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Mov Disord. 2019 May;34(5):657-663. doi: 10.1002/mds.27671. Epub 2019 Mar 22.

A roadmap for implementation of patient-centered digital outcome measures in Parkinson's disease obtained using mobile health technologies.

Author information

1
James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, University of Cincinnati, Cincinnati, Ohio, USA.
2
Center for the Study of Movement, Cognition, and Mobility, Department of Neurology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
3
Department of Physical Therapy, Sackler Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
4
Rush Alzheimer's Disease Center and Department of Orthopedic Surgery, Rush University, Chicago, Illinois, USA.
5
HM CINAC, Hospital Universitario HM Puerta del Sur, Móstoles, Madrid, Spain.
6
Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
7
Fraunhofer Institut for Integrated Circuits, Digital Health Pathway Research Group, Erlangen, Germany.
8
Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA.
9
Discipline of Physiotherapy, Faculty of Health Sciences, The University of Sydney, Sydney, New South Wales, Australia.
10
Department of Neurology, Oregon Health & Science University, Portland Veterans Affairs Medical System, Portland, Oregon, USA.
11
APDM, Inc, Portland, Oregon, USA.
12
Parkinson's Disease and Movement Disorders Center, Division of Neurology, Department of Medicine, The Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
13
George-Huntington-Institute, Technology Park, Muenster, Germany.
14
Department of Radiology, University of Muenster, Muenster, Germany.
15
Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany.
16
Neuromotor Rehabilitation Research Group, Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
17
Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
18
Institute of Neuroscience, Newcastle University, Newcastle Upon Tyne NE4 5PL, UK.
19
Newcastle upon Tyne Hospitals National Health Service Foundation Trust, Newcastle upon Tyne, UK.
20
Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, The Netherlands.
21
Department of Neurology, Christian-Albrechts University, Kiel, Germany.

Abstract

Obtaining reliable longitudinal information about everyday functioning from individuals with Parkinson's disease (PD) in natural environments is critical for clinical care and research. Despite advances in mobile health technologies, the implementation of digital outcome measures is hindered by a lack of consensus on the type and scope of measures, the most appropriate approach for data capture (eg, in clinic or at home), and the extraction of timely information that meets the needs of patients, clinicians, caregivers, and health care regulators. The Movement Disorder Society Task Force on Technology proposes the following objectives to facilitate the adoption of mobile health technologies: (1) identification of patient-centered and clinically relevant digital outcomes; (2) selection criteria for device combinations that offer an acceptable benefit-to-burden ratio to patients and that deliver reliable, clinically relevant insights; (3) development of an accessible, scalable, and secure platform for data integration and data analytics; and (4) agreement on a pathway for approval by regulators, adoption into e-health systems and implementation by health care organizations. We have developed a tentative roadmap that addresses these needs by providing the following deliverables: (1) results and interpretation of an online survey to define patient-relevant endpoints, (2) agreement on the selection criteria for use of device combinations, (3) an example of an open-source platform for integrating mobile health technology output, and (4) recommendations for assessing readiness for deployment of promising devices and algorithms suitable for regulatory approval. This concrete implementation guidance, harmonizing the collaborative endeavor among stakeholders, can improve assessments of individuals with PD, tailor symptomatic therapy, and enhance health care outcomes.

KEYWORDS:

Parkinson's disease; mobile health technologies; remote monitoring; wearable technology

PMID:
30901495
PMCID:
PMC6520192
[Available on 2020-05-01]
DOI:
10.1002/mds.27671

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