Integrating Mobile Health Technology for Symptom Management in Acute Pediatric Blood and Marrow Transplant Patients

Introduction: Pediatric Blood and Marrow Transplant (PBMT) is an intense treatment fraught with significant symptom burden for patients. Mobile health (mHealth) and wearable technologies provide patient generated health data which may enhance understanding of complex symptom patterns, trajectories, and interactions. Improved monitoring and understanding may result in the development of precision symptom management strategies, yet limited research exists for integrating these technologies into acute patient care.

Methods: We conducted a pilot study to determine the feasibility of integrating mHealth technology into symptom management for PBMT patients. Patient data includes: 1) an Apple Watch to collect objective data (heart rate, daily step count), and 2) a self-developed app to collect subjective symptom data. Patients were followed for up to 120 days, which could include both inpatient and outpatient days. Patients were asked to record within the mobile app daily and keep the wearable device (Apple Watch) on throughout each day and night with removal only to charge.

The number of days the mobile app and wearable device were used by each patient was assessed to determine compliance to study protocol. In addition, transplant, engraftment, hospital discharge, and study discharge dates were used as 4 discrete time points to determine study feasibility. For transplant and engraftment, the patient must have recorded in the app within a week of the event to be considered an interaction to account for increased fatigue and duress during these times. On completion of the study, patients also completed feasibility questionnaires and interviews.

Results: Twelve patients were approached and 10 patients enrolled in the study. Three patients withdrew early from the study citing the devices were to difficult to manage with their health status. Of the remaining 7 patients included in analysis, one went to the ICU on day 40. On average, the 7 patients charted data in the app for an average of 46.10% of their days involved in the study and the most commonly reported symptoms included pain (52%), fatigue (13%), fever (9%), and rash (9%). Patients wore the wearable device during 40.29% of their total days in the study. From their compiled 551 days in the study, this equates to 254 total days of app interaction and 222 days of using the wearable (Figure 1). Four patients completed all four discrete time points. Two patients are currently in the study (one has completed hospital discharge but not study discharge, and one has completed transplant and engraftment). For app interaction during discrete time points, the patients interacted with the mobile app 17 of 23 times. Furthermore, there was a 100% app usage during transplant and engraftment periods. When evaluating the app data jointly with the wearable data, it was determined that 71% of patients were interactive with the app and used the wearable device during transplant and 57% of patients were compliant with both the app and wearable device during engraftment.

Interview data of all patients at study completion (n=4) found the devices easy to use, useful, and helpful, with comments: "I liked it because it was easy to keep track of how I felt. I liked looking back and comparing how I felt as the days went by". However, when they felt poorly, they didn't use them as frequently, "sometimes I just didn't feel good and didn't want to use them".

Conclusion: There has been significant patient interest in participating in the study with the majority of patients approached also enrolling in the study. Study patients had variable compliance, which on average was nearly every other day. Limitations to app included patient fatigue and forgetfulness. Pain, itching, and battery life limited wearable compliance. Our findings suggest it is feasible to obtain data from mobile devices, although need to account for gaps in data due to significant symptoms and complications. Daily data collection may be difficult for acutely ill PBMT patients, however, combining both active and passive data collection measures may improve symptom cluster understanding and result in better symptom management interventions and strategies.

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