Since late 2022, the use of AI tools like ChatGPT has grown quickly in healthcare. They help with note-taking, documentation, and diagnostic support. Studies show AI answers can be as good as, or better than, some doctor-written replies. For example, researchers at the University of California checked chatbot answers on Reddit’s r/AskDocs forum. They found that professionals rated AI responses 3.6 times higher in quality and 9.8 times higher in empathy than verified doctors. GPT-4 also showed a 64% success rate in listing the correct diagnosis among difficult cases and had 39% accuracy in naming the true diagnosis.
Still, AI tools work as helpers, not replacements, for doctor judgment. Their outputs need careful checking.
Using AI for clinical notes raises questions about who is responsible for the information in records. It is important to keep records accurate and reliable. Being clear about AI use helps in several ways:
Because of this, healthcare practices need rules to say when AI is used, which version, and who wrote or checked the notes.
Clinical notes that use AI should clearly say so. This can be in the note’s header or footer. The note should include:
This helps everyone who reads the record understand where the information came from.
AI technology changes fast. Keeping track of the AI tool version used for notes is important for several reasons:
Adding the AI version in note metadata or policy appendices is a simple way to keep these records.
While AI can create or help write notes, the licensed healthcare provider still holds full responsibility. Recommended steps include:
This ensures clinicians remain accountable for the note’s accuracy and clinical decisions.
Protecting patient privacy is very important when using AI in healthcare records. AI services often use cloud platforms, which may send data to servers outside the U.S. This raises questions about data laws like HIPAA.
Key privacy points include:
Groups like the College of Physicians & Surgeons of Alberta advise careful use of AI with attention to practice standards, consent, and data safety. Although they are Canadian, these ideas also apply in the U.S.
There is no detailed federal law specifically about AI in clinical notes yet. This makes it tricky for U.S. providers using this technology. Still, some rules apply:
Because laws are unclear, medical leaders should be careful. They should keep strong documentation, clinician oversight, and openly share AI use. Advice from the Canadian Medical Protective Agency that AI should not replace clinical judgment is also useful in the U.S.
One good use of AI is to make workflows more efficient. AI can automate tasks like note-taking, summarizing, and drafting. This helps by:
Studies also show that less documentation workload can improve healthcare workers’ well-being. Too much paperwork is a main cause of burnout.
For healthcare IT managers, AI solutions like phone automation can also reduce staff work. This includes scheduling appointments, answering questions, and handling calls. Automating these helps staff work better and lets doctors focus on patient care.
To be clear and follow rules when using AI in clinical notes, medical leaders should:
AI-assisted clinical documentation can help healthcare by reducing paperwork, improving notes, and supporting diagnoses. But U.S. medical leaders and IT managers must be clear about AI use. They should disclose which AI tools are used, track versions, and keep clear authorship to protect data and follow laws.
With careful and informed use, AI can be a useful tool that helps doctors work better while protecting patient rights and building trust in healthcare.
Professionals must ensure patient consent for technology use, safeguard privacy, verify note accuracy and bias in differential diagnoses, and document appropriate clinical follow-up. They remain accountable for clinical judgment and documentation quality when integrating AI-generated content.
Early studies show generative AI such as GPT-4 correctly includes the true diagnosis in 39% of challenging clinical cases and presents it in 64% of differentials, comparing favorably to human counterparts, though these findings require further validation.
Major concerns include exposure of personally identifiable information, potential server locations outside of Canada, absence of privacy impact assessments, and the involvement of private companies with proprietary interests, risking legal and ethical breaches of patient data rights.
Due to the novelty and complexity of AI technologies, patients should be informed about data privacy risks, potential inaccuracies, and biases. Consent should cover recording clinical encounters and use of AI tools, ensuring ethical transparency.
Large language models trained on biased datasets may produce skewed or discriminatory outputs. Clinicians should critically evaluate AI content considering patient demographics and clinical context, maintaining transparency to mitigate ethical and clinical risks.
Data sovereignty ensures respect for Indigenous peoples’ rights under principles like OCAP, OCAS, and Qaujimajatuqangit data. AI use must align with governance policies to prevent violation of cultural data ownership and control.
Current laws are largely silent on AI’s role in clinical care, prompting calls for updated privacy legislation to protect patient rights, ensure data security, and balance innovation with ethical use. Physicians must follow professional standards and CMPA guidance emphasizing AI as a tool, not a replacement.
Harm risks include privacy breaches, inaccurate documentation causing clinical harm, and violation of cultural data rights. Benefits involve improved note quality, enhanced clinical communication, and possible diagnostic support, though these are based on preliminary evidence needing further study.
AI can improve workflow efficiency and reduce health system costs by streamlining charting and decision support. It may alleviate documentation burdens, promoting workforce wellness and enabling sustainable healthcare innovation.
Notes should specify author identity and clearly state AI tools and versions used. This transparency preserves data integrity, facilitates auditability, and supports continuity of care while complying with standards of practice.
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