Can GPs use AI ChatGPT for clinical notes? AI in Clinical Notes: Bridging Innovation with Privacy, Consent and Real-World Applications.

As Australian general practitioners (GPs) embrace artificial intelligence (AI), tools like ChatGPT are becoming pivotal in transforming patient consultations into comprehensive clinical notes. This leap in healthcare technology streamlines documentation, allowing doctors to concentrate more on patient interactions. Staff and Practice Managers also adopt tools like ChatGPT. However, this transition brings up critical issues around privacy and the necessity of obtaining patient consent.

The integration of AI raises concerns about the remote processing and potential overseas storage of sensitive patient data. Everything ‘sent’ to AI stays on its servers and forms the new data. That data may come to a use by millions of people. To mitigate risks, anonymizing patient data is paramount, ensuring clinical notes do not inadvertently reveal identifiable information. Yet, the practical application of this technology requires careful navigation to avoid compromising patient confidentiality.

The Importance of Patient Consent

An integral component of employing AI in clinical settings is patients’ explicit consent. GPs must inform patients about the AI’s role in processing their conversations. Patients have a right to know how their data is stored and the measures to protect their privacy.

Case Studies: The Path Forward

Case Study 1: Rare Hobby-Related Injury

Alex, known in their small town for performing at community events, sustains a unique injury from their uncommon hobby—competitive fire juggling. Alex details their recent performances and upcoming appearances during their consultation, where AI technology records the conversation. This specific information, if not anonymized, could easily identify Alex in their community, underscoring the need for careful data handling.

Case Study 2: Work-Related Stress in a Family Business

Jordan, who is involved in a prominent family-run restaurant chain, discusses with Dr. Patel the stress stemming from family disputes and business pressures, a situation vaguely covered in local media. The AI transcription of this consultation could link Jordan to the discussed personal and business tensions if the clinical notes include identifiable details about the family business or the nature of the stress, highlighting the importance of consent and anonymization.

Concluding Thoughts

AI in clinical documentation presents a promising future for enhancing healthcare delivery. Yet, as the case studies illustrate, it is crucial to navigate this innovation responsibly. GPs can use AI to improve clinical note-taking while keeping patient privacy and by prioritising patient consent and implementing rigorous data anonymisation processes. This balanced approach ensures that adopting AI technologies aligns with the ethical and legal standards essential to the medical profession.