Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

Taylor, Kirsten I.; Staunton, Hannah; Lipsmeier, Florian; Nobbs, David; Lindemann, Michael

doi:10.1038/s41746-020-0305-8

Cited by 67 publications

(67 citation statements)

References 32 publications

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“…Besides environmental sensors, passive sensing through ubiquitous devices such as smartphones and wearables can provide objective, rich, and granular data on clinically robust measures [24]. For example, a variety of daily activities (eg, boarding transport vehicles, washing dishes, or talking) of a person with dementia can be inferred from data sensed by his/her smartphones' microphone and accelerometer [25].…”

Section: Designing For People With Dementiamentioning

confidence: 99%

Smart Home Sensing and Monitoring in Households With Dementia: User-Centered Design Approach

Tiersen¹,

Batey²,

Harrison³

et al. 2021

JMIR Aging

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Background As life expectancy grows, so do the challenges of caring for an aging population. Older adults, including people with dementia, want to live independently and feel in control of their lives for as long as possible. Assistive technologies powered by artificial intelligence and internet of things devices are being proposed to provide living environments that support the users’ safety, psychological, and medical needs through remote monitoring and interventions. Objective This study investigates the functional, psychosocial, and environmental needs of people living with dementia, their caregivers, clinicians, and health and social care service providers toward the design and implementation of smart home systems. Methods We used an iterative user-centered design approach comprising 9 substudies. First, semistructured interviews (9 people with dementia, 9 caregivers, and 10 academic and clinical staff) and workshops (35 pairs of people with dementia and caregivers, and 12 health and social care clinicians) were conducted to define the needs of people with dementia, home caregivers, and professional stakeholders in both daily activities and technology-specific interactions. Then, the spectrum of needs identified was represented via patient–caregiver personas and discussed with stakeholders in a workshop (14 occupational therapists; 4 National Health Service pathway directors; and 6 researchers in occupational therapy, neuropsychiatry, and engineering) and 2 focus groups with managers of health care services (n=8), eliciting opportunities for innovative care technologies and public health strategies. Finally, these design opportunities were discussed in semistructured interviews with participants of a smart home trial involving environmental sensors, physiological measurement devices, smartwatches, and tablet-based chatbots and cognitive assessment puzzles (10 caregivers and 2 people with dementia). A thematic analysis revealed factors that motivate household members to use these technologies. Results Outcomes of these activities include a qualitative and quantitative analysis of patient, caregiver, and clinician needs and the identification of challenges and opportunities for the design and implementation of remote monitoring systems in public health pathways. Conclusions Participatory design methods supported the triangulation of stakeholder perspectives to aid the development of more patient-centered interventions and their translation to clinical practice and public health strategy. We discuss the implications and limitations of our findings, the value and the applicability of our methodology, and directions for future research.

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Section: Designing For People With Dementiamentioning

confidence: 99%

Smart Home Sensing and Monitoring in Households With Dementia: User-Centered Design Approach

Tiersen¹,

Batey²,

Harrison³

et al. 2021

JMIR Aging

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“…the development of domain-specific and overall MS outcome measures based on digital health technology 32. ConclusionUsing a consumer smartphone device, self-administered at-home active tests and passive monitoring assessed the functional ability across three key domains affected by MS: cognition, upper extremity function, and gait and balance.…”

mentioning

confidence: 99%

A smartphone sensor-based digital outcome assessment of multiple sclerosis

Montalbán¹,

Graves

Midaglia

et al. 2021

Mult Scler

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Background: Sensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care. Objective: The aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app. Methods: In a 24-week study (clinicaltrials.gov: NCT02952911), smartphone-based active tests and passive monitoring assessed cognition (electronic Symbol Digit Modalities Test), upper extremity function (Pinching Test, Draw a Shape Test), and gait and balance (Static Balance Test, U-Turn Test, Walk Test, Passive Monitoring). Intraclass correlation coefficients (ICCs) and age- or sex-adjusted Spearman’s rank correlation determined test–retest reliability and correlations with clinical and magnetic resonance imaging (MRI) outcome measures, respectively. Results: Seventy-six people with MS (PwMS) and 25 healthy controls were enrolled. In PwMS, ICCs were moderate-to-good (ICC(2,1) = 0.61–0.85) across tests. Correlations with domain-specific standard clinical disability measures were significant for all tests in the cognitive ( r = 0.82, p < 0.001), upper extremity function (|r|= 0.40–0.64, all p < 0.001), and gait and balance domains ( r = −0.25 to −0.52, all p < 0.05; except for Static Balance Test: r = −0.20, p > 0.05). Most tests also correlated with Expanded Disability Status Scale, 29-item Multiple Sclerosis Impact Scale items or subscales, and/or normalized brain volume. Conclusion: The Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.

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“…However, DHT raise substantial challenges including harmonization, standardization, validation, data storage and sharing, and privacy. Individual stakeholder groups are providing insightful recommendations for how some of these gaps can be addressed (e.g., [59, 60]). Tackling challenges collectively by advancing data-driven solutions and sharing costs and risks, as well as embracing open science, will be key to accelerating the adoption and regulatory acceptance of DHT and their use in clinical trials.…”

Section: Future Directionsmentioning

confidence: 99%

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

et al. 2020

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Innovative tools are urgently needed to accelerate the evaluation and subsequent approval of novel treatments that may slow, halt, or reverse the relentless progression of Parkinson disease (PD). Therapies that intervene early in the disease continuum are a priority for the many candidates in the drug development pipeline. There is a paucity of sensitive and objective, yet clinically interpretable, measures that can capture meaningful aspects of the disease. This poses a major challenge for the development of new therapies and is compounded by the considerable heterogeneity in clinical manifestations across patients and the fluctuating nature of many signs and symptoms of PD. Digital health technologies (DHT), such as smartphone applications, wearable sensors, and digital diaries, have the potential to address many of these gaps by enabling the objective, remote, and frequent measurement of PD signs and symptoms in natural living environments. The current climate of the COVID-19 pandemic creates a heightened sense of urgency for effective implementation of such strategies. In order for these technologies to be adopted in drug development studies, a regulatory-aligned consensus on best practices in implementing appropriate technologies, including the collection, processing, and interpretation of digital sensor data, is required. A growing number of collaborative initiatives are being launched to identify effective ways to advance the use of DHT in PD clinical trials. The Critical Path for Parkinson’s Consortium of the Critical Path Institute is highlighted as a case example where stakeholders collectively engaged regulatory agencies on the effective use of DHT in PD clinical trials. Global regulatory agencies, including the US Food and Drug Administration and the European Medicines Agency, are encouraging the efficiencies of data-driven engagements through multistakeholder consortia. To this end, we review how the advancement of DHT can be most effectively achieved by aligning knowledge, expertise, and data sharing in ways that maximize efficiencies.

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Outcome measures based on digital health technology sensor data: data- and patient-centric approaches

Cited by 67 publications

References 32 publications

Smart Home Sensing and Monitoring in Households With Dementia: User-Centered Design Approach

Smart Home Sensing and Monitoring in Households With Dementia: User-Centered Design Approach

A smartphone sensor-based digital outcome assessment of multiple sclerosis

Precompetitive Consensus Building to Facilitate the Use of Digital Health Technologies to Support Parkinson Disease Drug Development through Regulatory Science

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