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Patient safety concerns regarding artificial intelligence (AI) in healthcare are highlighted. Patients emphasize data integrity, efficacy, payment, and transparency, urging greater involvement in AI development and oversight for trustworthy patient care.

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Area of Science:

  • Healthcare technology
  • Artificial intelligence in medicine
  • Patient safety research

Background:

  • Growing integration of artificial intelligence (AI) in clinical settings raises patient safety concerns.
  • Patient advocacy groups are actively identifying potential risks associated with AI in healthcare.
  • Ensuring patient trust and safety is paramount as AI adoption accelerates.

Purpose of the Study:

  • To identify key areas of concern for artificial intelligence (AI) impact on patient safety from a patient perspective.
  • To outline critical considerations for AI developers, regulatory bodies, and clinical users.
  • To emphasize the necessity of patient involvement in AI governance for safe implementation.

Main Methods:

  • Qualitative analysis of patient advocate feedback and identified concerns.
  • Synthesis of patient-identified priorities regarding AI in healthcare.
  • Literature review on AI in patient care and safety implications.

Main Results:

  • Four primary areas of patient concern identified: data integrity and bias, efficacy, payment, and transparency for shared learning.
  • Patients request active participation in the development, assessment, and oversight of AI technologies.
  • Trustworthiness in AI for patient care is directly linked to patient involvement.

Conclusions:

  • Addressing patient-identified concerns is crucial for the ethical and safe deployment of AI in healthcare.
  • Enhanced patient engagement is essential to build trust and ensure AI serves patient needs effectively.
  • Collaborative efforts between patients, developers, regulators, and clinicians are vital for responsible AI innovation in medicine.