Abstract
Objective
Regret is a powerful motivating factor in medical decision making among patients and surgeons. Regret can be particularly important for surgical decisions, which often carry significant risk and may have uncertain outcomes. We performed a systematic review of the literature focused on patient and physician regret in the surgical setting.
Methods
A search of the English literature between 1986 and 2016 that examined patient and physician self-reported decisional regret was carried out using the MEDLINE/PubMed and Web of Science databases. Clinical studies performed in patients and physicians participating in elective surgical treatment were included.
Results
Of 889 studies identified, 73 patient studies and 6 physician studies met inclusion criteria. Among the 73 patient studies, 57.5% examined patients with a cancer diagnosis, with breast (26.0%) and prostate (28.8%) cancers being most common. Interestingly, self-reported patient regret was relatively uncommon with an average prevalence across studies of 14.4%. Factors most often associated with regret included type of surgery, disease-specific quality of life, and shared decision making. Only 6 studies were identified that focused on physician regret; 2 pertained to surgical decision making. These studies primarily measured regret of omission and commission using hypothetical case scenarios and used the results to develop decision curve analysis tools.
Conclusion
Self-reported decisional regret was present in about 1 in 7 surgical patients. Factors associated with regret were both patient- and procedure related. While most studies focused on patient regret, little data exist on how physician regret affects shared decision making.
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Wilson, A., Ronnekleiv-Kelly, S.M. & Pawlik, T.M. Regret in Surgical Decision Making: A Systematic Review of Patient and Physician Perspectives. World J Surg 41, 1454–1465 (2017). https://doi.org/10.1007/s00268-017-3895-9
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Keywords
- Radical Prostatectomy
- Biliary Tract Cancer
- Anticipate Regret
- Decisional Regret
- Decision Curve Analysis