Heuristics in the Delivery Room
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.
STATUS: Accepted at Science
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.
Learning-by-Doing in MTurkers and Surgeons: The Effect of Feedback on Performance Gaps (with Jacob Zureich)
Learning-by-doing is an important driver of individual and societal success. However, attempts to hasten learning are limited by the fact that some individuals are inherently slower learners, which impedes performance maximization. In this study, we examine whether giving better outcome-based feedback can help boost the performance of these slow learners ("Laggers) and allow them to catch up to fast learners ("Learners"). Evidence from both a controlled online experiment and a surgeon report card linked to over a million inpatient encounters shows that, perhaps counter-intuitively, feedback widens performance gaps between Learners and Laggers. In particular, feedback increases performance for Learners and decreases performance for Laggers. 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 explore-exploit strategies in response to the feedback. Thus outcome feedback may exacerbate performance disparities between Laggers and Learners rather than leveling the playing field. Future interventions to target Laggers may need to supplement outcome feedback with additional information, such as individualized attention or enhanced feedback interpretation.
STATUS: Under Review
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