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Completed

NCT Number: NCT06911645

Diagnostic Reasoning With Customized GPT-4 Model

This study will assess the impact of immediate access to a customized version of GPT-4, a large language model, on performance in case-based diagnostic reasoning tasks. Specifically, it will compare this approach to a two-step process where participants first use traditional diagnostic decision support tools to support their diagnostic reasoning before gaining access to the customized GPT-4 model.

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Key information

Conditions

Pathologic Processes Disease Pathological Conditions, Signs and Symptoms

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Stanford University

Palo Alto, California, 94305, United States

About this study

Artificial intelligence (AI) technologies, particularly advanced large language models like OpenAI's ChatGPT, have the potential to enhance medical decision-making. While ChatGPT-4 was not specifically designed for medical applications, it has demonstrated promise in various healthcare contexts, including medical note-writing, addressing patient inquiries, and facilitating medical consultations. However, its impact on clinicians' diagnostic reasoning remains largely unknown.

Clinical reasoning is a complex process that involves pattern recognition, knowledge application, and probabilistic reasoning. Integrating AI tools like ChatGPT-4 into physician workflows could help reduce clinician workload and decrease the likelihood of missed diagnoses. However, ChatGPT-4 was neither developed nor validated for diagnostic reasoning, and it may produce misleading information, including plausible but incorrect conclusions that could misguide clinicians. If not used appropriately, it may fail to improve-and could even hinder-clinical decision-making. Therefore, it is essential to study how clinicians use large language models to support clinical reasoning before integrating them into routine patient care.

This study will examine how immediate access to a customized version of ChatGPT-4 impacts performance on case-based diagnostic reasoning tasks, compared to a stepwise approach. In the stepwise approach, participants will first use traditional diagnostic decision support tools to support their case reasoning before interacting with a customized ChatGPT-4 model, at which point they will have the opportunity to revise their initial answers.

Participants will be randomized into different study arms and will respond to diagnostic cases by providing three differential diagnoses, along with supporting and opposing findings for each. They will also identify their top diagnosis and propose next diagnostic steps. Independent reviewers, blinded to treatment assignment, will evaluate their responses.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Participants must be licensed physicians and have completed at least post-graduate year 1 (PGY1) of medical training.
  • Training in Internal medicine, family medicine, or emergency medicine.

Exclusion criteria

  • Not currently practicing clinically.
  • Participated in one of our previous studies that used the same six diagnostic cases.

Treatment and study plan

Immediate access to customized version of GPT-4

Other

Group is given immediate access to a customized version of GPT-4 to support their diagnostic reasoning for each case.

Access to customized version of GPT-4 following use of conventional resources

Other

Group is first encouraged to reason through diagnostic cases with the support of conventional resources. After they submit a case's answers they are then given access to a customized version of GPT-4 and have the opportunity to change their initial answers.

Primary outcomes

  1. Diagnostic reasoning

    Time frame: Through study completion, an average of 6 months

    The primary outcome will be the percentage of correct responses per case (range: 0 to 100). For each case, participants will be asked to provide their top three differential diagnoses, along with supporting and opposing findings for each. They will receive 1 point for each plausible diagnosis. Supporting and opposing findings will be graded based on correctness, with 1 point for a partially correct response and 2 points for a completely correct response. Participants will then select their top diagnosis, earning 1 point for a reasonable choice and 2 points for the most accurate diagnosis. Finally, they will list up to three next steps for further patient evaluation, with 1 point awarded for a partially correct response and 2 points for a completely correct response. The primary outcome will be analyzed at the case level, comparing performance between the randomized study groups.

Secondary outcomes

  1. Time Spent Per Case

    Time frame: Through study completion, an average of 6 months

    The investigators will compare the average time (in minutes) participants spend on each case across the two study arms.

  2. Prompt frequency

    Time frame: Through study completion, an average of 6 months

    The investigators will compare the frequency of participant prompts to the customized GPT-4 model between the two study groups.

  3. Sentiment

    Time frame: Through study completion, an average of 6 months

    The investigators will compare the tone and sentiment of participant prompts to the customized GPT-4 model across the two study groups. The investigators will create a qualitative coding system to categorize the nature of the participants' prompts.

  4. Participant Perceptions of AI in Clinical Reasoning

    Time frame: Through study completion, an average of 6 months

    This outcome would be assessed in both study arms and would encompass changes in attitudes, confidence, and willingness to use AI diagnostic tools before and after being exposed to the customized tool. We will assess the number of participants who were open to using AI to help with complex clinical reasoning (pre- and post-quiz), if they enjoyed working with the AI diagnostic tool, if they felt like the tool provided a valuable collaborative experience for clinical reasoning, if seeing the AI diagnostic tool's recommendations increased their confidence in their differential diagnoses, and if they would use an AI diagnostic tool like the one in this study in their daily job. These will be evaluated on a Likert scale ranking from strongly disagree to strongly agree.

  5. Customized GPT-4's diagnostic reasoning

    Time frame: Through study completion, an average of 6 months

    The customized GPT-4's 'independent' diagnoses will be assessed for accuracy. The outcome will be the percentage of correct responses per case (range: 0 to 100). For each case, the meta-prompt directs the customized GPT-4 to provide its top three differential diagnoses, along with supporting and opposing findings for each, a final diagnosis, and next steps. The customized GPT-4 will receive 1 point for each plausible diagnosis. Supporting and opposing findings will be graded based on correctness, with 1 point for a partially correct response and 2 points for a completely correct response. Its top diagnosis will earn 1 point for a reasonable choice and 2 points for the most accurate diagnosis. Finally, it will list up to three next steps for further patient evaluation, with 1 point awarded for a partially correct response and 2 points for a completely correct response. The outcome will be analyzed at the case level, comparing performance with the randomized study groups' scores.

Sponsors and collaborators

Lead sponsor

Stanford University

Other

Collaborators

  • Beth Israel Deaconess Medical Center

Registry information

Official study title

Evaluating the Performance of LLMs and Clinicians in Complex Diagnostic Cases: A Randomized Controlled Trial

Important dates

Study start
2024
Primary completion
2025
Study completion
2025
First posted
Apr 4, 2025
Registry last updated
Apr 4, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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