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, 14 (1), 212

Measuring Disease Activity and Patient Experience Remotely Using Wearable Technology and a Mobile Phone App: Outcomes From a Pilot Study in Gaucher Disease


Measuring Disease Activity and Patient Experience Remotely Using Wearable Technology and a Mobile Phone App: Outcomes From a Pilot Study in Gaucher Disease

Aimee Donald et al. Orphanet J Rare Dis.


Background: Gaucher disease is an inherited lysosomal storage disorder of which there are three subtypes. Type 1 disease has no neurological involvement and is treatable with enzyme replacement therapy. Type 2 disease results in infant death and type 3 disease is a heterogenous disorder characterised by progressive neurological decline throughout childhood and adult life. Endeavours to find a therapy to modify neurological disease are limited by a lack of meaningful clinical outcome measures which are acceptable to patients.

Results: We present results from a pilot study utilising wearable technology to monitor physical activity as a surrogate of disease activity/severity paired with a mobile phone app allowing patients to complete self-reported outcome measures in the real world as opposed to the hospital environment. We demonstrate feasibility of the approach and highlight areas for development with this study of 21 patients, both children and adults.

Conclusions: We illustrate, where patients engage in the methodology, a rich dataset is obtainable and useful for proactive clinical care and for clinical trial outcome development.

Keywords: Gaucher; Mobile health; Wearable technology.

Conflict of interest statement

Dr. Donald has received honoraria for speaking and consulted on advisory boards with Sanofi and Oxyrane; Professor Hughes has received honoraria for speaking and advisory boards from Sanofi and Takeda; Dr. Davies is employed by Aparito and has shares with Aparito, she has offered consultancy with Prevail, Oxyrane, Lysogene and Amicus; Niamh Finnegan has received honoraria from Takeda, Amicus, Biomarin and Sanofi Genzyme; Tanya Collins-Histed has received honoraria and travel and research grants from Prevail, Oxyrane and Shire.


Fig. 1
Fig. 1
Frequency of reported events via the phone app. Legend: Pie chart showing reported events, colour coded by frequency as percentage and colour coded to depict bone pain, sleep, other event, other illness, missed school, choking, breathing, fall, tremor, diarrhoea
Fig. 2
Fig. 2
CHU9D scores by disease type. This chart shows the CHU9D domains across the x-axis and the mean scores for the domain by patient group, blue bars = type 1 disease and green bars = type 3 disease, the distribution shows the mean and 95% confidence intervals
Fig. 3
Fig. 3
Patient 005 CHU9D Responses Over Time. This chart shows a single patient (005) with time (date) on the x-axis and the y-axis shows the score at each time point for each domain of the CHU9D, reflected in a line graph (per domain (colour coded))
Fig. 4
Fig. 4
Patient 005 Reported Events. This graph records the reported events (y-axis) patient 005 recorded by date (x-axis) with a highlight of the date at which the perceived stress score (pss) value reduced
Fig. 5
Fig. 5
Patient 005 step count over time. This figure shows dates on the x-axis and the daily step count (y-axis) for patient 005, this line graph shows the change in activity over a specific period of time - highlighted on the graph

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