AI在医疗中应优先解决协调成本,而非单纯自动化。
Healthcare AI for Automation or Allocation? A Transaction Cost Economics Framework
- 按任务粒度分析医护工作,用大模型分类为四类协调成本
- 医生角色协调成本远高于非医护,主因信息搜索与决策协调
- 数字干预机会不均,取决于协调结构而非技术难度
医疗生产率不仅受临床复杂性影响,更受不确定性下协调工作成本制约。交易成本经济学可解释此类协调摩擦,但极少在职业任务层面应用。本研究利用O*NET职业数据库中的任务描述与频次权重,将医疗工作细化至任务层级,通过约束型大语言模型将每个任务归入四大交易成本类别之一(信息搜寻、决策与谈判、监控与执行、适应与协调),并生成整体交易成本强度评分。聚合至职业层面发现,临床人员的交易成本强度显著高于非临床人员,主要源于更高的信息搜寻与决策协调负担,而各职业内部的交易成本分布差异不大。结果表明,不同医疗角色间的协调工作存在系统性异质性,提示数字与AI干预机会分布不均,其关键不在于技术复杂度,而在于深层协调结构。
原文摘要 · Abstract (English)
Healthcare productivity is shaped not only by clinical complexity but by the costs of coordinating work under uncertainty. Transaction-cost economics offers a theory of these coordination frictions, yet has rarely been operationalised at task level across health occupations. Using task statements and frequency weights from the O*NET occupational database, we characterised healthcare work at task granularity and coded each unique task using a constrained large language model into one dominant transaction-cost category (information search, decision and bargaining, monitoring and enforcement, or adaptation and coordination) together with an overall transaction-cost intensity score. Aggregating to the occupation level, clinician roles exhibited substantially higher transaction-cost intensity than non-clinician roles, driven primarily by greater burdens of information search and decision-related coordination, while dispersion of transaction costs within occupations did not differ. These findings demonstrate systematic heterogeneity in the nature of coordination work across healthcare roles and suggest that the opportunities for digital and AI interventions are unevenly distributed, shaped less by technical task complexity than by underlying coordination structure.
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