The challenge of clinical documentation
Preparing for a patient consultation can require a clinician to review dozens—or even hundreds—of pages of medical records. This is particularly challenging when patients seek additional opinions and bring fragmented documentation from different healthcare systems. The administrative burden can reduce the time available for direct interaction, clinical reasoning, and shared decision-making.
According to Dr. Alexander Ryu, a physician and Vice Chair of Innovation in Mayo Clinic’s Department of Medicine, the organization receives tens of millions of pages of records each year. Locating the information that matters most within these files is therefore a substantial operational and clinical challenge. [1]
A practical use case for AI
Mayo Clinic has been testing an artificial-intelligence tool called Record Time to support record review before consultations. The system generates relevant patient summaries, organizes documents chronologically, and makes the record easier to search. In practice, this can help clinicians find important information more efficiently and reduce the risk that relevant details remain buried in long, unstructured files.
Dr Ryu has indicated that the tool saves between five and thirty minutes of preparation time per consultation, depending on the complexity of the case. [1] This is not merely an efficiency gain: it can be time returned to the patient. It can allow clinicians to focus more fully on listening, explaining, and making decisions together with the person in front of them.
Innovation with safeguards built in
The case is noteworthy not because it presents AI as a universal solution, but because it points to a disciplined implementation model. According to Mayo Clinic’s medical leadership, new AI tools are tested with small groups of patients under clinician supervision before they are broadened to larger populations. [1]
Mayo Clinic also states that any AI solution considered for clinical deployment must meet rigorous standards of safety and ethics. This includes work to mitigate bias, assess whether a tool functions as intended across diverse patient populations, and ensure that it improves care delivery and the patient experience while fitting naturally into daily clinical workflows. [2]
Returning technology to its purpose
The Record Time experience offers an important lesson for healthcare transformation. The most promising AI applications may not be those that seek to replace professional judgement, but those that release professionals from repetitive administrative tasks and enable them to devote more attention to care.
For healthcare organizations, the question is therefore not whether AI can be adopted, but how it can be introduced responsibly: with a clear clinical purpose, evidence-based evaluation, strong data governance, and meaningful involvement of the professionals who will use it. This is how technology can help strengthen—not weaken—the relationship at the heart of healthcare.
References
[2] Mayo Clinic Magazine — The Growing Role of Artificial Intelligence in Healthcare
