Learning from every patient: the 'outpatient innovation clinic'.

OBJECTIVES: To keep pace with rapid medical innovation, health care must be organized to enable systematic learning from every patient. The 'outpatient innovation clinic' was established to support this goal. This paper presents 12 years of experience with the outpatient innovation clinic, highlighting its approach, achievements, and challenges. METHODS: Established in 2013 at the Division of Imaging and Oncology at University Medical Center Utrecht, the Netherlands, the outpatient innovation clinic provides an infrastructure to systematically enroll patients into prospective cohort studies. Patients are invited for a consultation with a clinical researcher, and informed consent is asked for the reuse of medical data, the collection of patient-reported outcome measures (PROMs), randomization into trials, biobanking, and recontact. The infrastructure serves as a platform for evidence-based innovation, following the idea, development, exploration, assessment, and long-term evaluation (IDEAL) framework. RESULTS: Between 2013 and 2025, eight prospective (international) multicenter observational cohorts of patients with primary tumors, metastatic cancer, or neurovascular malformations were established. Out of a total of 45,099 participants, 15,691 were enrolled at the innovation clinic. Of these, 13,172 (84%) provided additional informed consent for the collection of PROMs, and 11,833 (79%) for randomization into future trials within cohorts, either to serve as controls or to receive an invitation for participation. A large real-world data repository was generated and is used for technical product development and testing, hypothesis-generating studies, training and evaluation of (deep learning) algorithms, long-term PROMs analysis, and randomized treatment comparisons. Since 2014, five cohort-embedded trials have been completed, four are ongoing, and one is in preparation. CONCLUSION: The outpatient innovation clinic offers a successful infrastructure for (deep) learning from every patient and for evaluating medical innovations within the IDEAL framework, while safeguarding patients' autonomy over the reuse of their medical data.