Multi-Disciplinary Treatment on the Anthropomorphism of Large Language Models

Официальное название

Multi-Disciplinary Treatment on the Anthropomorphism of Large Language Models: A Parallel Controlled Study

Обзор

This retrospective clinical trial aims to better explore the potential of large language models in medicine by comparing the effectiveness of MDT consultations conducted by human doctors with those conducted by large language models. The main questions to be addressed are: Does using large language models to conduct anthropomorphic MDT consultations yield better results than using non-anthropomorphic processes? Is there a significant performance gap between MDT consultations conducted by large language models and those conducted by humans? How much greater is the economic benefit of MDT consultations from large language models compared to those conducted by humans? Retrospectively collect MDT consultation records from the past 20 years in northern Sichuan in China, as well as anonymized patient medical records. Group 1: Different large language models are assigned to act as doctors from different departments and as MDT secretaries to summarize consultations. Group 2: The large language model directly outputs diagnostic and treatment recommendations for patients. Compare the outputs of groups 1 and 2 with human performance retrospectively, score them, and select the best model from each department for a re-evaluation through anthropomorphic MDT consultations, once again comparing them to human results.

Вмешательства

• Диагностический тест GPT-4o
  Input all patient medical records, including text, examination reports, and imaging data, into GPT-4o. Use pre-tested prompts to establish department roles, enabling it to provide diagnostic and treatment recommendations pertinent to the respective department.
• Диагностический тест GPT-4o mini
  Input all patient medical records, including text, examination reports, and imaging data, into GPT-4o mini. Use pre-tested prompts to establish department roles, enabling it to provide diagnostic and treatment recommendations pertinent to the respective department.
• Диагностический тест MedicalGPT
  Input all patient medical records, including text, examination reports, and imaging data, into MedicalGPT. Use pre-tested prompts to establish department roles, enabling it to provide diagnostic and treatment recommendations pertinent to the respective department.
• Диагностический тест Claude-3.5 Sonnet
  Input all patient medical records, including text, examination reports, and imaging data, into Claude-3.5 Sonnet. Use pre-tested prompts to establish department roles, enabling it to provide diagnostic and treatment recommendations pertinent to the respective department.
• Диагностический тест Claude 3 Haiku
  Input all patient medical records, including text, examination reports, and imaging data, into Claude 3 Haiku. Use pre-tested prompts to establish department roles, enabling it to provide diagnostic and treatment recommendations pertinent to the respective department.
• Диагностический тест Real Doctors
  Retrospectively collect the diagnostic and treatment recommendations from the corresponding departments involved in the multidisciplinary treatment of past patients, as well as the overall recommendations.

Первичные конечные точки

• Consultation Cost ($) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Consultation Time (min) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Comprehensiveness of the Multi-Disciplinary Treatment Results (Percentage Scale) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Clarity of Multi-Disciplinary Treatment Results (Percentage Scale) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Correctness of Multi-Disciplinary Treatment Results (Percentage Scale) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Cross-Professional Team Collaboration Practice Assessment (CPAT) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Rating Scale for Summarization [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]
• Flesch-Kincaid Readability Test [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]

Вторичные конечные точки (1)

• Ethical Compliance (Boolean) [Срок оценки: From Multi-Disciplinary Treatment Process to Multi-Disciplinary Treatment Process until all json fields are output, the time taken by human doctors to record the time using His system generally does not exceed 12 hours.]

Критерии участия

Критерии включения

• 1\. The medical records include interdisciplinary consultation notes, with recommendations from specialists of various departments and a well-documented final summary.
• 2\. The medical records contain data from at least one year prior to and one year following the consultation (including intact reports and imaging records).
• 3\. The patient\'s discharge conditions improved due to the multidisciplinary treatment plan after the consultation.

Критерии исключения

• 1\. The medical records do not include multidisciplinary consultation notes, or the recommendations from various departmental physicians and the final summary notes are incomplete or inadequate.
• 2\. The medical records lack data from 1 year before and after the consultation, or miss necessary reports and imaging data, resulting in incomplete documentation.
• 3\. The patient\'s condition at discharge has not improved following the multidisciplinary treatment plan, or the condition has worsened.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Другое

Центры проведения

Китай · 1 центр

• The Affiliated Hospital of North Sichuan Medical College — Nanchong

Публикации

• Schroder C, Medves J, Paterson M, Byrnes V, Chapman C, O'Riordan A, Pichora D, Kelly C. Development and pilot testing of the collaborative practice assessment tool. J Interprof Care. 2011 May;25(3):189-95. doi: 10.3109/13561820.2010.532620. Epub 2010 Dec 23. PMID 21182434

Идентификаторы

NCT: NCT06627985 · 1426887-2024-3

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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