设计多指标评分体系，让提升分数必然改善所有表现指标。
Score Design for Multi-Criteria Incentivization
- 构建双目标评分框架：升分必增全指标，最优分数对应最优指标
- 算法可证明在弱假设下生成维度最小的评分系统
- 适合医疗评级等需避免激励错配的现实场景
我们提出一种用于总结性能指标的评分设计框架。该设计包含两个多准则目标：(1) 评分提升应使所有性能指标均得到改善；(2) 达到帕累托最优评分时，也应实现帕累托最优的指标表现。我们通过最小化评分维度来满足上述目标，并给出了在性能指标结构满足温和假设下的评分设计算法，其结果可被严格证明为最小。该框架源于真实世界中医院评级系统的实践，其中评分与实际表现指标不一致会导致非预期后果。
原文摘要 · Abstract (English)
We present a framework for designing scores to summarize performance metrics. Our design has two multi-criteria objectives: (1) improving on scores should improve all performance metrics, and (2) achieving pareto-optimal scores should achieve pareto-optimal metrics. We formulate our design to minimize the dimensionality of scores while satisfying the objectives. We give algorithms to design scores, which are provably minimal under mild assumptions on the structure of performance metrics. This framework draws motivation from real-world practices in hospital rating systems, where misaligned scores and performance metrics lead to unintended consequences.
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