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EP2: How good is my clinical GPT?

  • Writer: Hongjian Zhou
    Hongjian Zhou
  • Dec 21, 2023
  • 2 min read

Following up on our previous episode on how to build your custom GPT, we've created an easy-to-follow tutorial on evaluating your clinical GPT – with a proven framework! The framework, TEHAI (Translational Evaluation of Healthcare AI), is shared in this post with everyone!


🎥 Episode Breakdown:

0:00 - 1:40: Introducing the TEHAI framework

1:40 - 7:00: Capability evaluation

7:00 - 13:00: Utility evaluation

13:00 - 16:35: Adoption evaluation



Evaluation Framework: TEHAI Assessment for GPT in Clinical Practice


This is an easy-to-follow framework to evaluate your clinical GPT. Under each section, we provide sample questions and prompts that you can use to show how to practically apply this framework. Our example questions relate to the Pneumonia GPT we created in the first episode.


1. Capability 

  • Intrinsic Capability: Evaluate the model's ability to enhance decision-making, reliability, and knowledge provision

  • Performance Metrics & Use Case: Has the GPT been tested against any relevant performance metrics?

2. Utility 

  • Generalizability and Contextualization: Is the output of the GPT accurate in various clinical contexts.

  • Safety and Quality: Is there ongoing monitoring and governance of the GPT?

  • Transparency: Can the GPT explain how it produces an answer.

  • Privacy: Always ensure no personal health information is shared with the GPT

  • Time Efficiency: Does using the GPT save time in your clinical practice? How does it compare to what you are using right now?

3. Adoption 

  • Clinical Context Use: Assess the practicality of utilizing the GPT in your clinical setting. Does it integrate within your current clinical workflow or do you need to change how you practice?

  • Technical Integration and Operational Dependability: Can the GPT be integrated within your EMR? Do you have access to ChatGPT in your clinical setting?

  • Alignment with Domain: Ensure that the GPT aligns with healthcare regulations and standards.


Assessing GPT Summary:

  • Step 1: Identify a specific GPT tool you are considering for clinical practice.

  • Step 2: Allocate 10-15 minutes for a thorough yet rapid assessment.

  • Step 3: Go through each component of the TEHAI framework, focusing on the key areas outlined above

  • Step 4: Score each component based on how well the GPT meets the requirements (e.g., High, Medium, Low). For more technical scoring system see reference on TEHAI framework below.

  • Step 5: Make an informed decision based on your aggregate assessment and your clinical needs.


(Reddy S. Evaluating large language models for use in healthcare: A framework for translational value assessment. Informatics in Medicine Unlocked. 2023)


Techniques for improvement

  • Narrow down your use case for each GPT

  • Provide as much context as possible: Organize your prompt in a structured way and be specific with what output you are looking for.

  • Iterate on your prompts to see how the GPT reacts to various scenarios

  • Provide few-shot samples for your unique cases. Few shot samples are template Q&A that you wish the model to follow. For example, you may provide examples of how you would like the GPT to answer every question, in a style that is helpful for you.


To read more about the TEHAI Framework, consider the following references:

  1. Reddy S, Rogers W, Makinen VP, Coiera E, Brown P, Wenzel M, Weicken E, Ansari S, Mathur P, Casey A, Kelly B. Evaluation framework to guide implementation of AI systems into healthcare settings. BMJ Health Care Inform. 2021 Oct;28(1):e100444. doi: 10.1136/bmjhci-2021-100444. PMID: 34642177; PMCID: PMC8513218.

  2. Reddy S. Evaluating large language models for use in healthcare: A Framework for translational value assessment. Informatics in Medicine Unlocked. 2023 Volume 41. https://doi.org/10.1016/j.imu.2023.101304




7 Comments


unicorn682688
Jun 15

I think evaluating a clinical GPT is most useful when you look at both accuracy and consistency, not just how confidently it responds. Testing it with real-world scenarios and comparing the answers with trusted sources can give a better picture of its strengths and limits. It also highlights the value of guidance when learning complex subjects. For example, students sometimes seek Java assignment writing help when they struggle with coding concepts. In both cases, support and careful review help improve understanding and outcomes.

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Aimee Mowbray
Aimee Mowbray
Jun 09

I really appreciate the insightful discussion in this post about Clinical GPT and its practical applications in healthcare workflows. The analysis is thoughtful and highlights important considerations around accuracy and real-world usability. It also connects well with the growing need for premium book writing services that help translate complex ideas into clear, structured, and accessible content for wider audiences. Such conversations are valuable for understanding how AI is shaping professional writing and communication today.

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Ricky B Littles.
Ricky B Littles.
Jun 08

Apprecceating this insightful discussion on how clinical GPT performs in real-world healthcare scenarios and the challenges of accuracy and reliability. It makes me think about how different industries evaluate expertise and trust, similar to how book publishers in vermont focus on quality standards and credibility in publishing. How do you think such AI tools should be validated in clinical settings?

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Cecilia Moore.
Cecilia Moore.
Jun 08

Appreciating this insightful discussion on clinical GPT and its real-world applications in healthcare innovation. It’s impressive to see how AI is evolving in medical contexts and improving decision-making support. At the same time, maintaining accuracy and clarity in content remains essential, which is where book proofreading services can play an important role for researchers and writers sharing complex technical insights.

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melica john
melica john
Jun 08

This post provides an interesting look at how AI tools can be evaluated in clinical settings. It is important to understand both the strengths and limitations of technology, especially in healthcare. As a student, I find data-driven topics very engaging. While working on a research project, I used SPSS Assignment Help in UK to better understand statistical analysis and interpret results correctly. Careful evaluation is essential when working with both data and technology. nice post.

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