| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w26168 |
| 来源ID | Working Paper 26168 |
| Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care | |
| Sendhil Mullainathan; Ziad Obermeyer | |
| 发表日期 | 2019-08-19 |
| 出版年 | 2019 |
| 语种 | 英语 |
| 摘要 | How effective are physicians at diagnosing heart attacks? To answer this question, we contrast physician testing decisions with a machine learning model of risk. When the two deviate, we use actual health outcome data to judge whether the algorithm or the physician was right. We find physicians over-test: tests that are predictably useless are still performed. At the same time, physicians also under-test: many predicted high-risk patients are untested and then suffer adverse health events (including death) at high rates. A natural experiment using shift-to-shift testing variation confirms these findings: increasing testing improves health and reduces mortality, but only for patients flagged as high-risk by the algorithm. The simultaneous existence of over- and under-testing cannot easily be explained by incentives alone, and instead suggests errors. We provide suggestive evidence on the psychology behind these errors: (i) physicians use too simple a model of risk, suggesting bounded rationality; (ii) they over-weight salient information; and (iii) they over-weight symptoms that are representative or stereotypical of heart attack. Together, these results suggest the need for health care models and policies to incorporate not just physician incentives, but also physician mistakes. |
| 主题 | Econometrics ; Estimation Methods ; Microeconomics ; Economics of Information ; Behavioral Economics ; Health, Education, and Welfare ; Health |
| URL | https://www.nber.org/papers/w26168 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/583842 |
| 推荐引用方式 GB/T 7714 | Sendhil Mullainathan,Ziad Obermeyer. Diagnosing Physician Error: A Machine Learning Approach to Low-Value Health Care. 2019. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w26168.pdf（765KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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