Bringing the patient back in: behavioral decision-making and choice in medical economics

Abstract

We explore the behavioral methodology and “revolution” in economics through the lens of medical economics. We address two questions: (1) Are mainstream economic assumptions of utility-maximization realistic approximations of people’s actual behavior? (2) Do people maximize subjective expected utility, particularly in choosing from among the available options? In doing so, we illustrate–in terms of a hypothetical experimental sample of patients with dry eye diagnosis—why and how utility in pharmacoeconomic assessments might be valued differently by patients when subjective psychological, social, cognitive, and emotional factors are considered. While experimentally-observed or surveyed behavior yields stated (rather than revealed) preferences, behaviorism offers a robust toolset in understanding drug, medical device, and treatment-related decisions compared to the optimizing calculus assumed by mainstream economists. It might also do so more perilously than economists have previously understood, in light of the intractable uncertainties, information asymmetries, insulated third-party agents, entry barriers, and externalities that characterize healthcare. Behavioral work has been carried out in many sub-fields of economics. Only recently has it been extended to healthcare. This offers medical economists both the challenge and opportunity of balancing efficiency presumptions with relatively autonomous patient choices, notwithstanding their predictable, yet seemingly consistent, irrationality. Despite its comparative youth and limitations, the scientific contributions of behaviorism are secure and its future in medical economics appears to be promising.

Keywords:

• Behaviorism
• counter-intuitive
• efficiency
• experimentation
• pharmacoeconomic assessments
• predictable irrationality
• revealed preferences
• utility-maximization

JEL classification codes:

• C91
• D83
• D91
• I12

At the annual international convention of economists held in Philadelphia from January 4–7, 2018¹, no less than 20 panel sessions were devoted to health economics, each of which featured three paper presentations. Several offered cost assessments of novel therapeutic and device interventions. Among these are the adoption and diffusion of and returns from new medical technology, namely percutaneous coronary interventions (PCI) for acute myocardial infarction², and transcatheter aortic valve replacement (TAVR)³; pharmaceutical innovations stimulated by the FDA’s Breakthrough Therapy Designation (BTD) for new drugs⁴; the effect of Prescription Drug Monitoring Programs (PDMPs) on drug quantities and deaths⁵; and the impact of oncology practice consolidation on prices of outpatient, prescription drug-based cancer treatment paid by commercial insurers and patients⁶. Besides my affiliation with the host associations, I attended the convention as a board member for the Journal of Medical Economics, together with journal staff.

While often used interchangeably with health economics, medical economics as a distinct sub-specialty seeks to optimize medical outcomes while containing costs, so that drugs, devices, and medical treatments yield the highest outcome per dollar spent⁷. Whether in the form of cost-effect comparisons or analyses of the economic burden of diseases, original studies published in the Journal of Medical Economics exemplify this objective. Evaluating the pharmacoeconomic literature, employing suitable economic modeling techniques, and incorporating medical economic theory into healthcare policies and practices have become increasingly common, both nationally and internationally, in promoting the most efficient and appropriate utilization of pharmaceutical products and medical treatments.

In contrast to many comparative cost studies, the referenced papers and panel discussions partly inquired into how patients and institutions might have valued the choices or alternatives before them, and what behavioral factors could have influenced their decision calculus. For example, in documenting the evolution of productivity and practice style in the use of PCI (without, and later with, stenting), the authors developed a model of treatment choice to demonstrate how these evolve over time, allowing for measurements of tradeoffs between short-run and long-run quality and cost considerations over PCI’s life cycle². In the BTD study, the authors calculated trade-offs between faster time-to-market for new drugs and patient safety risks in examining certain behavioral incentives for new drug development. They found a slightly higher rate of adverse events among BTD drugs, although they appear to considerably enhance patient access to them⁴. The study on prescription drug-based cancer care asked whether increased payment associated with provider (oncology practice) consolidation alters patient demand propensities for cancer care⁶. Although it was not a costing study, one other convention paper may be worth mentioning here for its behavioral insights. In analyzing consumer choice and learning in federally-facilitated marketplaces under the US Affordable Care Act, the authors concluded that a “deeper understanding of consumer decision-making is fundamental to improving the design of insurance markets as well as ensuring that the individual insurance market is attractive to insurers”⁸. It drew attention to behavioral aspects of consumer choice in any marketplace and market design, including for pharmaceutical products.

The behavioral dimension these papers touched one way or the other, and which made for some very interesting panel and convention dinner discussions, is rather timely. Barely 3 months earlier, in October 2017, the Nobel Prize in Economic Sciences was awarded to Richard Thaler of the University of Chicago. Considered the most prestigious award in the profession, it recognized Thaler’s work “in creating the new and rapidly expanding field of behavioural economics”, “[b]y exploring the consequences of limited rationality, social preferences, and lack of self-control” among individuals, and “how these human traits systematically affect individual decisions as well as market outcomes”⁹. As the New York Times ably reported:

Mainstream economics was built on the simplifying assumption that people behave rationally. Economists understood that this was not literally true, but they argued that it was close enough.

Professor Thaler has played a central role in pushing economists away from that assumption. He did not simply argue that humans are irrational, which has always been obvious, but is not particularly helpful. Rather, he showed that people depart from rationality in consistent ways, so their behavior can still be anticipated and modeled (italics applied).

…

The Nobel committee, announcing the award in Stockholm, said that it was honoring Professor Thaler for his pioneering work in establishing that people are predictably irrational—that they consistently behave in ways that defy economic theory. People will refuse to pay more for an umbrella during a rainstorm; they will use the savings from lower gas prices to buy premium gasoline; they will offer to buy a coffee mug for $3 and refuse to sell it for $6.

…

In a presidential address to the American Economic Association (AEA) in January 2016, Professor Thaler predicted behavioral economics would succeed so well it would eventually disappear.

“I think it is time to stop thinking about behavioral economics as some kind of revolution,” he said. In time, he added, “all economics will be as behavioral as the topic requires”¹⁰.

Of course, Thaler is neither the first nor the only one deserving of credit and recognition. The upsurge of interest in behavioral economics preceded Thaler’s Nobel Prize, and has occurred at least in the last two decades. Herbert Simon, Amos Tversky, Daniel Kahneman, Vernon Smith, and Robert Schiller, among others, have made equally significant and multi-awarded contributions. If, at all, the 2017 Nobel Prize formally acknowledged and honored behaviorism’s entrenchment in the economic sciences. To others, however, it also meant putting the rational choice mainstream on the defensive¹¹. Whether as an object of investigation or as something invoked to explain outcomes of interest, behavioral decision-making—even if it may not be theoretically optimal—has undoubtedly reshaped, and continues to reshape, the economic landscape. The effects of psychological, social, cognitive, and emotional factors on the economic decisions of individuals and institutions, and their consequences for market prices, returns, and resource allocation inevitably raise two challenging questions:

1. Are mainstream economic assumptions of utility-maximization realistic approximations of people’s actual behavior?

2. Do people maximize subjective expected utility (value), particularly in choosing from among the available options?

In addressing these questions, it might be initially helpful to see how the behavioral approach and “revolution” has enriched experimental economics in ways that have accounted for their frequently assumed synonymity. For one, much behavioral work in economics has been done by means of experimentation. The infusion of psychology, along with sociology and neuroscience, has also turned experimental work on economic decision-making more interdisciplinary. That is important considering that “economics does not have a long-established tradition of experimental work, and experimenters are forced to develop their methodology and philosophy at the same time they investigate particular phenomena”^{12 (p. 3)}. Economic experiments borrow from a rich tradition in cognitive psychology and related disciplines to study behavior and preferences within a controlled setting. There, subjects choose between alternatives that typically carry real financial payoffs which are incentive-compatible and determined by the choices that subjects make^13,14. Controlled and incentivized experiments (whose protocols are standardized and pre-tested) contrast with survey measures of behavior and preferences where subjects can consciously or unconsciously misrepresent their preferences at no cost to themselves¹⁴. However, the propensity for controlled experimentation in economics is tempered by the expense involved, as well as ethical questions in the use of human subjects. On the other hand, natural and quasi economic experiments—for which psychologists and sociologists have made significant strides—do not seek to manipulate control and test groups. Instead, these are allowed to be influenced by nature (i.e. factors that cannot be randomized and are beyond the researchers’ control)¹⁵. Natural and many quasi experiments, nonetheless, subscribe to the primary principles of experimental study because the control group has clearly defined exposure to some condition, which is absent in the test group for comparison. The observed outcomes of these experiments can be credited to the exposure, so that there is some cause for discovering a causal relationship as opposed to a simple correlation¹⁶. The potential for causality differentiates natural and many quasi experiments from non-experimental observational research^16,17.

To choice modeling, behavioral methodologies introduced stated preferences, as distinguished from the mainstream’s revealed preferences. The latter assume that consumer choices are revealed by their purchasing habits (e.g. willingness to pay for a particular commodity over another). Stated preference studies use choices made under experimental conditions to estimate utilities. These studies allow behavioral economists to enquire into the motivations for people’s choices and actions, rather than looking solely at utility-maximizing behavior and aggregate data like prices, quantities, and resource allocation outcomes. As Amartya Sen reminds us, while economists tend to sanctify the notion of rational choice, rationality is non-sensical if it is not motive-related, but only behavioral from an efficiency standpoint. That is because the source/s of the optimization interpretation is external to the observed behavior used for determining which preferences an individual might possess and reveal^18,19. Also, as economists gradually come to terms with experimental or survey results that seemingly falsify utility theory (and lead them to uncover preference reversals), many of them have come to formulate more psychologically and sociologically realistic theories of human choice^20,21. Some have combined revealed and stated preferences in choice modeling, so that it can be anchored on observed choices, as new or out-of-range alternatives based on hypothetical choices are considered²⁰.

Psychosocial underpinnings, experimentation, incentive-induced motivation, predictable irrationality, and counter-intuitive choice—what do they hold for the sub-field of medical economics? Specifically, what is behaviorism’s contribution and future in medical economics, especially as it pertains to costings of pharmaceutical products and medical treatments, heavy as these are on mathematical modeling for synthesizing financial data with biostatistical and epidemiological outcomes? I believe that behavioral approaches and methodologies offer a robust toolset for the study of wide-ranging consumer or patient behaviors involving, among others, trade-offs related to finite resources and critical time and informational constraints. Where experimentation, surveying, or observation reveals that people do not have the mental capacity to consider huge amounts of information and feasible options, and neither do they have tastes endemic to them and not subject to manipulation, preferences for drugs, devices, or treatments unravel the fundamental disconnect between rationality presumptions and decisional realities. By not assuming that patients simply optimize expected utility when presented with cost-efficient options, realistic healthcare strategies and policy interventions can be devised beyond simply manipulating prices, quantities, and allocations of available resources.

Let us assume, for illustration, that randomized patients are uniformly suffering from dry eyes (keratoconjunctivitis sicca) owing to meibomian gland dysfunction (MGD), with or without blepharitis.* MGD is the root cause of dry eyes in almost 9 out of every 10 patients.²² Assume further that their respective opthalmologists recommended medical grade fish oil (omega-3 essential fatty acids), given its efficacy in relieving chronic ocular surface inflammation (both an MGD symptom and cause) and improving the quality of oil in tears²². The choice of whether to purchase physician-recommended, albeit expensive, brand-name X or the comparatively cost-effective generic version Y involves micro-decisions about how to allocate time, energy, and search and information costs. Reviewing and consulting about comparative pharmacoeconomic analyses of fish oil, and then searching for and comparing sellers, are costly in terms of patient time and energy expenditures today. However, they provide rewards (e.g. lower medical costs and improved vision health) in the future.

In dealing with these constraints and forming judgments, another (behavioral) experiment or survey might find that most patients relied for decision-making on heuristics (mental shortcuts or rules of thumb that focus on one aspect of a problem or solution)²³; or framing (collection of anecdotes and stereotypes that make up a person’s emotional filters)²⁴; or prospecting (decision-making based on the potential value of losses and gains evaluated using certain heuristics, rather than the final outcome)²⁵. Hence, patients might fail to grapple with self-control, attach too much value to present enjoyments as opposed to future well-being, assign a lower value (e.g. due to beliefs, anecdotal evidence, marketing) to new information finding for the comparatively cost-effective Y, and overstate the risk and uncertainty of some contingencies, while understating them for others.

These and other cognitive and social biases lead to systematic deviations from logic, probability, and efficiency. They could drive most patients in our hypothetical illustration to select the costlier brand X without any reservation. While it is evidently not in their long-run best interest, and might suggest that these patients do not know what will make them better off, these biases present a more realistic picture of what humans often make out of medical economic analyses (i.e. they may not collect the necessary information, even if available, or do not use it properly). Would counter-intuitive choice X change if patients were subsequently offered a certain sum of money to pay for their product choice for a period of time (e.g. 6 months worth of supply) and allowed to keep whatever amount was left after their purchase? And could a different cue lead them to a different calculus? It would be interesting to see how financial and other payoffs might alter patients’ valuation of expected utility in an experimental behavioral study. Real-world decision-making in this instance becomes “not only more interesting than the hyperrational calculus assumed by economic theory, but also more perilous than economists have previously understood, particularly in areas touching on health and healthcare”^{26 (p. 439)}. Yet, behavioral studies bring the patient back in as a relatively autonomous, albeit predictably irrational, decision-maker. There lies a new horizon for advancing research in medical economics.

The AEA launched a registry for randomized controlled trials at the 2018 economics convention. This should be a very valuable resource for investigators to share their work and for others to find out about on-going and completed economic experiments. Studies that meld economics with psychology and other behavioral disciplines can be carried out independently of the authors who published the pharmacoeconomic assessments. Or they could be initiated by the original authors themselves as an expanded or second phase of their research agenda. Although behavioral work has been pursued in many areas of economics, only recently has it been extended to healthcare. As with any problem-solving approach or methodology, behaviorism has its limitations. Among them are lack of a unifying foundational theory, being a collection of loosely related and situation-specific observations at this stage of its development, and the skepticism over stated preferences (from experimentally-observed or surveyed behavior), particularly in value determination^26,27. Several behaviorists have qualified or outrightly dismissed these claims as vestiges of hardcore rationalists’ resistance and by pointing out the consistent results typically generated from multiple situations and geographies which have yielded key theoretical and practical insights²⁸, including for healthcare²⁶.

In its statement of aims and scope, the Journal of Medical Economics encourages studies that explore health economics “methodologies” and “modeling” as much as it does economic analyses of therapeutic and device interventions. While the latter tend to populate the monthly issues, the journal continuously strives for a balanced representation of the “economics” side of its title. Actual, rather than assumed, choices of medications and treatments analyzed in cost-and-outcomes studies put patients center-stage as ultimate healthcare decision-makers as well as beneficiaries. Thus, behavioral economics betters our understanding of and influence over health-affecting behaviors, particularly in light of the intractable uncertainties, information asymmetries, insulated third-party agents, entry barriers, and externalities that characterize healthcare. After all, as one medical economist aptly put it, “many of the most vexing problems facing individuals and society as a whole in healthcare are neither medical nor scientific in nature; they are behavioral”^{26 (p. 432)}.

In his AEA presidential address before the 2018 Philadelphia convention, Alvin Roth—himself a Nobel economist—thanked the profession for its “open culture” and for being so “welcoming”, even if his entire academic training is in engineering. There is plenty of room for cross-fertilization of ideas, he said, including those from immigrant fields for which “economists are on the whole enthusiastic”²⁹. This we should “treasure gratefully, but also vigilantly”²⁹, to ensure that new and alternative ways of exploring human behavior are capable of addressing vital economic questions. Despite its relative youth and limitations, the scientific contributions of behaviorism are secure and its future in medical economics appears to be promising.

Transparency

Declaration of funding

This paper has received no funding.

Declaration of financial/other relationships

The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in, or financial conflict with, the subject matter or materials discussed in the manuscript. This may include employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgements

The author is grateful to two anonymous referees and the editor-in-chief of this journal, Kenneth K. Lee, for helpful comments and suggestions. Initial discussions with Kelly Soldavin and Tanya Stezhka, and the editorial assistance of Charlotte McSharry, of Taylor & Francis are also acknowledged with thanks. The usual caveat applies.

Note

Notes

*Much of this illustration draws from my ongoing research project on the comparative cost-effectiveness of medical grade, omega-3 fish oils in patients with meibomian gland dysfunction (MGD).