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Learning from every patient: the ‘outpatient innovation clinic’

  • Maarten J. Kamphuis
  • , Irene C. van der Schaaf
  • , Roxanne Gal
  • , Joanne M. van der Velden
  • , J. P. Maarten Burbach
  • , Nicolien Kasperts
  • , Jochem R. N. van der Voort van Zyp
  • , Joost J. C. Verhoeff
  • , Danny A. Young-Afat
  • , Martijn P. W. Intven
  • , Sofie A. M. Gernaat
  • , Frederieke H. van der Baan
  • , Geraldine R. Vink
  • , Miriam Koopman
  • , Faye J. Raaijmakers
  • , Fia Cialdella
  • , Tariq A. Lalmahomed
  • , Jasmijn M. Westerhoff
  • , Renée Hovenier
  • , Eline H. Huele
  • Frederik R. Teunissen, Dieuwke R. Mink van der Molen, Sophie R. de Mol van Otterloo, Merle Hattink, Mathijs L. Tomassen, Lois A. Daamen*, Helena M. Verkooijen
*Corresponding author for this work
  • Utrecht University
  • Department of Radiology, University Medical Center Utrecht (UMCU), Utrecht, The Netherlands.
  • Departement of Neurology and Neurosurgery, UMC Utrecht Brain Center
  • Division of Imaging and Oncology, University Medical Center Utrecht
  • Department of Radiation Oncology, University Medical Center Utrecht, Utrecht
  • University of Groningen
  • Department of Surgery, University Medical Center Groningen, Groningen, The Netherlands.
  • Department of Medical Oncology, University Medical Center Utrecht, the Netherlands.
  • Netherlands Comprehensive Cancer Organisation (IKNL)
  • Radboud University Nijmegen
  • Department of Radiation Oncology, Radboud University Medical Center, Nijmegen
  • Department of Surgery, Regional Academic Cancer Center Utrecht, University Medical Center Utrecht / St. Antonius Hospital Nieuwegein, Utrecht & Nieuwegein
  • Imaging Division, Netherlands Cancer Institute - Antonie van Leeuwenhoek, Amsterdam

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

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.
Original languageEnglish
Article number112250
JournalJournal of Clinical Epidemiology
Volume195
DOIs
Publication statusPublished - 1 Jul 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Cohort studies
  • Patient reported outcome measures
  • Pragmatic clinical trials as topic
  • Prospective studies
  • Quality of life
  • Registries
  • Routinely collected health data

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