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ORIGINAL ARTICLE Promising Approaches From Behavioral Economics to Improve Patient Lung Cancer Screening Decisions Andrew J. Barnes, PhD a , Lauren Groskaufmanis, MPH b, Norman B. Thomson III, MD, MBA c Abstract Lung cancer is a devastating disease, the deadliest form of cancer in the world and in the United States. As a consequence of CMS’s determination to provide low-dose CT (LDCT) as a covered service for at-risk smokers, LDCT lung cancer screening is now a covered service for many at-risk patients that first requires counseling and shared clinical decision making, including discussions of the risks and benefits of LDCT screening. However, shared decision making fundamentally relies on the premise that with better information, patients will arrive at rational decisions that align with their preferences and values. Evidence from the field of behavioral economics offers many contrary viewpoints that take into account patient decision making biases and the role of the shared decision environment that can lead to flawed choices and that are particularly relevant to lung cancer screening and treatment. This article discusses some of the most relevant biases, and suggests incorporating such knowledge into screening and treatment guidelines and shared decision making best practices to increase the likelihood that such efforts will produce their desired objectives to improve survival and quality of life. Key Words: Behavioral economics, lung cancer, cancer screening, smoking J Am Coll Radiol 2016;13:1566-1570. Copyright 2016 American College of Radiology INTRODUCTION Lung cancer is a devastating disease, the deadliest form of cancer in the world and in the United States (US), expected to account for 158,080 deaths (26.5% of all cancer deaths) in the US in 2016, with 224,390 newly diagnosed cases this year [1]. The 5-year survival rate remains a dismal 17.7%, with only slight improvement over the past four decades, despite advances in diagnosis and treatment [1]. The annual direct costs (ie, use of resources for cancer care) of lung cancer in 2020 are projected to be in the range of $14.7 billion to $18.8 billion [2]. Costs due to lost time and productivity are more difficult to model but are likely larger than direct costs [3]. a Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond, Virginia. b School of Medicine, Duke University, Durham, North Carolina. c Department of Radiology and Imaging, Medical College of Georgia, Augusta University, Augusta, Georgia. Corresponding author and reprints: Andrew J. Barnes, PhD, Department of Health Behavior and Policy, Virginia Commonwealth University, 830 East Main Street, 9th floor, Richmond, VA 23219; e-mail: Andrew.barnes@ vcuhealth.org. The authors have no conflicts of interest related to the material discussed in this article. A sea change in lung cancer care occurred with the release of the National Lung Screening Trial finding of a 20% reduction in lung cancer mortality among smokers with annual low-dose CT (LDCT) screening [4]. As a result of the United States Preventive Services Task Force’s recommendation in favor of LDCT lung cancer screening for smokers and the CMS’s determination to provide LDCT as a covered service for at-risk smokers, LDCT lung cancer screening is now a covered service for many atrisk patients. The CMS coverage determination requires a prescreening visit with a qualified medical provider to confirm eligibility and to engage in counseling and shared clinical decision making to include a discussion of the risks and benefits of LDCT screening [5]. The CMS requirement states: “As part of the counseling and shared decision making visit, we are requiring that, among other things, shared decision making (including the use of one or more decision aids) includes information on benefits, harms, follow-up diagnostic testing, over-diagnosis, false positive rate and total radiation exposure” [5]. This requirement for shared decision making as a prerequisite to a screening examination represents a new step for CMS that reflects rising consumerism in US health care. ª 2016 American College of Radiology 1566 1546-1440/16/$36.00 n http://dx.doi.org/10.1016/j.jacr.2016.09.004 The decisions confronting smokers and patients with positive LDCT screening tests are complex. The balance of harms and benefits as patients navigate the complexities of short-term follow-up versus biopsy, risks and benefits of various biopsy and staging procedures, and benefits and harms of various surgical, chemotherapeutic, and radiation treatment options is extremely complex and difficult to model. Patient and caregiver preferences and concerns must be included in the decision to screen, diagnose, and treat lung cancer. Provider, patient, and caregiver biases can distort optimum outcomes. Patients considering LDCT lung cancer screening must learn the intricacies of prevalence, incidence, trueand false-positive findings, and true- and false-negative findings, and appreciate that for 1,000 LDCT-screened patients, 100 to 200 will have positive scans but only 10 to 20 will have lung cancer. Only a third of newly diagnosed lung cancers are expected to be curable. The question of over-diagnosis and unexpected and potentially clinically significant findings adds to the complexity and the challenge of fully informing patients and caregivers of the pros and cons of screening and follow-up testing. Decision support tools have been developed by the National Comprehensive Cancer Network [6] and the University of Michigan [7] to assist in shared clinical decision making. These tools assist in framing the basic concepts and manage the complex decisions implicit in choosing to screen and in choosing alternatives when navigating a positive screen finding. However, such decision aids are fundamentally reliant on the premise that with better information, patients will arrive at rational decisions that align with their preferences and values. Evidence from the field of behavioral economics offers many contrary viewpoints that take into account decision making biases on the part of both patients and providers and the role of the shared decision environment that can lead to flawed choices. For guidance in better understanding the role of biases and decision environments in shared decision making, and opportunities to intervene and improve lung cancer screening and treatment decisions, we turn to behavioral economics. BRIEF OVERVIEW OF BEHAVIORAL ECONOMICS Behavioral economics is a branch of economics that challenges the fundamental assumption that humans behave as fully informed and rational actors. Rather, behavioral economics, as a discipline, combines the fundamentals of economic theory with insights from psychology about the common biases that influence decision making. Behavioral economics understands decision making as a process with predictable biases [8]. Given the predictable nature of decision making biases, health policy can be crafted to anticipate and counteract biases to produce socially desirable outcomes. Health care has long been identified as a sector where the actors—patients, providers, and payers—fail to behave in a rational manner. As described in Irrationality in Health Care: What Behavioral Economics Reveals about What We Do and Why, many features of this market make it uniquely resistant to description via traditional economic models [9]. For example, owing to insurance, patients, the consumers of health care goods and services, pay for only a fraction of the services they consume with little salience to the cost of consumption [9]. Additionally, the price of services is unclear, and both patients and payers generally lack the ability to compare goods and services on the basis of value and price [9]. There is an inherent information bias in the consumption and selection of health services; patients must rely on providers to select the procedures and medications that are necessary [10]. Theories based on a rational decision maker fail to explain why people eat poorly when they do not want to be obese, or fail to take prescribed medication that they have gone to a physician to obtain [10]. Given the unique aspects of this market, individuals are particularly prone to irrationality and bias in decision making. Using behavioral economics to anticipate these “irrational” choices allows for the formulation of more realistic and effective policy [11]. Once policy is no longer predicated on a rational actor, possibilities emerge for novel approaches to delivering care, incentivizing health behavior, promoting evidence-based medicine, and communicating crucial health information [11,12]. Behavioral economics holds promise as a tool for designing the framework for health care choices—called “choice architecture.” By taking advantage of expected decision biases, individuals can be guided or “nudged” toward wiser choices without restricting choice freedom [8]. PATIENT BIASES AFFECTING MEDICAL DECISIONS Patients often make shared health decisions in collaboration with a health care provider. Frequently, multiple treatment options exist for a given condition and the Journal of the American College of Radiology Barnes, Groskaufmanis, Thomson n Behavioral Economics and Lung Cancer Screening Decisions 1567 provider and patient must reach a consensus about which option to pursue [13]. This is an inherently biased process, because the provider has unique expertise about the situation and is expected to use that expertise to guide the patient toward optimal treatment [13]. Behavioral economics has valuable explanatory power at the level of the individual actor. Among the individual actors, patients arguably have the greatest impact on health outcomes. Interactions with the health system and health care providers contribute to only a fraction of the overall health of an individual; lifestyle choices, which are largely under the control of the patient actor, are a major component of overall health. In 2010, for example, it was estimated that 42.7% of the cancers that occurred in Britain could be attributed to exposures owing to lifestyle factors, such as obesity, smoking, and exercise [14]. Powerfully, behavioral economics can be used to design choices that guide individuals toward healthier decisions without denying them the ability to choose less healthy alternatives [15,16]. By understanding the patient as a nonrational actor with predictable biases, it becomes easier to understand why individuals do not sign up to become organ donors even though they would like to [17], or why they fail to exercise when they would like to lose weight [18]. Policies that anticipate patient biases can be more effective in their efforts to promote healthier behavior. Some of the most well-documented biases of patient actors are presented below. Key biases of patient actors include the following: n n Loss aversion: People generally weigh losses more heavily than equivalent gains. Thus, patients will be likely to weigh the small cost of a preventive service (eg, getting the LDCT screen) more heavily than the benefits of avoiding a costly illness in the future [19]. Although patients face zero cost sharing for many preventive services under the Affordable Care Act, including a number of cancer screenings, the indirect costs of transportation and missed work time, among others, create perceived cost barriers to screening. Evidence from behavioral economics suggests that LDCT screening barriers could be mitigated if incentives were designed to reduce these barriers (eg, cover transportation costs or provide gift cards or lotteries to increase screening rates) [20]. Present bias: Individuals overly weigh the outcomes that occur in the present and overly discount the potential outcomes of the future. Thus, patients may be more likely to weigh the immediate challenges of 1568 n n n n undergoing a screening test—transportation, time off work, discomfort—more heavily than the long-term reduction in risk provided by the screening [21]. Framing effect: Framing is the expression of logically equivalent information in different ways. For example, negative lung cancer risk framing states that a patient has an 80% chance of dying, whereas positive framing states that the same patient has a 20% chance of survival. Patients respond more favorably to the same information, framed in a positive manner [22]. Empathy gaps: Empathy gaps occur when individuals make choices in a certain emotional state that they would not make in a different emotional state. For example, cigarette smokers who are not deprived of a cigarette underestimate the amount that they will be willing to pay for a cigarette after being deprived [23]. Such empathy gaps may bias patients’ lung cancer screening and treatment preferences in a shared decision making context. Shared decision making could, therefore, occur with a timing gap. The timing gap, as an evaluation tool, allows the patient to review the information and carefully consider the benefits and harms before acting. Reflection in an environment other than the doctor’s office, which may be an emotionally charged environment, could better align patient choices with desired outcomes. Mental accounting: Individuals value the same absolute amount differently, depending on the reference point. For example, a $10 discount on a $20 purchase will be viewed as less valuable than a $10 discount on a $10 purchase [24]. In the context of presenting lung cancer risks after LDCT screens, how the risks are framed affects patient risk perceptions and decision making. Framing can be a useful evaluation tool; it can emphasize either the benefits of screening or the harms of overtreatment [22]. Appropriate framing guidelines, available to radiologists, could serve as a valuable evaluation tool for patients considering LDCT. Decision fatigue: Choosing among large numbers of options is overwhelming. Paradoxically, individuals faced with more options are less likely to select options that satisfy their needs [25]. Thus, in shared decision making contexts, patients may quickly become cognitively overloaded when multiple treatment pathways are proposed, increasing the likelihood that they employ heuristics rather than systemic and analytic decision strategies. When faced with complex decisions, or a large number of options, individuals use mental shortcuts or “heuristics” to reach decisions. Journal of the American College of Radiology Volume 13 n Number 12PB n December 2016 n This is beneficial because it allows for maximization of efficiency, but overreliance can result in unintended outcomes [26]. Further, when faced with many options in a shared decision environment, patients may be more likely to experience decision regret [27]. Default bias: If a default decision is made for an individual, even if an individual is free to go against the default without consequences, the individual will be more likely to select this option [28]. Thus, even in shared decision making, patients’ ultimate choice will be sensitive to the screening or treatment option presented by the provider as the default. Shared decision making for LDCT could consider taking advantage of default bias by providers presenting a default option that maximizes benefits and minimizes risks. As argued by Purnell et al. [20], radiologists could advocate to nudge patients into LDCT screening appointments by leveraging EHR systems to schedule them automatically, and underserved populations that typically bear the brunt of disparities in access to cancer care and cancer outcomes may especially benefit from such behaviorally informed interventions. Creating such defaults can be used to nudge patients toward a more socially and personally beneficial outcome. However, any default screening or treatment option (including no treatment) should be frequently reevaluated as further research is produced and a more definitive scientific consensus is reached regarding the benefits and harms of the default versus alternative options. LOOKING AHEAD A crucial consideration when evaluating the role of behavioral economics is the ultimate power of choice architecture in crafting behavior. Proponents of libertarian paternalism argue that small interventions that incorporate the principles of behavioral economics, also known as “nudges,” can promote socially advantageous behavior through choice architecture, without reductions in freedom [8]. By taking advantage of typical biases of decision making that patients exhibit, architects can guide these decision makers towards choices that are in their (or society’s) best interest, without relying on mandates [23]. Behaviorally informed interventions may achieve the strongest gains in LDCT screening among underserved populations by alleviating barriers to understanding and evaluating screening and treatment options and accessing services. Such interventions will also be most effective among patients with a high degree of trust that their provider is indeed considering the patients’ best interests in any nudges given during screening decisions. Nevertheless, the limitations to behaviorally informed interventions must be considered. Many changes to the choice architecture, including defaults or other types of nudges, have been criticized for being overtly paternalistic. They might seem—rightly or wrongly—to manipulate patients into making lung cancer screening and treatment decisions that go against their wishes. This raises the ethics of intentionally using behavioral economics to “nudge” patients toward one decision over another and must be balanced with the principles of shared decision making put forward by medical professional societies and patient advocates. The behaviorally informed interventions presented in this paper may strike the right balance with ethicists when cancer screening decisions are steered toward improving patient health when unintentional patient decision making biases impede their ability to adequately obtain and process the information needed to make these decisions. Further, despite the best of intentions, providers might use behavioral economic tools such as defaults incorrectly, such as by nudging people toward screening and treatment decisions that would make patients worse off. Additionally, it is sometimes inefficient to solely take advantage of biases to change behavior. If a health issue is pressing or drastic enough, a combination of mandates and strong incentives must be used. For example, although the principles of behavioral economics should be used to craft smoking cessation interventions, high cigarette taxes or raising the minimum legal age to purchase will undoubtedly have a greater impact on smoking rates than carefully crafted cessation programs [29]. Looking forward, the increased utilization of electronic health records provides a new and exciting venue for interventions that help physicians and patients make appropriate choices in general, and regarding LDCT in particular. Electronic health records provide a novel mechanism for crafting choice architecture. Similarly, mobile health (mHealth) platforms provide opportunities to improve health decisions by leveraging actor-specific insights from behavioral economics. Knowledge of the inherent biases of decision making will allow for better design of systems that support less biased, more socially beneficial decisions. Conversely, inattention to potential biases could result in the creation of systems that reinforce these biases and facilitate poor choices. Overall, behavioral economics provides a useful tool for understanding the behavior of actors in the health Journal of the American College of Radiology Barnes, Groskaufmanis, Thomson n Behavioral Economics and Lung Cancer Screening Decisions 1569 system at a time of rapid change and can be a valuable tool set to incorporate into LDCT shared decisionmaking paradigms. Incorporating knowledge about patient biases into screening and treatment guidelines and shared decision making best practices increases the likelihood that such efforts will produce their desired objectives to improve survival and quality of life and place patients and families at the center of their health care decisions. TAKE-HOME POINTS - - - - Recent LDCT coverage policies require counseling and shared clinical decision making, including discussions of the risks and benefits of LDCT screening. Shared decision making fundamentally relies on the premise that with better information, patients will arrive at rational decisions that align with their preferences and values. Evidence from the field of behavioral economics suggests that patient decision making biases can lead to flawed choices. Nudges, among other behavioral economic interventions, can leverage patient biases to increase LDCT screening. ADDITIONAL RESOURCES Additional resources can be found online at: http://dx. doi.org/10.1016/j.jacr.2016.09.004. REFERENCES 1. National Cancer Institute. Surveillance, Epidemiology, and End Results program. Available at: http://seer.cancer.gov/statfacts/html/lungb. html. Accessed May 14, 2016. 2. Mariotto AB, Yabroff KR, Shao Y, Feuer EJ, Brown ML. Projections of the cost of cancer care in the United States: 2010-2020. J Natl Cancer Inst 2011;103:117-28. 3. Yabroff KR, Lund J, Kepka D, Mariotto A. Economic burden of cancer in the United States: estimates, projections, and future research. Cancer Epidemiol Biomarkers Prev 2011;20:2006-14. 4. National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409. 5. Jensen TS, Chin J, Ashby L, Hermansen J, Hutter JD. Decision memo for screening for lung cancer with low dose computed tomography (LDCT). Centers for Medicare and Medicaid Services, Baltimore, Maryland; 2015. CAG-00439N. 1570 6. National Comprehensive Cancer Network. Lung cancer screening. NCCN guidelines for patients version 1.2016. Available at: https://www. nccn.org/patients/guidelines/lung_screening/index.html#. Accessed May 16, 2016. 7. University of Michigan. Lung cancer CT screening. Should I get screened? 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Journal of the American College of Radiology Volume 13 n Number 12PB n December 2016