Recent randomised evidence has demonstrated that an online symptom-reporting tool can reduce emergency department use, improve patient quality of life and overall survival in oncology care1. Further, physical activity may attenuate symptoms of disease and treatment2. New mobile technologies may remotely collect patient-reported outcomes (PROs) and patient-generated health data (PGHD) as symptom and physical activity measures.
This case study describes an innovative model of care using a mobile application (‘app’) to collect PROs and PGHD, with data integrated into the electronic health record (EHR) to support clinical decision-making in routine oncology care.
Patients were enrolled in the CancerAid app (Sydney, Australia) at Cedars-Sinai Medical Centre, an academic health system in Los Angeles, California. Patients may track 18 symptoms, recording severity, associated features, and medication efficacy. Severity alerts were inbuilt advising the patient to seek urgent medical attention if required.
The app also supported HealthKit, an Apple software framework for collecting PGHD. Physical activity data (step count, exercise minutes and weight) were recorded using smartphone sensors and connected devices.
Data collected by the CancerAid app were securely integrated within the hospital EHR. Data transmission was in compliance with relevant privacy legislation including HIPAA. Data was linked to existing medical record numbers and presented to clinical care teams using a graphical dashboard.
Implementation of an app to remotely collect PROs and PGHD, with integration into the EHR has been successful. The app has been well-accepted, with clinicians able to access longitudinal symptom and physical activity information.
CancerAid is among the first apps to make PROs and PGHD visible to clinicians within the EHR, supporting clinical decision-making in oncology care. Prospective studies on stakeholder engagement, and correlation of PGHD to patient performance status are underway. This case study may be instructive for other centres looking to integrate these data into clinical workflows.