Medical Aid In Dying And Telemedicine: Improving Access And Protecting Patients by Konstanin Tretyakov :: SSRN

Medical aid in dying is a form of medical treatment recognized in several states and the District of Columbia and available to adult residents of those states who are competent and suffer from a terminal disease. It is critical to ensure timely access to this form of treatment to qualifying patients. The paper explores the possibility of improving access to medical aid in dying via telemedicine — a method of delivery of health care remotely by means of electronic communication. The paper explores the feasibility of this option from clinical and legal perspectives and also explores several normative issues lying at the intersection of telemedicine and medical aid in dying.

via Medical Aid In Dying And Telemedicine: Improving Access And Protecting Patients by Konstanin Tretyakov :: SSRN

Social Determinants of mHealth Effectiveness: Evidence from a Large-Scale Experiment

mHealth holds great promise to promote health and improve care. However, most mHealth treatments failed to achieve a significant impact on clinical outcomes, and there is surprisingly little knowledge of factors that affect mHealth effectiveness. This study examines mHealth effectiveness from a social determinant perspective. We leverage one of the world’s largest field experiments on improving the health of expectant mothers and reducing cesarean sections. We hypothesize that the husband, as one of the most significant social factors, can be an important moderator in mHealth effectiveness. Our analyses show that the husband’s healthy behavior is pivotal to enable mHealth in reducing cesarean sections. The cesarean section reduction in the strongest intervention group is 12 times bigger for those wives whose husbands exercise often that those whose husbands do not exercise. Further analyses reveal that the husband exercise behavior has a stronger influence on mHealth effectiveness when the husband has a more dominating socioeconomic status. Our findings represent one of the first studies on the critical role of social support in determining mHealth effectiveness, which has important implications to both academic research and practice of mHealth.

via Social Determinants of mHealth Effectiveness: Evidence from a Large-Scale Experiment by Weiguang Wang, Yanfang Su, Guodong (Gordon) Gao :: SSRN

Grants

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.

via Grants by W. Nicholson Price :: SSRN

Why Has Economic Growth Slowed When Innovation Appears to Be Accelerating?

Measured between quarters with identical unemployment rates, U. S. economic growth slowed by more than half from 3.2 percent per year during 1970-2006 to only 1.4 percent during 2006-16, and only half of this GDP growth slowdown is accounted for diminished productivity growth. The paper starts from the proposition that GDP growth matters, not just productivity growth, because slower GDP growth provides fewer resources to address the nation’s problems, including faltering education, aging infrastructure, and the looming shortfall in funding for Social Security and Medicare, and it also implies lower net investment and a reduced rate at which new capital can embody the latest technology. The paper documents the contribution to slower GDP growth of the separate components of demography — fertility, mortality, life expectancy, and immigration. Particular emphasis is placed on the interaction between rising inequality and the slower secular rise of life expectancy in the U.S. compared to other developed countries, both in the form of a large gap in life expectancy between rich and poor, and the stagnation of life expectancy for the lowest income quintile. Further contributions to slowing growth are made by a decline in the population share of both legal and illegal immigration and a turnaround from rising to declining labor force participation. Rising inequality creates a gap between the growth of average real per-capita income relative to that of median real income, and alternative measures of the evolution of this gap are compared and assessed.Causes of declining productivity growth begin with the slowdown in the rate of increase of educational attainment resulting from the interplay of demand and supply factors, including the flattening of the college wage premium and the rising relative price of college education. Why did productivity growth decline after 2006 despite an increase in the rate at which new U.S. patents were issued in 2006-16 compared to earlier decades? Part of the slowdown is attributed to the maturity of the IT revolution, which also helps to explain the trajectory of the college wage premium. Aspects of the productivity growth slowdown include the declining productivity of research workers, diminishing returns to drug innovation, and the evolutionary rather than revolutionary impact of robots and artificial intelligence, which are replacing workers slowly and only in a minority of industrial sectors throughout the economy. Also considered are alternative explanations of slower productivity growth, including low investment and mismeasurement.

via Why Has Economic Growth Slowed When Innovation Appears to Be Accelerating? by Robert J. Gordon :: SSRN

The Impact of New Drug Launches on Life-Years Lost in 2015 from 19 Types of Cancer in 36 Countries

This study employs a two-way fixed effects research design to measure the mortality impact and cost-effectiveness of cancer drugs: it analyzes the correlation across 36 countries between relative mortality from 19 types of cancer in 2015 and the relative number of drugs previously launched in that country to treat that type of cancer, controlling for relative incidence.One additional drug for a cancer site launched during 2006-2010 is estimated to have reduced the number of 2015 disability-adjusted life years (DALYs) lost due to cancer at that site by 5.8%. The estimated cost per life-year gained at all ages in 2015 from cancer drugs launched during 2006-2010 is $1635.We estimate that drugs launched during the entire 1982-2010 period reduced the number of cancer DALYs lost in 2015 by about 23%. In the absence of new drug launches during 1982-2010, there would have been 26.3 million additional DALYs lost in 2015.

via The Impact of New Drug Launches on Life-Years Lost in 2015 from 19 Types of Cancer in 36 Countries by Frank R. Lichtenberg :: SSRN

Service Systems with Heterogeneous Customers: Investigating the Effect of Telemedicine on Chronic Care

Medical specialists treating chronic conditions typically face a heterogeneous set of patients. Such heterogeneity arises because of differences in medical conditions as well as the travel burden each patient faces to visit the clinic periodically. Given this heterogeneity, we compare the strategic behavior of revenue-maximizing and welfare-maximizing specialists and prove that the former will serve a smaller patient population, spend more time with the patients, and have shorter waiting times. We also analyze the impact of telemedicine technology on patient utility and the specialists’ operating decisions. We consider both the case when specialists can freely set their own fee for service and the case when fees are set exogenously by a third-party payer. We prove that with the introduction of telemedicine the specialists become more productive and the overall social welfare increases, though some patients, unexpectedly, will be worse off. Our analytical results lead to some important policy implications for facilitating the further deployment of telemedicine in the care of chronically ill patients.

via Service Systems with Heterogeneous Customers: Investigating the Effect of Telemedicine on Chronic Care by Balaraman Rajan, Tolga Tezcan, Abraham Seidmann :: SSRN

Concentrating on the Fall of the Labor Share by David H. Autor, David Dorn, Lawrence F. Katz, Christina Patterson, John Van Reenen :: SSRN

The recent fall of labor’s share of GDP in numerous countries is well-documented, but its causes are poorly understood. We sketch a “superstar firm” model where industries are increasingly characterized by “winner take most” competition, leading a small number of highly profitable (and low labor share) firms to command growing market share. Building on Autor et al. (2017), we evaluate and confirm two core claims of the superstar firm hypothesis: the concentration of sales among firms within industries has risen across much of the private sector; and industries with larger increases in concentration exhibit a larger decline in labor’s share.

Source: Concentrating on the Fall of the Labor Share by David H. Autor, David Dorn, Lawrence F. Katz, Christina Patterson, John Van Reenen :: SSRN

The Social Value of Health Research and the Worst Off by Nicola Barsdorf, Joseph Millum :: SSRN

In this article we argue that the social value of health research should be conceptualized as a function of both the expected benefits of the research and the priority that the beneficiaries deserve. People deserve greater priority the worse off they are. This conception of social value can be applied for at least two important purposes: (1) in health research priority setting when research funders, policy‐makers, or researchers decide between alternative research projects; and (2) in evaluating the ethics of proposed research proposals when research ethics committees (RECs) assess whether the social value of the research is sufficient to justify the risks and burdens to research participants and others. In assessing how far a proposed research project will advance the interests of people who are more disadvantaged, research priority setters and RECs should examine (at least) the diseases that the research targets and the type of research. Just as certain diseases impose a greater burden on people who are more disadvantaged, so certain types of intervention and forms of research are more likely to benefit people who are more disadvantaged. We outline which populations are likely to be representative of the global worst off and identify what types of health research, and which disease categories, are priorities for these populations.

Source: The Social Value of Health Research and the Worst Off by Nicola Barsdorf, Joseph Millum :: SSRN

How Does Technological Change Affect Quality ­Adjusted Prices in Health Care? Systematic Evidence from Thousands of Innovations by Kristopher Hult, Sonia Jaffe, Tomas Philipson :: SSRN

Medical innovations have improved survival and treatment for many diseases but have simultaneously raised spending on health care. Many health economists believe that technological change is the major factor driving the growth of the heath care sector. Whether quality has increased as much as spending is a central question for both positive and normative analysis of this sector. This is a question of the impact of new innovations on quality-adjusted prices in health care. We preform a systematic analysis of the impact of technological change on quality-adjusted prices, with over six thousand comparisons of innovations to incumbent technologies. For each innovation in our dataset, we observe its price and quality, as well as the price and quality of an incumbent technology treating the same disease. Our main finding is that an innovation’s quality-adjusted prices is higher than the incumbent’s for about two-thirds (68%) of innovations. Despite this finding, we argue that quality-adjusted prices may fall or rise over time depending on how fast prices decline for a given treatment over time. We calibrate that price declines of 4% between the time when a treatment is a new innovation and the time when it has become the incumbent would be sufficient to offset the observed price difference between innovators and incumbents for a majority of indications. Using standard duopoly models of price competition for differentiated products, we analyze and assess empirically the conditions under which quality-adjusted prices will be higher for innovators than incumbents. We conclude by discussing the conditions particular to the health care industry that may result in less rapid declines, or even increases, in quality-adjusted prices over time.

Source: How Does Technological Change Affect Quality ­Adjusted Prices in Health Care? Systematic Evidence from Thousands of Innovations by Kristopher Hult, Sonia Jaffe, Tomas Philipson :: SSRN

A Very Depressing Paper on the Great Stagnation – Marginal REVOLUTION

Since 1950 life expectancy at birth has been growing at a remarkably steady rate of about 1.8 years per decade but that growth has only been bought by ever increasing number of researchers. Here, for example, is cancer mortality as function of the number of publications or clinical trials. Each clinical trial used to be associated with ~8 lives saved per 100,000 people but today a new clinical trial is associated with only ~1 life saved per 100,000.

Source: A Very Depressing Paper on the Great Stagnation – Marginal REVOLUTION