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Chatbots in medicine: certification process and applied use case.

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Chatbots in healthcare offer benefits if their scope is defined and regulations are met. This study details certification and regulatory compliance for medical chatbots, using confIAnce as a case study.

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Area of Science:

  • Artificial Intelligence in Healthcare
  • Medical Device Regulation
  • Digital Health

Background:

  • Chatbots, accelerated by large language models, face limited healthcare adoption due to privacy, diagnostic, and regulatory concerns.
  • Carefully defined scope, appropriate use, and long-term monitoring are crucial for realizing healthcare benefits from chatbots.
  • The confIAnce chatbot serves as an informational tool for public health education on primary care and chronic diseases.

Purpose of the Study:

  • To describe certification and regulatory aspects of healthcare chatbots, particularly in primary care.
  • To explore the classification of chatbots as medical devices under Swiss and EU regulations.
  • To provide a framework for chatbot development, certification, and compliance in healthcare.

Main Methods:

  • Case study analysis of the confIAnce chatbot.
  • Examination of Swiss regulations and the European Union AI Act.
  • Review of classification criteria for medical devices and AI in healthcare.

Main Results:

  • Chatbots can range from non-medical informational tools to high-risk Class III medical devices.
  • Key considerations include defining scope, regulatory compliance, security, safety, and continuous performance evaluation.
  • A lexicon of relevant terms for AI in healthcare and medical device regulation is provided.

Conclusions:

  • Chatbots have significant potential for patients and healthcare professionals when scope is clear and regulations are followed.
  • Transparency in certification and regulatory compliance is essential for safe and effective implementation.
  • This review offers valuable insights for healthcare stakeholders navigating AI in medicine.