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Patient-reported symptom monitoring: using (big) data to improve supportive care at the macro-, meso-, and
Yan Wang1,2, Matthew J Allsop3, Joel B Epstein4,5
1Department of Health and Community Systems, School of Nursing, University of Pittsburgh, 3500 Victoria Street, Pittsburgh, PA, 15261, USA.
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.
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