The Legacy of Peter Fishburn: Foundational Work and Lasting Impact

Peter Fishburn has had a tremendous impact on the field of decision analysis, developing ideas that would come to be foundational across decision analysis and that would impact the literature on decision making in economics, psychology, finance, engineering, and mathematics. This paper provides an overview of his legacy. We summarize 11 of his influential papers. We then trace his impact on recent research in topics including preference representation and elicitation, risk attitudes, time preferences, health preferences, behavioral decision making, social choice and voting, and geometric analyses.

Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2022.0461 .

Balanced Opioid Prescribing via a Clinical Trade-Off: Pain Relief vs. Adverse Effects of Discomfort, Dependence, and Tolerance/Hypersensitivity

In the backdrop of the opioid epidemic, opioid prescribing has distinct medical and social challenges. Overprescribing contributes to the ongoing opioid epidemic, whereas underprescribing yields inadequate pain relief. Moreover, opioids have serious adverse effects including tolerance and increased sensitivity to pain, paradoxically inducing more pain. Prescribing trade-offs are recognized but not modeled in the literature. We study the prescribing decisions for chronic, acute, and persistent pain types to minimize the cumulative pain that incorporates opioid adverse effects (discomfort and dependence) and the risk of tolerance or hypersensitivity (THS) developed with opioid use. After finding closed-form solutions for each pain type, we analytically investigate the sensitivity of acute pain prescriptions and examine policies on incorporation of THS, patient handover, and adaptive treatments. Our analyses show that the role of adverse effects in prescribing decisions is as critical as that of the pain level. Interestingly, we find that the optimal prescription duration is not necessarily increasing with the recovery time. We show that not incorporating THS or information curtailment at patient handovers leads to overprescribing that can be mitigated by adaptive treatments. Last, using real-life pain and opioid use data from two sources, we estimate THS parameters and discuss the proximity of our model to clinical practice. This paper has a pain management framework that leads to tractable models. These models can potentially support balanced opioid prescribing after their validation in a clinical setting. Then, they can be helpful to policy makers in assessment of prescription policies and of the controversy around over- and underprescribing.

On (Measurable) Multiattribute Value Functions: An Expository Argument

In this note, we provide an easy-to-understand introduction to strength-of-preference measures in the context of deterministic multiattribute value assessments, focusing on what they are and why they matter. Though these issues are well understood by some decision analysts, we believe that many do not understand or appreciate the role of strength-of-preference assumptions when assessing or interpreting multiattribute value functions. The note is structured around an argument between the two authors that took place when reviewing applications of multiattribute value functions.

Microfoundations of Discounting

An important question in economics is how people choose between different payments in the future. The classical normative model predicts that a decision maker discounts a later payment relative to an earlier one by an exponential function of the time between them. Descriptive models use nonexponential functions to fit observed behavioral phenomena, such as preference reversal. Here we propose a model of discounting, consistent with standard axioms of choice, in which decision makers maximize the growth rate of their wealth. Four specifications of the model produce four forms of discounting—no discounting, exponential discounting, hyperbolic discounting, and a hybrid of exponential and hyperbolic discounting—two of which predict preference reversal. Our model requires no assumption of behavioral bias or payment risk.

Cost-effectiveness Analysis of Preoperative Screening Strategies for Obstructive Sleep Apnea among Patients Undergoing Elective Inpatient Surgery

Background

Obstructive sleep apnea is underdiagnosed in surgical patients. The cost-effectiveness of obstructive sleep apnea screening is unknown. This study’s objective was to evaluate the cost-effectiveness of preoperative obstructive sleep apnea screening (1) perioperatively and (2) including patients’ remaining lifespans.

Methods

An individual-level Markov model was constructed to simulate the perioperative period and lifespan of patients undergoing inpatient elective surgery. Costs (2016 Canadian dollars) were calculated from the hospital perspective in a single-payer health system. Remaining model parameters were derived from a structured literature search. Candidate strategies included: (1) no screening; (2) STOP-Bang questionnaire alone; (3) STOP-Bang followed by polysomnography (STOP-Bang + polysomnography); and (4) STOP-Bang followed by portable monitor (STOP-Bang + portable monitor). Screen-positive patients (based on STOP-Bang cutoff of at least 3) received postoperative treatment modifications and expedited definitive testing. Effectiveness was expressed as quality-adjusted life month in the perioperative analyses and quality-adjusted life years in the lifetime analyses. The primary outcome was the incremental cost-effectiveness ratio.

Results

In perioperative and lifetime analyses, no screening was least costly and least effective. STOP-Bang + polysomnography was the most effective strategy and was more cost-effective than both STOP-Bang + portable monitor and STOP-Bang alone in both analyses. In perioperative analyses, STOP-Bang + polysomnography was not cost-effective compared to no screening at the $4,167/quality-adjusted life month threshold (incremental cost-effectiveness ratio $52,888/quality-adjusted life month). No screening was favored in more than 90% of iterations in probabilistic sensitivity analyses. In contrast, in lifetime analyses, STOP-Bang + polysomnography was favored compared to no screening at the $50,000/quality-adjusted life year threshold (incremental cost-effectiveness ratio $2,044/quality-adjusted life year). STOP-Bang + polysomnography was favored in most iterations at thresholds above $2,000/quality-adjusted life year in probabilistic sensitivity analyses.

Conclusions

The cost-effectiveness of preoperative obstructive sleep apnea screening differs depending on time horizon. Preoperative screening with STOP-Bang followed by immediate confirmatory testing with polysomnography is cost-effective on the lifetime horizon but not the perioperative horizon. The integration of preoperative screening based on STOP-Bang and polysomnography is a cost-effective means of mitigating the long-term disease burden of obstructive sleep apnea.

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