Plastic surgeon expertise in predicting breast reconstruction outcomes for patient decision analysis

Given that a woman can be a candidate for multiple medically appropriate methods of breast reconstruction, making a decision on which method to pursue can be a difficult one.1 Normative decision-making is a framework that could be used to help women make difficult decisions about breast reconstruction. Normative decision-making is an exhaustive, iterative process that involves identifying alternatives, obtaining information about the uncertainty of the outcomes, and clarifying preferences and values.2–4 For the case of breast reconstruction, the alternatives, that is, different reconstruction procedures, are very well understood.1,5,6 However, information about the uncertainties of the outcomes (eg, number of revisions needed, chances of experiencing a complication, or the final aesthetic result) is more difficult to obtain because large quantities of data may not exist for uncommon procedures or rare patient profiles. Clarifying preferences and values about breast reconstruction is also challenging7–9; however, the focus of this study is on the difficulty of estimating the probabilities of reconstruction outcomes. Such probabilities may be employed by future computational decision support systems to aid in patient decision-making and may make use of surgeon predictions obtained before system deployment. In the clinical decision-making literature, it is suggested that, in the absence of large quantities of data, probabilities of outcomes can be estimated by experts,10–12 that is, plastic surgeons in the case of breast reconstruction. Of course, estimating probabilities about breast reconstruction outcomes is difficult because there are numerous variables involved. Moreover, to provide the information needed for decision support, plastic surgeons must be able to estimate outcome probabilities in general, not simply for their own patients. However, we are unaware of any prior studies that address the validity of expert-elicited probabilities about breast reconstruction outcomes. The clinical impact of this study is in the context of a future computational decision support system for shared breast reconstruction decision-making. Such systems require patient-specific probability information that surgeons may provide. The goal of this study was to investigate to what extent plastic surgeons can predict breast reconstruction outcomes. The purpose of the system is to inform both the patient and the surgeon of risk and help them make better decisions regarding breast reconstruction.