Global Health

Natarajan, Karthik; Swaminathan, Jayashankar M.

doi:10.1002/9781119300977.ch7

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…One such application is, for example, in healthcare. In [14], it is suggested that healthcare interventions such as reducing infection spread or slowing disease progression rate may modify the optimal strategies for constrained resource allocation. This connects to the explorationexploitation trade-off discussed in Subsection 3.2 of this paper.…”

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confidence: 99%

Online Learning and Matching for Resource Allocation Problems

Chen¹

2020

SIURO

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In order for an e-commerce platform to maximize its revenue, it must recommend customers items they are most likely to purchase. However, the company often has business constraints on these items, such as the number of each item in stock. In this work, our goal is to recommend items to users as they arrive on a webpage sequentially, in an online manner, in order to maximize reward for a company, but also satisfy budget constraints. We first approach the simpler online problem in which the customers arrive as a stationary Poisson process, and present an integrated algorithm that performs online optimization and online learning together. We then make the model more complicated but more realistic, treating the arrival processes as non-stationary Poisson processes. To deal with heterogeneous customer arrivals, we propose a time segmentation algorithm that converts a non-stationary problem into a series of stationary problems. Experiments conducted on large-scale synthetic data demonstrate the effectiveness and efficiency of our proposed approaches on solving constrained resource allocation problems.

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Online Learning and Matching for Resource Allocation Problems

Chen¹

2020

SIURO

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Role of Donors in Global Health Supply Chains

Berenguer

Rashkova²

2021

Springer Series in Supply Chain Management

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Impact of Physician Payment Scheme on Diagnostic Effort and Testing

Adida,

Dai

2024

Management Science

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Diagnostic errors are common and can result in serious patient harm. Making the right diagnosis often requires significant diagnostic effort. Yet most physician payment schemes are procedure based and do not account for diagnostic effort or accuracy because of observability issues. In this paper, we develop a parsimonious model to examine the impact of a physician payment scheme on a physician’s decisions to (1) exert diagnostic effort and (2) perform a confirmatory test. High effort provides an informative (though imperfect) signal of the patient’s true state; the test is confirmatory in that it is a prerequisite for diagnosing a severe condition. Our model uses a two-step diagnostic process to capture the interaction between the physician’s diagnostic effort and testing decisions. We show that under a fee-for-service payment scheme, the physician may view the diagnostic effort and the confirmatory test as either complementary or substitutive, depending on the additional revenue from testing. We also reveal nonmonotonic properties such that a more patient-centered physician may not exert more effort or provide a more accurate diagnosis. In addition, either a flat or differentiated payment scheme may be optimal. We also show that an alternative payment scheme, under which the revenue from the confirmatory test is contingent on its result, can induce the social optimum under certain conditions. With the advent of artificial intelligence as part of the standard of care and its increasing use as confirmatory tests, our research has implications for the design of physician payment systems in light of concerns about the potential erosion of individual attention. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: T. Dai was supported by the Johns Hopkins Discovery Award (2022–2024) and the Hopkins Business of Health Initiative Seed Grant (2022–2023). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4937 .

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Global Health

Cited by 5 publications

References 25 publications

Online Learning and Matching for Resource Allocation Problems

Online Learning and Matching for Resource Allocation Problems

Role of Donors in Global Health Supply Chains

Impact of Physician Payment Scheme on Diagnostic Effort and Testing

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