If doctors use heuristics to guide delivery decisions, the effects may be suboptimal

If a prior patient had complications in one childbirth delivery mode, a physician may be more likely to switch to the other—and likely inappropriate—delivery mode for the subsequent patient, a new study shows. It reports that the use of “heuristics,” or simplified decision rules, by these physicians may lead to small but suboptimal effects on patient health. The rate of maternal mortality and morbidity in the United States has been steadily increasing; understanding how physicians make delivery decisions, to improve patient health outcomes, is critical. Doctors are routinely required to evaluate complex information when determining the best clinical decisions for their patients. This is particularly true during childbirth. Theories of decision-making suggest that humans making decisions frequently rely on heuristics – mental shortcuts that allow people to solve problems and/or make judgments quickly and efficiently. While this behavior is efficient, heuristics can lead to making suboptimal decisions. The potential risks of decision biases in clinical settings aren’t well studied. Here, Manasvini Singh investigated whether a physician’s decision on delivery-mode during childbirth – vaginal versus cesarian – is influenced by a “win-stay/lose-shift” heuristic, according to which the decision-maker either switches strategies if the last outcome was a “loss” or continues with the same strategy if the last outcome was a “win.” Using a dataset spanning more than 86,000 childbirths by 231 physicians, Singh found that when patients experience a complication during childbirth through one delivery method, their doctors are slightly more likely to switch to the opposite delivery method for their next patient’s birth (3.4% more likely to switch to vaginal delivery if complications with a cesarean, and 3.6% more likely to switch to cesarean, if complications with vaginal delivery). “It is time to acknowledge the prevalence of heuristics and decision biases in clinical practice and to view these patterns as predictably human instead of blaming individual doctors,” write Meng Li and Helen Colby in a related Perspective. “Only then can we start helping doctors improve clinical decisions and, as a result, the health of the public.”