Bias control in shared decision-making: still too many loose ends
13 November 2012
Mulley and cols. present a compelling description, somehow prescriptive, of the steps to foster shared decision-making. The relevance of SDM to quality of care is not under debate. Still it is not clear how to minimize the potential impact of the many factors, both external (noise) and those inherent to the stakeholders (biases) that influences the complexity of the task.[2,3] How to counteract these biases while respecting patient preferences and values?
In contexts where the probability of facing undifferentiated problems is higher, like in the primary care setting, the correct evaluation of patient’s preferences is even more challenging. Because the diagnostic landscape is broader, to diagnose patient’s preferences require the consideration of multiple trade-offs between benefits and risks. The inherent biases caused by the framing of the information, how and how many options are presented, overconfidence of clinicians, and the likeness of the options, are always in play.[5,6]
Uncertainty, error and regret are inherent to every decision we made. Then what is an acceptable burden of regret when the outcomes of our decisions do not match our expectations? Physicians and patients must learn how to deal with uncertainty and regret, and be comfortable with it to avoid an unnecessary increase in their decision thresholds.
How to distinguish between “preference misdiagnosis” from hindsight bias, attribution error, and regret based on the outcome of the decision? One the authors proposed three years ago that “decisions cannot be measured by reference to their outcomes” and propose to “emphasize the deliberation process rather than the decisions end results.”
Instead of a straightforward step-by-step process, shared decision-making must be seen as a spiral and constant comparison process. Where patient’s ideas, concerns and expectations around his/her problems, are constantly weighted and compared against the professional’s own ideas concerns and expectations, within the boundaries imposed by the published evidence, the context, and our biased nature.
1. Mulley a. G, Trimble C, Elwyn G. Stop the silent misdiagnosis: patients’ preferences matter. BMJ 2012;345:e6572–e6572.
2. Epstein RM, Alper BS, Quill TE. Communicating evidence for participatory decision making. JAMA 2004;291:2359–66.
3. Edwards M, Davies M, Edwards A. What are the external influences on information exchange and shared decision-making in healthcare consultations: a meta-synthesis of the literature. Patient education and counseling 2009;75:37–52.
4. Pinto J, Abellán J, Sánchez F. La incorporación de las preferencias de los pacientes en las decisiones clínicas. Barcelona: Masson 2004.
5. Tversky A, Kahneman D. The framing of decisions and the psychology of choice. Science 1981;211:453–8.
6. Gigerenzer G. Why does framing influence judgment? Journal of general internal medicine 2003;18:960–1.
7. Tsalatsanis A, Hozo I, Vickers A, et al. A regret theory approach to decision curve analysis: a novel method for eliciting decision makers’ preferences and decision-making. BMC medical informatics and decision making 2010;10:51.
8. Henriksen K, Kaplan H. Hindsight bias, outcome knowledge and adaptive learning. Quality & safety in health care 2003;12 Suppl 2:ii46–50.
9. Elwyn G, Miron-Shatz T. Deliberation before determination: the definition and evaluation of good decision making. Health expectations 2010;13:139–47.
Competing interests: None declared
University of Antwerpen, Universiteitsplein 1, Wilrijk 2610, Belgium
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