Anthropometrics is a research program that explores the extent to which economic processes affect human biological processes using height and weight as markers. This agenda differs from health economics in the sense that instead of studying diseases or longevity, macro manifestations of well-being, it focuses on cellular-level processes that determine the extent to which the organism thrives in its socio-economic and epidemiological environment. Thus, anthropometric indicators are used as a proxy measure for the biological standard of living as complements to conventional measures based on monetary units.
Using physical stature as a marker, we enabled the profession to learn about the well-being of children and youth for whom market-generated monetary data are not abundant even in contemporary societies. It is now clear that economic transformations such as the onset of the Industrial Revolution and modern economic growth were accompanied by negative externalities that were hitherto unknown. Moreover, there is plenty of evidence to indicate that the Welfare States of Western and Northern Europe take better care of the biological needs of their citizens than the market-oriented health-care system of the United States.
Obesity has reached pandemic proportions in the United States affecting 40% of the population. It is fostered by a sedentary and harried lifestyle, by the diminution in self-control, the spread of labor-saving technologies, and the rise of instant gratification characteristic of post-industrial society. The spread of television and a fast-food culture in the 1950s were watershed developments in this regard that accelerated the process. Obesity poses a serious health risk including heart disease, stroke, diabetes, and some types of cancer and its cost reaches $150 billion per annum in the United States or about $1,400 per capita. We conclude that the economy influences not only mortality and health but reaches bone-deep into the cellular level of the human organism. In other words, the economy is inextricably intertwined with human biological processes.
Andrea Gabrio, Gianluca Baio, and Andrea Manca
The evidence produced by healthcare economic evaluation studies is a key component of any Health Technology Assessment (HTA) process designed to inform resource allocation decisions in a budget-limited context. To improve the quality (and harmonize the generation process) of such evidence, many HTA agencies have established methodological guidelines describing the normative framework inspiring their decision-making process. The information requirements that economic evaluation analyses for HTA must satisfy typically involve the use of complex quantitative syntheses of multiple available datasets, handling mixtures of aggregate and patient-level information, and the use of sophisticated statistical models for the analysis of non-Normal data (e.g., time-to-event, quality of life and costs). Much of the recent methodological research in economic evaluation for healthcare has developed in response to these needs, in terms of sound statistical decision-theoretic foundations, and is increasingly being formulated within a Bayesian paradigm. The rationale for this preference lies in the fact that by taking a probabilistic approach, based on decision rules and available information, a Bayesian economic evaluation study can explicitly account for relevant sources of uncertainty in the decision process and produce information to identify an “optimal” course of actions. Moreover, the Bayesian approach naturally allows the incorporation of an element of judgment or evidence from different sources (e.g., expert opinion or multiple studies) into the analysis. This is particularly important when, as often occurs in economic evaluation for HTA, the evidence base is sparse and requires some inevitable mathematical modeling to bridge the gaps in the available data. The availability of free and open source software in the last two decades has greatly reduced the computational costs and facilitated the application of Bayesian methods and has the potential to improve the work of modelers and regulators alike, thus advancing the fields of economic evaluation of healthcare interventions. This chapter provides an overview of the areas where Bayesian methods have contributed to the address the methodological needs that stem from the normative framework adopted by a number of HTA agencies.
Economists have long regarded healthcare as a unique and challenging area of economic activity on account of the specialized knowledge of healthcare professionals (HCPs) and the relatively weak market mechanisms that operate. This places a consideration of how motivation and incentives might influence performance at the center of research. As in other domains economists have tended to focus on financial mechanisms and when considering HCPs have therefore examined how existing payment systems and potential alternatives might impact on behavior. There has long been a concern that simple arrangements such as fee-for-service, capitation, and salary payments might induce poor performance, and that has led to extensive investigation, both theoretical and empirical, on the linkage between payment and performance. An extensive and rapidly expanded field in economics, contract theory and mechanism design, had been applied to study these issues. The theory has highlighted both the potential benefits and the risks of incentive schemes to deal with the information asymmetries that abound in healthcare. There has been some expansion of such schemes in practice but these are often limited in application and the evidence for their effectiveness is mixed. Understanding why there is this relatively large gap between concept and application gives a guide to where future research can most productively be focused.