Singh, M. (2021). Heuristics in the delivery room. Science, 374(6565), 324-329.
Abstract: Clinical decisions made in the delivery setting are often made under high pressure, great uncertainty, and have serious consequences for mother and baby. Theories of decision-making suggest that individuals in such settings may resort to using “heuristics”, or simplified decision-rules, to aid complex decision-making. This study investigates whether physicians’ delivery-mode decisions (i.e., when to perform a vaginal vs. a cesarean) are influenced by such a heuristic. Electronic health record data spanning 86,000 deliveries suggests that, if the prior patient had complications in one delivery-mode, the physician will be more likely to switch to the other -- and likely inappropriate -- delivery-mode on the subsequent patient, regardless of patient indication. There is evidence that this heuristic has small, suboptimal effects on patient health.
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Racial Gaps in In-Hospital Mortality Increase with Hospital Strain (with Atheendar Venkataramani)
A growing literature has documented racial disparities in health outcomes. We argue that racial disparities may be magnified when hospitals operate at capacity, when conditions associated with poor patient outcomes (such as limited clinical resources and physician bandwidths) are aggravated. Using detailed, time-stamped electronic health record data from two major hospitals, we document a 20\% relative increase in mortality for Black compared to White patients as hospitals approach capacity, driven entirely by patients with more medical comorbidities. Put differently, 8.5\% of Black patient deaths in our sample could have been avoided if Black patients had experienced the same mortality-capacity relationship as White patients. Differential racial trends in patient selection or care intensity do not explain these results; in fact, Black patients generally receive less care (e.g., longer wait times, less intensive care, etc) than White patients at all levels of strain. Instead, this mortality gap is explained by racial differences in how patient characteristics and care inputs predict in-hospital mortality at high capacity strain - which may reflect unobserved racial differences in hospital processes, provider behavior, and returns to care.
Strained and Constrained: How ICU Capacity Affects Physician Decisions (with David Howard and Thomas Valley)
Limited ICU capacity has been said to exacerbate several consequences of COVID-19, such as mortality, misallocation of resources by physicians, and harmful spillovers on nonCOVID patients. However, whether greater ICU capacity would have avoided these pitfalls is not clear. The goal of this paper is to shed light on how ICU capacity affects physician decision-making and patient welfare when the healthcare system is strained. We use two sources of variation in ICU capacity to estimate its causal effect on physician thresholds for admitting patients to the ICU: i) ICU “expansions”, resulting from increases in hospital number of ICU beds, and ii) ICU “strain”, resulting from random fluctuations in ICU bed availability. Our analysis uses 100% inpatient EHR data from two hospitals (150K encounters. 2015-18) both of which expanded their ICUs separately. Importantly, we use lab test results to assign patients an objective and validated measure of ICU-need, called the eSOFA score. We motivate our empirical analyses using a model of physicians’ dynamic admission decisions when there is uncertainty about a patient’s ICU-need. Results show that increases in capacity cause physicians to lower their thresholds for ICU admission, with mixed effects on patient welfare. Patients are 1.8 pp more likely to be admitted to the ICU post-expansion (even when ICU strain is at pre-expansion levels), but there is significant heterogeneity in likelihood of admission and in-hospital mortality by ICU strain and ICU-need. Expanding ICU capacity does not always help the patients who need it most, and at times harms patients who need it least. Finally, the greatest benefits of ICU expansions accrue to patients in the general wards by allowing physicians to better allocate non-ICU resources, especially when the hospital is operating at capacity.
Who Benefits From Feedback? Evidence from a Surgeon Report Card (with Jacob Zureich)
In learning-by-doing tasks, feedback is often given to improve individual performance. However, it is unclear who feedback benefits more: the individuals who are already adept at learning-by-doing (“Learners”) or those who are less so (“Laggers”). Examining this question is important for designing feedback interventions that can reduce performance gaps and for explaining the lackluster effects of feedback interventions in the literature. Using the release of a nationwide Surgeon Report Card linked to 350,000 elective surgeries in the US, we find that providing feedback widens performance gaps amongst surgeons by making Learners better and Laggers worse, a difference that increases in the informativeness of the feedback. This result is replicated using a controlled online lab experiment. Further investigations of both settings reveal that this difference is due in part because Laggers (i) pay less attention to feedback, (ii) struggle with negative feedback in particular, and (iii) ineffectively adapt their learning strategies in response to the feedback. Thus, feedback can exacerbate performance disparities between Laggers and Learners rather than leveling the playing field. In follow-up experiments, we find that offering incentives based on improvements rather than just performance helps Laggers catch up to Learners, while providing additional feedback interpretation only solidifies the advantage of Learners. This suggests that the differences between Learners and Laggers are more likely driven by differences in motivation rather than ability.