The integration of artificial intelligence (AI) in pathology is raising complex ethical issues, particularly when it comes to error disclosures and the use of de-identified data. When an error occurs, pathologists must be prepared to disclose the issue to the treating physician, rather than directly to the patient. This approach allows for a more nuanced discussion, given the established relationship between the physician and patient.
Before making a disclosure, pathologists should conduct a root cause analysis to determine the cause of the error. They should also involve a risk management team and notify malpractice providers if patient harm or unreasonable care occurs. When disclosing the error, pathologists should be prepared to provide information on how to prevent similar problems in the future.
The use of de-identified data in AI systems also raises concerns about patient privacy and data protection. Companies can potentially re-identify data by combining multiple datasets, even if individual datasets are de-identified and HIPAA-compliant. Pathologists should therefore ensure that contractual terms prohibit downstream actions when sharing practice data with third parties.
Furthermore, pathologists should oversee the quality and accuracy of diagnostic software used in their practice. Regulatory approaches need to be developed to ensure competence in quality management for medical AI. Given the current immaturity in medical AI, pathologists' advocacy is crucial in ensuring that quality control measures are in place.
Overall, the integration of AI in pathology requires careful consideration of ethical issues related to error disclosures, data privacy, and quality control. By prioritizing transparency, accountability, and patient safety, pathologists can navigate these complex issues and ensure that AI is used in a way that benefits patients and the medical community.
