Cass R. Sunstein’s 2016 book The Ethics of Influence: Government in the Age of Behavioral Science provides an extremely informative introduction to the science and ethics of the exercise of “influence” over others. As a longtime physician employed in both the public and private sectors, I now recognize that most of my formal training has been in the hard sciences, with little, if any, training in the appropriate influence of the decision-making processes of my patients and/or other health care professionals in institutional settings. Breast cancer screening is an excellent example of the conflicts of modern medicine, highlighting our collective inability to effectively “nudge” others in the pursuit of health and/or organizational effectiveness and efficiency. Using the framework of Sunstein’s ethical values of welfare, autonomy, dignity, and self-government, I discuss many of the conflicting issues in a nationwide breast cancer screening program and the effects of these issues on client nudging to determine whether mammography screening is ethical.

Although much has been written about overdiagnosis in mammographical screening, analytical estimates of the extent of overdiagnosis are rare in the literature. Estimates specific to ductal carcinoma in situ (DCIS) and the implications for future invasive disease are even more difficult to find. In this paper, we review studies of incidence of DCIS within breast screening programmes and its association with subsequent incidence of invasive breast cancer. Although sparse, published results suggest that the majority of DCIS cases have the propensity to progress to invasive disease.

Objective: Economic evaluations such as cost-effectiveness and cost-utility analyses generally fail to incorporate elements of intangible costs and benefits, such as anxiety and discomfort associated with the screening test and diagnostic test, as well as the magnitude of utility associated with a reduction in the risk of dying from cancer. This paper seeks to include all costs and effects incurred by introducing mammography screening through the application of discrete ranking modeling.

Methods: In the present analysis, 207 women were interviewed and asked to rank, according to priority, a number of alternative breast cancer screening setups. The alternative programs varied with respect to number of tests performed, risk reduction obtained, probability of a false-positive outcome, and extent of copayment. Using discrete ranking modeling, the stated preferences were analyzed and the relative weighting of the program attributes identified. For a range of hypothetical breast cancer programs, relative utilities and corresponding willingness-to-pay estimates were derived.

Results: A comparison of cost and willingness to pay for each of the programs suggested that net benefits are maximized when screening person aged 50–74 years biennially. More intensive screening produces lower or similar levels of utility at a higher cost.

Conclusion: Discrete ranking modeling can aid decision making by identifying inferior healthcare programs, i.e., programs that are more costly but less beneficial.