Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levels

Yan Wang, Matthew J. Allsop, Joel B. Epstein, Doris Howell, Bernardo L. Rapoport, Penelope Schofield, Ysabella van Sebille, Melissa S. Y. Thong, Iris Walraven, Julie Ryan Wolf, Corina J. G. van den Hurk

Research output: Contribution to journalComment/Letter to the editorAcademic

Abstract

Purpose: This paper aims to provide a comprehensive understanding of the need for continued development of symptom monitoring (SM) implementation, utilization, and data usage at the macro-, meso-, and micro-levels. Methods: Discussions from a patient-reported SM workshop at the MASCC/ISSO 2022 annual meeting were analyzed using a macro-meso-micro analytical framework of cancer care delivery. The workshop categories “initiation and implementation, barriers to adoption and utilization, and data usage” were integrated for each level. Results: At the macro-level, policy development could encourage data sharing and international collaboration, including the exchange of SM methods, supportive care models, and self-management modules. At the meso-level, institutions should adjust clinical workflow and service delivery and promote a thorough technical and clinical integration of SM. At the micro-level, SM should be individualized, with timely feedback for patients, and should foster trust and understanding of AI decision support tools amongst clinicians to improve supportive care. Conclusions: The workshop reached a consensus among international experts on providing guidance on SM implementation, utilization, and (big) data usage pathways in cancer survivors across the cancer continuum and on macro-meso-micro levels.
Original languageEnglish
Article number182
JournalSupportive Care in Cancer
Volume32
Issue number3
DOIs
Publication statusPublished - 1 Mar 2024

Keywords

  • Real-world data
  • Supportive care
  • Symptom monitoring

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