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

dc.contributor.authorWang, Yan
dc.contributor.authorAllsop, Matthew J.
dc.contributor.authorEpstein, Joel B.
dc.contributor.authorHowell, Doris
dc.contributor.authorRapoport, Bernardo Leon
dc.contributor.authorSchofield, Penelope
dc.contributor.authorVan Sebille, Ysabella
dc.contributor.authorThong, Melissa S.Y.
dc.contributor.authorWalraven, Iris
dc.contributor.authorWolf, Julie Ryan
dc.contributor.authorVan den Hurk, Corina J.G.
dc.date.accessioned2025-03-19T10:55:34Z
dc.date.available2025-03-19T10:55:34Z
dc.date.issued2024-03
dc.descriptionDATA AVAILABILITY : The data that support the findings of this study are available on request from the corresponding author.en_US
dc.description.abstractPURPOSE : 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.departmentImmunologyen_US
dc.description.librarianhj2024en_US
dc.description.sdgSDG-03:Good heatlh and well-beingen_US
dc.description.urihttp://link.springer.com/journal/520en_US
dc.identifier.citationWang, 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.issn0941-4355 (print)
dc.identifier.issn1433-7339 (online)
dc.identifier.other10.1007/s00520-024-08373-x
dc.identifier.urihttp://hdl.handle.net/2263/101602
dc.language.isoenen_US
dc.publisherSpringeren_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.subjectSymptom monitoringen_US
dc.subjectReal-world dataen_US
dc.subjectSupportive careen_US
dc.subjectSDG-03: Good health and well-beingen_US
dc.titlePatient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and micro-levelsen_US
dc.typePostprint Articleen_US

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