Singh, M. (2021). Heuristics in the delivery room. Science, 374(6565), 324-329.
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.
Results as a limerick
A patient has a bad reaction,
To the Doc’s deep dissatisfaction,
Doc cries out, "Oh sh*t!"
And switches her medical plan of action.
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Capacity Strain and Racial Disparities in Hospital Mortality (with Atheendar Venkataramani) (Revisions requested at Nature Communications)
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.
Results as a limerick
Behavioral Responses to Surgeon Report Cards (with Jacob Zureich) (Revisions requested at Management Science)
Feedback interventions such as report cards are often used in healthcare to encourage physicians to improve performance. However, providing feedback is tricky because it often conveys negative information to individuals about their performance, which can induce behavioral responses (e.g., dejection, confusion, attributional errors, etc) that interfere with learning and improvement. In this paper, we use novel data from a surgeon report card (linked to 320,000 surgeries) to examine surgeon response to positive vs. negative feedback, and to identify which surgeons improve most from such feedback. Exploiting two sources of plausibly exogenous variation in report card information, we highlight two results: i) consistent with behavioral responses to feedback, patient outcomes improve for surgeons receiving positive feedback and deteriorate for those receiving negative feedback, and ii) the largest returns to the feedback accrue to those already skilled at learning from experience ex-ante (i.e., the inframarginal physician) because they respond more effectively to both positive and negative feedback. These results are replicated in the lab, where we explore mechanisms and test interventions to attenuate suboptimal behavioral responses, such as providing help interpreting feedback and adding improvement-based incentives. Overall, report cards should be carefully designed to avoid triggering counterproductive behavioral responses to negative feedback.
Results as a limerick
Power Dynamics in the Doctor-Patient Relationship (with Steve Schwab)
Power, broadly defined as the asymmetric control of resources, affects nearly all individual decision-making. Yet there is little observational evidence on how power affects real-world behavior and resource allocation. Understanding such power dynamics is especially important in healthcare, where “powerful” physicians make decisions for patients in highly asymmetric information environments. To examine this question, we exploit the plausibly exogenous assignment of patients to physicians in US military hospital emergency departments. Using the difference in military ranks between doctor and patient as a proxy for the power imbalance between them, we show that physician effort and resource use increases with the patient’s relative seniority. Furthermore, within-physician effort is significantly less for patients about to be promoted vs those recently promoted to a given rank. This additional care does not map onto better patient outcomes (30-day ED or inpatient readmission) for higher-ranked patients. We document other interesting effects such as the “power spillover”: when a physician attends to a higher-ranked patient, they concurrently decrease effort for their lower-ranked patients. Taken together, we conclude that the magnitude of the power imbalance in the doctor-patient relationship nontrivially affects patient care, and should be especially considered when making critical clinical decisions for vulnerable patients.
Results as a limerick
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.