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

Show simple item record

dc.contributor.author Wang, Yan
dc.contributor.author Allsop, Matthew J.
dc.contributor.author Epstein, Joel B.
dc.contributor.author Howell, Doris
dc.contributor.author Rapoport, Bernardo Leon
dc.contributor.author Schofield, Penelope
dc.contributor.author Van Sebille, Ysabella
dc.contributor.author Thong, Melissa S.Y.
dc.contributor.author Walraven, Iris
dc.contributor.author Wolf, Julie Ryan
dc.contributor.author Van den Hurk, Corina J.G.
dc.date.accessioned 2025-03-19T10:55:34Z
dc.date.available 2025-03-19T10:55:34Z
dc.date.issued 2024-03
dc.description DATA AVAILABILITY : The data that support the findings of this study are available on request from the corresponding author. en_US
dc.description.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. en_US
dc.description.department Immunology en_US
dc.description.librarian hj2024 en_US
dc.description.sdg SDG-03:Good heatlh and well-being en_US
dc.description.uri http://link.springer.com/journal/520 en_US
dc.identifier.citation Wang, Y., Allsop, M.J., Epstein, J.B. et al. Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levels. Supportive Care in Cancer 32, 182 (2024). https://doi.org/10.1007/s00520-024-08373-x. en_US
dc.identifier.issn 0941-4355 (print)
dc.identifier.issn 1433-7339 (online)
dc.identifier.other 10.1007/s00520-024-08373-x
dc.identifier.uri http://hdl.handle.net/2263/101602
dc.language.iso en en_US
dc.publisher Springer en_US
dc.rights © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. The original publication is available at : http://link.springer.com/journal/520. en_US
dc.subject Symptom monitoring en_US
dc.subject Real-world data en_US
dc.subject Supportive care en_US
dc.subject SDG-03: Good health and well-being en_US
dc.title Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levels en_US
dc.type Postprint Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record