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临床试验/NCT06208423
NCT06208423招募中不适用

Management Reasoning With AI Chat Bots

Stanford University2 个研究点 分布在 1 个国家目标入组 50 人开始时间: 2023年12月28日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
招募中
入组人数
50
试验地点
2
主要终点
Management Reasoning

研究概览

简要总结

This study will evaluate the effect of providing access to GPT-4, a large language model, compared to traditional management decision support tools on performance on case-based management reasoning tasks.

详细描述

Artificial intelligence (AI) technologies, specifically advanced large language models like OpenAI's ChatGPT, have the potential to improve medical decision-making. Although ChatGPT-4 was not developed for its use in medical-specific applications, it has demonstrated promise in various healthcare contexts, including medical note-writing, addressing patient inquiries, and facilitating medical consultation. However, little is known about how ChatGPT augments the clinical reasoning abilities of clinicians.

Clinical reasoning is a complex process involving pattern recognition, knowledge application, and probabilistic reasoning. Integrating AI tools like ChatGPT-4 into physician workflows could potentially help reduce clinician workload and decrease the likelihood of mismanagement. However, ChatGPT-4 was not developed for clinical reasoning nor has it been validated for this purpose. Further, it may be subject to disinformation, including convincing confabulations that may mislead clinicians. If clinicians misuse this tool, it may not improve reasoning and could even cause harm. Therefore, it is important to study how clinicians use large language models to augment clinical reasoning prior to routine incorporation into patient care.

In this study, participants will be randomized to answer clinical management cases with or without access to ChatGPT-4. Each case has multiple components, and the participants will be asked to discuss their reasoning for each component. Answers will be graded by independent reviewers blinded to treatment assignment. A grading rubric was developed for each case by a panel of 4-7 expert discussants. Discussants independently developed a rubric for each case, and then any discrepancies were resolved through multiple rounds of discussions.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Treatment
盲法
Single (Outcomes Assessor)

盲法说明

The grading of responses will be performed by assessors blinded to participant identity and treatment assignment.

入排标准

性别
All
接受健康志愿者

入选标准

  • Participants must be licensed physicians and have completed at least post-graduate year 2 (PGY2) of medical training.
  • Training in Internal medicine, family medicine, or emergency medicine.

排除标准

  • Not currently practicing clinically.

研究组 & 干预措施

GPT-4

Active Comparator

Group will be given access to GPT-4

干预措施: GPT-4 (Other)

Usual Resources

No Intervention

Group will not be given access to GPT-4 but will be encouraged to use any resources they wish besides large language models (UpToDate, Dynamed, google, etc).

结局指标

主要结局

Management Reasoning

时间窗: Within one-hour study

Percent correct (range: 0 to 100) for each case.

次要结局

  • Time Spent on Management(Within one-hour study)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Jonathan Chen

Assistant Professor of Medicine

Stanford University

研究点 (2)

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