverage levels for patients.
Contracts between drug companies and the middle players are closely guarded secrets. The PBM customers, including Medicare, private insurers, and even their auditors, are not permitted access to the terms. And the middle players are not alone; everyone is feeding at the trough.
Markets, like gardens, grow best in the sun; they wither without information. Thus, competitive distortions and suboptimal outcomes are unsurprising.
Despite the extreme secrecy, details have begun to seep out — through case documents (including recent contract disputes among parties), government reports, shareholder disclosures, and industry insider reports. Piecing together these sources, this article presents a picture of incentive structures in which higher-priced drugs receive favorable treatment, and patients are channeled towards more expensive medicines. In exchange for financial incentives structured in different ways to appeal to hospitals, insurers, doctors, and even patient advocacy groups, drug companies ensure that lower-priced substitutes cannot gain a foothold. It is a win-win for everyone, except of course for taxpayers and society. This article also analyzes popular proposals that are unlikely to work and suggests approaches for aligning incentives.
In this paper we set up an overlapping generations model of gerontological founded human aging that takes the interaction between R&D-driven medical progress and access to health care into account. We use the model to explore potential futures of human health and longevity. For the baseline policy scenario of health care access, the calibrated model predicts substantial future increases in health and life expectancy, associated with rising shares of health expenditure in GDP. Freezing the expenditure share at the 2020 level by rationing access to health care severely reduces potential gains in health, longevity and welfare. These losses are greatest in the long run due to reduced incentives for medical R&D. For example, rationing is predicted to reduce potential gains of life-expectancy at age 65 by about 4 years in the year 2050. Generally, and perhaps surprisingly, young individuals (i.e. those who save the most health care contributions through rationing) are predicted to suffer the greatest losses in terms of life expectancy and welfare.
Consumer Engagement in Health Care Among Millennials, Baby Boomers, and Generation X: Findings from the 2017 Consumer Engagement in Health Care SurveyMay 13, 2018
The EBRI/Greenwald & Associates Consumer Engagement in Health Care Survey (CEHCS) is an online survey that examines issues surrounding consumer-driven health care, including the cost of insurance, the cost of care, satisfaction with health care, satisfaction with health care plans, reasons for choosing a plan, and sources of health information. It is co-sponsored by the Employee Benefit Research Institute (EBRI) and Greenwald & Associates, with support from seven private organizations.
The 2017 survey was conducted online Aug. 10 to Sept. 1, 2017, using the Ipsos’ consumer panel. Over 3,560 adults ages 21−64 who had health insurance provided through an employer, purchased directly from a carrier, or purchased through a government exchange participated in the survey. However, most survey participants (82 percent) received coverage through an employer. The sample was weighted to reflect the actual proportions in the population ages 21–64 with private, health-insurance coverage.
This Issue Brief focuses on differences in consumer engagement in health care by generational cohorts – i.e., Millennials, Baby Boomers, and Gen Xers.
• Millennials are more satisfied than other generational cohorts with various aspects of their health coverage. More than other generational cohorts, Millennials are satisfied with their health coverage, out-pocket costs, and health plan choices.
• Millennials and Generation X engage with health care providers differently than Baby Boomers. Baby Boomers are more likely than Gen Xers and Millennials to have a primary care provider (PCP). Among those with a PCP, Baby Boomers are more likely than Generation X and Millennials to report that they make healthier lifestyle choices after seeing a PCP; that it is important that their PCP knows them and their medical history personally; that their PCP is aware of all of the other medical care that they receive; and that they are comfortable telling their PCP about their health issues. Both Millennials and Generation X are more likely than Baby Boomers to report that they have used a walk-in clinic.
• Millennials have the highest rates of wellness program participation. Millennials are nearly across the board more likely than Baby Boomers to participate in various aspects of wellness programs. They are more likely to report that they have visited an on-site clinic; made a tobacco-free pledge or participated in a smoking cessation program; participated in counseling or stress management training; participated in activity-based wellness challenges; received reimbursement for fitness club memberships; attended free seminars; and received financial wellness resources. Millennials are less likely than Baby Boomers to have completed a health risk assessment or biometric screenings.