A BMJ podcast raises important questions about patient access to artificial intelligence tools to review their health data, but significant safeguards already exist—and gaps remain.
A thought-provoking question posed by the British Medical Journal’s Medicine and Science Podcast has sparked debate about the future of patient autonomy and artificial intelligence in healthcare: “How ready are we for patients to put their medical records into a large language model and ask the question: have I been harmed?”
The question reflects a growing reality in modern medicine. Large language models (LLMs)—sophisticated artificial intelligence systems trained on vast amounts of text data—are becoming increasingly accessible to the general public. The possibility that patients might use these tools to analyse their own medical histories, flag potential medication errors, identify missed diagnoses, or spot patterns in their care raises profound questions about patient safety, data security, and the readiness of the NHS to manage this shift.
The Current Landscape for Patient Data Protection
The NHS already operates under a strict legal framework designed to protect patient confidentiality and data security. Under UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018, NHS England acts as the “safe and effective guardian” of health data collected from NHS and adult social care services.
According to NHS England’s published guidance, health records cannot be shared with third parties—including private companies or AI platforms—without explicit legal justification and appropriate safeguards. When private sector organisations do access patient data, they must sign legal contracts stipulating how data can be used and typically cannot transfer information to other parties without specific approval.
The NHS operates a Data Uses Register, which the public can access to see who is receiving NHS data and for what purposes. Additionally, patients retain significant control over their own information. Under current regulations, individuals can opt out of their data being shared for research and planning purposes through a Type 1 Opt-out form submitted to their GP practice—a choice that does not affect their clinical care.
The Challenge Posed by Large Language Models
The emergence of LLMs as consumer tools creates a novel scenario not fully anticipated by existing regulatory frameworks. If a patient downloads their medical records—which they have a legal right to access—and inputs them into a publicly available AI system to seek analysis, several concerns arise.
First is the question of data security. Most commercial LLM platforms retain or use data for training purposes. Uploading sensitive health information to such systems could expose confidential medical details to unintended processing or retention, potentially breaching the confidentiality principles that underpin NHS data protection.
Second is accuracy and clinical liability. Large language models, whilst sophisticated, are not infallible and can make errors or “hallucinations”—generating plausible-sounding but incorrect information. A patient receiving a misguided analysis from an AI tool about potential harm in their care could lead to unnecessary anxiety, loss of trust in their healthcare provider, or conversely, dangerous delays in seeking genuine medical attention.
Third is the question of accountability. If an LLM provides advice or analysis that affects a patient’s health decisions, who bears responsibility if something goes wrong? The NHS, the AI company, or the patient? Current legal frameworks are unclear on this point.
What Safeguards Already Exist
The NHS and UK regulators have not ignored these risks. The use of Secure Data Environments (SDEs)—platforms where health data cannot leave NHS infrastructure—is being expanded as a way to reduce risks associated with external data transfers. These environments allow researchers and approved organisations to analyse NHS data without ever removing it from a protected space.
NHS guidance makes clear that health professionals have a legal duty to support individual patient care through appropriate information sharing, balanced against confidentiality duties. Organisations must publish privacy notices explaining how patient data is used, and patients can object to specific uses of their information.
However, the scenario posed by the BMJ podcast—where patients independently upload their own medical records to consumer AI tools—sits in a regulatory grey area. Current frameworks focus on organisational data handling, not individual patient choices about their own data.
What Needs to Happen Next
The question posed by the Medicine and Science Podcast suggests that policymakers, healthcare leaders, and technology regulators need to think proactively about patient access to AI tools. This could involve:
Developing clear guidance for patients about the risks and benefits of using consumer AI tools with sensitive health data. Public awareness campaigns could explain data security implications and the limitations of AI analysis in healthcare contexts.
Working with AI companies to develop standards for handling health data—such as commitments not to retain or train on medical information from personal uploads.
Creating pathways for patients to use approved, secure AI analysis tools within NHS-controlled environments, where safety and accuracy can be assured.
Establishing clearer liability frameworks so patients, healthcare providers, and technology companies understand responsibilities if AI-assisted analysis leads to harm.
What This Means for Kent Residents
For patients across Kent, these developments carry practical implications. The NHS continues to evolve how it manages and shares patient data, with strong protections already in place through UK GDPR and established data governance frameworks. Kent and Medway NHS Trust, like all NHS organisations, follows strict protocols for data access and security.
If you have concerns about how your medical records are being used or shared, you can contact your GP practice or speak with your NHS organisation’s information governance department. You retain the right to opt out of data sharing for research purposes, and you can always ask how your information is being used.
As artificial intelligence tools become more prevalent, staying informed about where you choose to share your health information—and understanding the difference between NHS-approved data platforms and consumer AI tools—will become increasingly important for protecting your privacy and ensuring safe, accurate healthcare.
Source: @bmj_latest
Key Takeaways
- Patients are increasingly able to access their medical records digitally, raising questions about how they use this information with AI tools
- The NHS operates strict data protection frameworks under UK GDPR, but these focus on organisational handling rather than individual patient choices
- Uploading medical records to consumer AI platforms carries risks including data security concerns and potential inaccuracy in AI analysis
- Current regulatory frameworks do not fully address liability or safety standards when patients use commercial LLMs for health analysis
- Developing clearer guidance and secure NHS-approved AI tools could help patients benefit from AI analysis whilst protecting privacy and accuracy
What This Means for Kent Residents
If you are a patient in Kent, you can be reassured that your NHS records are protected by robust legal safeguards and security protocols. However, it is important to be cautious about uploading sensitive health information to consumer websites or apps, even if they use artificial intelligence. If you have questions about your medical records, privacy rights, or how your data is being used, contact your GP practice or the information governance team at your NHS trust. You can also visit the NHS England website to access the Data Uses Register and learn more about your rights to opt out of data sharing for research purposes.
