What we talk about when we talk about risk: refining surgery's hazards in medical thought.

The high and rising costs of medical care in the United States (Bodenheimer 2005; Cutler, Rosen, and Vijan 2006), along with persistent regional variations in health services utilization (Fisher et al. 2003a, b; Wennberg 2010) have thrust to the fore the processes of medical decision making—particularly in regard to costly interventions with equivocal or poorly defined benefits—in efforts to restrain potentially wasteful medical spending (Neuman 2010). At the level of the doctor-patient encounter, efforts to increase the transparency of medical decisions and the extent to which treatment choices align with the preferences of individual patients have featured prominently in proposed policy strategies to control growth in medical spending. Such efforts are exemplified by shared decision-making strategies (Guadagnoli and Ward 1998) and tools such as structured decision aids, which seek to supplement discussions between clinicians and patients with information about the risks and benefits of treatment alternatives (Barry 2002; O’Connor, Llewellyn-Thomas, and Flood 2004; O’Connor et al. 2007). Calls for the more widespread use of tools such as patient decision aids imply that the mechanics of everyday medical decision making are flawed. Such calls bespeak a desire for more standardization of the processes by which practitioners and patients communicate “information on options, outcomes, probabilities, and scientific uncertainties,” and “the personal value or importance [that patients] place on benefits versus harms” of specific treatments (O’Connor, Llewellyn-Thomas, and Flood 2004, 64). As a result, they frame current patterns of health care use and spending as symptomatic of failed communication between physicians and patients on a large scale and assume that reforming such communication will yield a better, more sustainable pattern of health care utilization. While frequently acknowledging the uncertainties present in all medical choices, such efforts to improve the mechanics of medical decision making view the inputs to treatment choices, such as risks and benefits, as stably defined “outcomes and probabilities” waiting to be communicated (O’Connor, Llewellyn-Thomas, and Flood 2004). Yet in regard to the risks of medical treatments in particular, alternate viewpoints articulated over the last three decades have framed “risk” itself as a contingent, “collectively constructed” category and entity (Douglas and Wildavsky 1982; Slovic, Fischhoff, and Lichtenstein 1980). From this standpoint, the selection and definition of risks at any given moment in time are subject to specific, largely unseen and unappreciated cultural assumptions and biases (Heyman, Henriksen, and Maughan 1998; Slovic 1999). As a result, the way in which “risk” is defined in current medical practice carries its own set of implications for the personal, professional, and policy discourse that determines which patients are thought to be appropriate candidates for costly medical interventions, how this information is communicated between physicians and patients, and how physicians and third-party payers agree on “routine indications” for a given treatment. Past work in the sociology of medicine has shown that research and the evidence it produces are culturally shaped (De Vries and Lemmens 2006; De Vries, Lemmens, and Bosk 2008; Mol 2002). Nonetheless, the notion of risk as a subjective phenomenon challenges assumptions common to current medical thought and practice. For example, an excerpt from a recent textbook of surgery characterizes risk assessment as a straightforward, value-free exercise in measurement: “The aim of preoperative evaluation is … to identify and quantify comorbidity that may impact operative outcome” (Neumayer and Vargo 2008, 251–2). This text, like others in surgery, internal medicine, anesthesiology, and other disciplines, offers simple, statistically derived prediction rules to facilitate the process of risk quantification before surgery (Arozullah et al. 2000; Detsky et al. 1986; Goldman et al. 1977; Lee et al. 1999). This conceptualization of operative risk assessment contrasts sharply with the understanding of risk assessment evident in similar textbooks from just over four decades ago: The assessment of operative risk should be approached as a statistical problem. … However, the statistical approach demands accurate data pertaining to the effects of many factors such as age, starvation, heart disease, etc. … upon the operative risk. These are practically nonexistent. … Obviously, because of these factors the accurate assessment of the operative risk for an individual case is impossible today. All we can do is guess. (Moyer 1970, 232) Just how operative risk assessment changed from an enterprise perceived by physicians to be a matter of “guesswork” to one seen as a process of “quantification” represents an overlooked chapter in the history of medical thought. Past scholarship has demonstrated the emergence since the 1950s of the “risk factor” as a concept that has come to define the contemporary study, treatment, and experience of illness across a range of conditions by creating a status of being “at-risk” that coexists with states of “sick” and “well” (Aronowitz 1998, 2009; Rothstein 2003). Over this same period, an analogous terminology of risk factors also emerged in the context of decision making for surgical interventions. Drawing on analytic methods and concepts originating in epidemiologic studies of chronic disease, this new terminology came to be applied to, and in turn altered, the task of characterizing, categorizing, and making sense of the hazards of surgery. To gain perspective on how surgery's hazards have been defined and redefined in medical thought, we examine in detail here changes over time in notions of risk related to operative care. Choices to undertake surgery all involve, to a greater or lesser degree, an acceptance of implicit procedural hazards, making physicians’ assessments of the dangers of treatment to an individual a central element of decision making surrounding surgical procedures (Bosk 1979). Accordingly, we studied writings from the years surrounding the 1977 publication of the first major statistical “risk factor” system focused on predicting a subset of adverse surgical outcomes, the Cardiac Risk Index (Goldman et al. 1977). We traced how the rapid appearance of this index in academic and clinical surgical writings, along with the development of similar statistical models to predict a range of other postoperative outcomes, offered physicians an increasingly standardized and statistically grounded way to assess the risks of surgery in individual patients. Taking the widespread acceptance of probabilistic statements regarding surgery's specific risks as a development to be explained rather than as a simple step forward for medical science (Berg 1995; Hacking 1990), we follow in this article Douglas and Wildavsky's admonition that “what needs to be explained is how people agree to ignore most of the potential dangers that surround them and interact so as to concentrate only on certain aspects” (Douglas and Wildavsky 1982, 9). We explain how the adoption of a new way of assessing the likelihood of a specific type of negative outcome—postoperative cardiac complications—implied a focus on certain dangers of surgery and the relative neglect of others while simultaneously obscuring the subjective nature of risk assessment itself. Further, we look at how such an approach to risk assessment created distinct challenges to cost-effective decision making by physicians and patients that remains beyond the reach of probabilistic rules, statistical guidelines, and applicable decision-making tools.