Streamlining clinical records with AI: Efficiency, accuracy and ethical challenges

Accurate clinical documentation is a cornerstone of effective patient care. This responsibility falls squarely on the shoulders of doctors who have legal and professional obligations to maintain accurate records. However, with doctors spending between one-quarter and one-third of their day on paperwork, the allure of artificial intelligence solutions such as AI scribes to relieve the pressure is understandable. With the promises of efficiency and accuracy, doctors must be attuned not only to the benefits AI but also the risks. For doctors and practices exploring these tools, we have identified some key issues to keep in mind.

At Avant, we spend a good deal of time talking about the importance of good clinical record-keeping.

Avant’s analysis of claims involving medical records found records were assessed as below standard for one in every nine claims. Of the claims where a doctor’s care of the patient was ultimately found to be below standard, one-quarter had poor clinical records.

Further, some claims could not be defended because of incomplete or missing records. Complaints to regulators resulted in more severe outcomes when records were found to be poor.

Inadequate records can compromise patient care by contributing to missed or delayed diagnosis and medication errors. Poor quality records are often involved in legal or regulatory action including investigations by Ahpra and Medicare investigations. Poorly maintained records can also have broader public health implications if they compromise continuity of care, medical research, epidemiological studies, and public health initiatives.

AI scribes use ambient listening to capture the content of a doctor-patient consultation, extract clinically relevant information, then collate and structure data into a coherent clinical note based on a template or framework. This is then reviewed and added to as required by the doctor. The same content can be re-formatted into a summary letter or treatment plan for the patient, referral letter, discharge summary, or other paperwork. A copy of the final note can also be provided to the patient. 

It is the doctor’s responsibility to ensure that all relevant information – including non-verbal information and examination findings – is incorporated into the record at the end of the consultation.

AI models can incorporate checklists or prompts to reduce the risk of omitting key information. This may improve diagnostic accuracy and continuity of care and assist with prevention or early intervention provided that the clinician reviews and considers the recommendations made by the AI tool.

If the original record is reviewed carefully, creating multiple documents out of the same source data may also reduce the risk of transcription errors. One (small) UK study based on patient vignettes showed AI (ChatGPT) performed as well or better than junior doctors in producing discharge summaries, and was less likely to make transcription errors or omit key information. However, care must be exercised when using an AI tool which is not created for use in healthcare to ensure that it is fit for its clinical purpose.

By removing the need to take comprehensive notes during the consultation, AI scribes may allow doctors to focus more on patients, and patients to feel they have their doctors’ full attention. If doctors find themselves verbalising observations and thought processes for the benefit of the AI, the process may also increase transparency during the consultation. If the notes produced form the base record which is then reviewed and added to by the clinician, records may be improved. 

 If you are considering adopting an AI scribe to assist with clinical notetaking, consider what you hope the tool can do to assist your practice, and how you plan to use the outputs. Undertake your own due diligence to determine whether the tool will meet your clinical needs. Make sure you have considered the following issues.

Privacy and confidentiality

Some AI scribes are integrated into practices’ medical records software systems and clinical workflows, while other scribes operate outside practice systems. Either way, , you must be confident that patient privacy and confidentiality is protected. That means checking where the data is processed, where and how it is stored (in Australia or overseas), and how it will be used (will the company use it for other purposes?).

Always obtain patient consent to use an AI scribe.  Our article AI scribes and patient consent provides more information on the reasons for obtaining consent.  

Do not use publicly available general purpose AI tools (such as ChatGPT). These tools have not been designed for a medical purpose and are unlikely to offer sufficient protection for sensitive data.  For more information see our article ChatGPT for clinical notes: why not?

Ensure your practice has included a reference to AI in its privacy policy, as required under changes to privacy legislation commencing on 10 December 2026 Office of the Australian Information Commissioner AI transparency obligation 

Is your AI ‘medical grade’?

Not all AI is the same. Research is progressing on designing AI specifically for medical applications, with sufficient scientific rigour and trained on appropriate and high-quality clinical data. However, the technology is still evolving, and not all tools will be able to process medical information in a modern Australian context. AI scribing tools also generally fall outside the Therapeutic Goods Administration’s medical device regulatory processes, although some now include functions that go beyond transcription and summarisation. These are likely to meet the definition of a medical device and, if so, must comply with the TGA’s regulatory requirements.

Applications such as clinical scribing tools require the AI to process the text to identify clinically significant information. Scribe tools may be unable to interpret languages other than standard English or may have difficulty understanding accents. Since AI tools have been ‘trained’ on historical datasets, there is the potential to perpetuate historical biases, for example based on race, gender or sexuality. It is important that introducing AI support in healthcare does not reverse progress on addressing healthcare inequities.

How will it affect the flow of the consultation?

Verbalising all your observations and considerations for the audio transcript may be clinically inappropriate in some consultations. Examples could include recording the BMI of a patient being treated for anorexia nervosa or recording your concerns about the cause of a patient’s injuries.

Further, the scribe will not pick up non-verbal communications or cues. You will need to make sure you are able to capture and incorporate these observations into the record. 

Consider for example whether you would need to be able to add in additional notes after the patient has left the room to add further observations.

How will you check the record?

You are responsible for making sure the record accurately reflects the consultation. Never assume the AI-generated record is accurate. You need to be able to check the AI has captured and correctly interpreted relevant details. If you do not check the AI generated record, and it is incorrect or has raised a diagnostic issue you have not considered, you may be vulnerable to criticism, and there may be patient safety implications if there is an error.

As noted above, the AI-generated note may be incomplete or misleading because it does not reflect non-verbal cues. It may also miss clinical indications that contradict what is said – for example it may record the patient saying they have no allergies but miss the fact they said that they had experienced an adverse reaction a medication. Our article AI scribes in practice: common errors to consider contains more examples.

Further, AI’s tendency to fill in gaps or extrapolate findings, could lead to a misleading record. Ultimately, the clinician is responsible  for the notes which are produced by the AI tool at the clinician’s request – so check the note every time

You will also need to be satisfied the record captures sufficient detail to justify any Medicare item numbers you have billed for the consultation.

Finally, regularly monitor and review their use in your practice, to ensure that they are fit for their clinical purpose and produce the intended outcomes.

Conclusion

Do your own due diligence to be confident the AI scribe you choose:

• is appropriate for your practice,
• can help you deliver safe patient care, and
• can comply with your legal and professional obligations – including ensuring patient privacy.

Seek advice from your peers and professional colleagues and ask the software vendor to provide you with information about how the scribe complies with Australian privacy laws and therapeutic goods legislation (if relevant). .

Remember you are ultimately responsible for the accuracy of your clinical records. Always exercise your own professional clinical judgement. Treat any output as a draft and ensure you can review and check outputs for accuracy.

References and further reading

Ahpra Meeting your professional obligations when using AI in healthcare, 2024.

Australian Medical Association. AMA position statement on AI in healthcare. 2023. https://www.ama.com.au/articles/artificial-intelligence-healthcare

Office of the Australian Information Commissioner AI transparency obligation, 2026.

More information

For medico-legal advice, please contact us here, or call 1800 128 268, 24/7 in emergencies.