Gynecologic Cancer Clinical Trial
Official title:
SIMPRO Research Center: Integration and Implementation of PROs for Symptom Management in Oncology Practice
Deficits in the management of common symptoms cause substantial morbidity for cancer patients.Because the health care delivery system is structured to be reactive and not proactive, there are missed opportunities to optimize symptom control. Growth in Internet access and proliferation of smartphones has created an opportunity to re-engineer cancer care delivery. Electronic symptom tracking and feedback is a promising strategy to improve symptom control. Electronic patient reported outcome (ePRO) monitoring of cancer symptoms has been shown to decrease symptom burden, improve quality of life, reduce acute care and even extend survival. SIMPRO will use functioning ePRO prototypes to create and refine the electronic symptom management system eSyM
A multi-disciplinary team of investigators from 6 health systems have formed the Symptom Management IMplementation of Patient Reported Outcomes in Oncology (SIMPRO) Research Center. SIMPRO will use functioning ePRO prototypes to create and refine the electronic symptom management system eSyM. eSyM is the name of the platform the team will refine, integrate, implement and evaluate. eSyM addresses each of the 4 evidence gaps by: - Implementing eSyM in cancer centers in small, rural or community-based systems. - Integrating eSyM into the EHR (electronic health record) of the predominant vendor used nationwide. - Leveraging evidence-based tools, patient engagement, and population management. - Executing this work using the Consolidated Framework for Implementation Research across all phases to maximize the chances that eSyM and similar systems achieve their intended goals and decrease the morbidity of cancer treatment at a population level. This project contains 5 activities: 1. Obtain stakeholder feedback 2. Build and deploy eSyM 3. Pilot test eSyM 4. Pragmatic stepped-wedge cluster randomized trial 5. Integration of eSyM data to develop algorithms to estimate the risk of experiencing an outcome, including, but not limited to, ED usage and hospitalization among cancer patients ;
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