Aim: Precision oncology requires integrated multidisciplinary expertise to support routine cancer care. We evaluated the Precision Care Clinic molecular MDT, a component of the service, by characterising its implementation, specialist activity workflows and decision-support outputs to inform optimisation and sustainable scale-up.
Methods: A prospective observational evaluation was undertaken during pilot implementation of a national molecular MDT. Purpose-designed tools captured team composition, implementation processes, multidisciplinary participation, decision-making, resource utilisation and service outcomes across specialist case preparation, multidisciplinary deliberation and curation of personalised recommendations. Quantitative data, including specialist time, were summarised descriptively, while qualitative field notes were analysed using the Consolidated Framework for Implementation Research.
Results: Between September 2023 and June 2026, 48 MDT meetings comprising 161 case discussions from 131 referrals (including two re-referrals) were observed. Referral indications included germline genetics assessment (52, 39.7%) and MDT review (79, 60.3%). Median case discussion time was 9 minutes (range 1–32), with the shortest discussion reflecting notation of germline validation results only. MDT review referrals required approximately 6–8 hours of specialist effort outside the meeting, including literature appraisal, molecular and bioinformatic review, external consultation and preparation of recommendation reports. Most patients (98, 77.8%) were discussed once, while 22.2% required multiple reviews. Individual discussions commonly generated multiple decision-support outputs, including molecular interpretation (65.2%), germline assessment (58.9%), identification of therapeutic options (55.7%), supported treatment planning (53.2%), filtering low-value care options (44.9%), prioritisation of treatment strategies (41.8%), and clinical trial identification (39.2%).
Conclusion: The Precision Care Clinic MDT functions as an integrated decision-support service rather than a discrete multidisciplinary meeting. By characterising workflow and specialist effort, this study provides a foundation for implementation and economic evaluation. These data will inform future work to identify implementation barriers and evaluate scalable solutions, including workforce development and digitally enabled decision support, to facilitate sustainable precision oncology.