Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement–the Mobilise-D study protocol

Abstract

Background The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. Methods/design The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson’s Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. Discussion The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. Trial registration ISRCTN12051706.

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease

“…Participants with PD were recruited as part of the Medical Research Council (MRC) Confidence in Concept (CiC) funded study “Translating digital healthcare to enhance clinical management: evaluating the effect of medication on mobility in people with Parkinson's Disease” (ISRCTN Number: 13156149, https://www.isrctn.com/ISRCTN13156149 ). This study is also a sub-study of the Mobilise-D—Clinical Validation Study (REC reference: 20/PR/0792) ( 21 ).…”

“…Eligibility criteria are the same as previously published for the Mobilise-D project ( 21 ) and are displayed in Table 1 . In the later stages of the disease (Hoehn and Yahr stages IV and V), loss of independence can decrease the ability to perform activities of daily living, this induces difficulties to remotely monitor mobility with IMUs.…”

Estimating real-world walking speed from a single wearable device: analytical pipeline, results and lessons learnt from the Mobilise-D technical validation study

“…Through the extensive real-world and laboratory validation across multiple cohorts, this study represents, to the best of our knowledge, the most accurate estimate of the expected error ranges of a lower-back wearable device for estimation of walking speed. The presented state-of-the-art algorithms-pipelines could reliably estimate DMOs across a wide range of scenarios, providing a solid foundation for future studies to establish their clinical meaningfulness 42 . Our results showed that various parameters can in uence DMO performance and multi-faceted analysis is crucial for understanding of the capabilities of any DMO pipeline.…”

“…Thus, we would recommend using all (WBs > 10 s) to include a balance between capturing a su cient number of WBs for patients with a variety of condition severities, whilst ensuring walking speed can still be quanti ed reliably. Future clinical validation studies with a larger number of participants with severe gait impairments are required to con rm the reported error ranges for speci c disease populations and can con rm the in uence of WB duration upon the functional insight of mobility provided by walking speed 42 .…”

“…Thus, this provides further justi cation to our recommendation that medium length WBs provide the right balance between functional relevance and accuracy. Exploration of the clinical properties of walking speed encapsulated within these WBs, will become a topic of research in further investigated in on-going clinical validation efforts 42 . Furthermore, measurements with cohorts consisting of predominantly slow walkers will likely result in larger error ranges.…”