Technology
complexity, urgency or completeness, directly addressing the fatigue issue. If a meeting begins with its most clinically demanding cases, while participants are freshest, the quality of decisions for those patients is likely to improve. Conversely, if patients with straightforward, guideline-consistent presentations can be routed through a pre-agreed standard-of-care pathway and documented accordingly, they are reviewed appropriately without consuming the focused discussion time that complex cases require. Finally, systems that allow any team member
to upload an image of a blood test result, paste a report from a different clinical system, or attach an audio note alongside a formal referral could help achieve the data completeness that EPR integration promises, but cannot deliver, due to integration issues.
The patient voice: an underused variable MDT reform is frequently discussed in terms of efficiency and clinical throughput. Less often discussed, but equally important, is the question of whether MDT decisions reflect what patients actually want. A qualitative study published in January 2025 drew on interviews and questionnaires from two major UK oncology centres to examine the integration of patient preferences into MDT decision-making. It found that while clinicians recognised the value of incorporating patient preferences, standardised referral forms and meeting structures provided no consistent mechanism to capture or relay them.11 This gap has consequences. Research
on shared decision-making in oncology is consistent: patients who are well-informed and whose preferences are incorporated into treatment planning report greater satisfaction, experience less decisional
conflict, and adhere better to treatment.12 A patient who has indicated a preference against surgery, or who is managing a complex social situation that affects their capacity to tolerate certain treatment regimens, should not have a treatment plan formulated without that information being available to the MDT. Yet the current paper-list model provides no standardised means of recording or transmitting such input. Digital MDT tools that include structured fields for patient-reported preferences alongside clinical data begin to address this gap. They do not replace the clinical consultation in which those preferences are explored, but they ensure that what patients have said reaches the meeting room rather than being filtered out by the limitations of the referral format.
The research dividend that is currently being wasted There is a final dimension to MDT improvement that rarely features in efficiency discussions: the value of the data that MDTs generate, and the near-total failure to capture it systematically. A typical breast cancer MDT at a major teaching hospital discusses in the region of 3,000 cases per year. Over five years, that represents 15,000 cases, each with a treatment plan and (eventually) an outcome. Current survival predictions use the PREDICT algorithm. PREDICT was first published in Breast Cancer Research in January 2010 by Wishart et al; 13
it was derived from East Anglia ECRIC
registry data from women diagnosed/treated surgically for invasive breast cancer during 1999–2003 and validated using West Midlands Cancer Intelligence Unit data. Thus, the data on which we base current predictions is over 20 years. The data collected over five years from one teaching hospital could have easily re-validated
the data or modified the calculation using current data and outcomes, as well as similar geography to the patients served. For colorectal cancer, the UK has ~48000 cases each year or around 600-800 cases per year. That is 3000- 4000 cases per large hospital every five years. The clinical research that could be done with full capture of data at the time of referral is immense. The dataset implicit in that volume of MDT activity is precisely the kind of real-world evidence that health systems need to evaluate new treatments, identify outcome variation, and improve guidelines. At present, almost none of this is captured in a format that makes analysis possible. MDT decisions are recorded in EPR free text, embedded in letters, or written on paper lists that are never digitised. The research potential of 25 years of weekly MDT meetings across the NHS has been almost entirely wasted. Digital MDT platforms that capture
structured decision data, including which clinicians contributed, what information was available, what plan was made and what the patient outcome was, can create a dataset of extraordinary research value as a byproduct of normal clinical use. At a time when the Cancer Plan is explicitly calling for more real-world evidence to support cancer innovation, building that evidence infrastructure into the tools clinicians use every week is both efficient and urgent.
The right kind of digital transformation The NHS should not need to wait for a comprehensive EPR integration programme before MDTs can work significantly better. The evidence for targeted digital improvement is already substantial: structured digital tools reduce per-patient discussion time, improve data completeness, support asynchronous participation, enable risk-based case triaging, and create the data infrastructure for future research, without requiring trusts to overhaul their legacy systems or having to wait for a large-scale IT programme that may be years away. The Royal College of Radiologists’ review could set a direction that is both clinically credible and practically achievable. What the evidence supports is not a revolution in hospital information architecture, but a rethink of the tools through which clinical expertise is organised and applied. If MDT meetings are, at their best, the mechanism through which the NHS delivers its most expert and equitable cancer care, the priority must be to remove every barrier between that expertise and the patient. Better data management that is flexible, complete,
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