Health Care Costs: How Do We Decide Value? When Do We Decide? How Do We Particularize the Decisions?

How do oncologists and patients make heath care decisions? Do we use a “shared decision-making” model? Has paternalism become a thing of the past? Do we rely on the latest randomized trial data and then apply it in the same way that the trial eligibility criteria were determined? When we counsel someone about cancer care (screening, prevention, and treatment), do we include financial risks in the discussion? Costs for cancer care are rising throughout the world. This is especially noted in high-income countries [1]. Contributors to increasing costs include demographic, technological, regulatory, industrial, and governmental factors as well as individual patient and physician behaviors. Lack of knowledge of “costs” and limited reporting of “true” benefits of medical care are impediments to meaningful discussions of providing individual care and reforming health care. Individual and societal expectations are also driving the “cost curve” of health care. Financial considerations, overuse, for example, are perceived to be placing more pressure on the practice of medicine in the U.S. than in the past. Costs of new treatment development through the clinical trial process, individual and group expenditures, and public/governmental monetary outlays for cancer treatment drugs continue to rise. The research focus on “targeted therapy,” like trastuzumab, and personalized cancer treatment based on the molecular characteristics of an individual’s cancer may also increase the costs of new treatment development and patient care. There is a great deal of angst regarding the future of medicine and the care of the sick based on the perception that we will not be able to afford care. The recent emphasis on “endof-life” care has precipitated worry of “rationing,” an act undertaken by policy makers, and financial means testing for medical care. Reports of personal bankruptcy resulting from critical or life-threatening medical illnesses fill the news [2]. There is also a perception of inequality in access and distribution of health interventions known to be of value, not rationing but an access to care concern and a distributive justice issue nonetheless. It is incumbent on the oncology community that we discuss, review, and assess the best means of providing care for the benefit of all citizens. The costs of cancer care have been the subject of ethical review, and the question has been asked: “How much is life worth?” [3] Evidence-based medicine, based on analysis of randomized controlled trials (RCTs), and comparative effectiveness research provide two methods that have been proposed to assist in decision making for health care. Whereas evidence-based medicine has, as a component, the patient’s values and participation in the decision, comparative effectiveness research (CER) does not “particularize” an individual treatment decision. CER is defined as “the generation and synthesis of evidence that compares the benefits and harms of alternative methods to prevent, diagnose, treat, and monitor a clinical condition, or to improve the delivery of care.” This is intended to provide assistance in health care decisions for the public, policy makers, and individuals with the goal of improving health care [4]. Other clinical decision aids, such as number needed to treat and number needed to harm, and clinical efficacy reports from RCTs have their proponents. It has been suggested that RCTs lack the necessary details for use in clinical practice [5]. Each method has supporters and detractors and no “surefire” best method is available to practicing physicians and patients to aid in clinical decision making. Countries such as the U.K. have developed formal processes for the evaluation of technologies and drug therapies to guide health care financial coverage decisions. The U.K. National Institute for Clinical Excellence provides an explicit methodology for analysis of technologies and therapeutics and includes cost-effective analysis (CEA) in the process. This method uses decision analysis methodology and data from RCTs to reach a decision on the relative benefits and costs of interventions. The