Healthcare Mechanisms from Policy-as-Code Search under Strategic Provider Response
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arXiv:2605.30680v1 Announce Type: new Abstract: Healthcare mechanisms are inseparable from the strategic provider response they induce: existing healthcare AI benchmarks hold this response fixed and so cannot evaluate mechanisms by the equilibrium they produce. We recast hospital mechanism design as program synthesis for language models: typed, inspectable rule programs are executed and scored by Medi-Sim, a multi-agent simulator with five strategic provider channels (coding, selection, delay, e
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✦ AI Summary· Claude Sonnet
Computer Science > Artificial Intelligence
[Submitted on 29 May 2026]
Healthcare Mechanisms from Policy-as-Code Search under Strategic Provider Response
Zihan Wang, Xiang Xu, Hongyuan Zha, Wenhao Li
Healthcare mechanisms are inseparable from the strategic provider response they induce: existing healthcare AI benchmarks hold this response fixed and so cannot evaluate mechanisms by the equilibrium they produce. We recast hospital mechanism design as program synthesis for language models: typed, inspectable rule programs are executed and scored by Medi-Sim, a multi-agent simulator with five strategic provider channels (coding, selection, delay, effort, triage). An incentive sweep recovers classical health-economics findings as adjacent regimes -- up-coding and low-complexity-patient selection under profit pressure, and Goodhart-style drift where measured performance becomes anti-correlated with true outcomes -- and a single audit lever exposes pressure migration: closing the coding channel more than doubles low-complexity selection. LLM-guided evolutionary code search over the same rule-program space then synthesizes an inspectable mixed-objective program that eliminates up-coding, halves rejection, and retains most of the profit-oriented baseline's funds.
Comments: 32 pages, 18 figures, 4 tables
Subjects: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)
Cite as: arXiv:2605.30680 [cs.AI]
(or arXiv:2605.30680v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2605.30680
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Submission history
From: Wenhao Li [view email]
[v1] Fri, 29 May 2026 00:21:54 UTC (4,753 KB)
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