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Metadata Concepts for Advancing the Use of Digital Health Technologies in Clinical Research.
Badawy, Reham; Hameed, Farhan; Bataille, Lauren; Little, Max A; Claes, Kasper; Saria, Suchi; Cedarbaum, Jesse M; Stephenson, Diane; Neville, Jon; Maetzler, Walter; Espay, Alberto J; Bloem, Bastiaan R; Simuni, Tanya; Karlin, Daniel R.
Afiliação
  • Badawy R; School of Computer Science, University of Birmingham, Birmingham, United Kingdom.
  • Hameed F; Digital Medicine and Pfizer Innovation Research Lab, Early Clinical Development, Pfizer, Inc., Cambridge, Massachusetts, USA.
  • Bataille L; College of Computer and Information Science, Northeastern University, Boston, Massachusetts, USA.
  • Little MA; Global Real World Data, Strategy, Analytics & Informatics (GRWD-SAI), Analytics, Informatics & Business Intelligence, Chief Digital Office, Pfizer, Inc., New York, New York, USA.
  • Claes K; The Michael J. Fox Foundation for Parkinson's Research, New York, New York, USA.
  • Saria S; School of Computer Science, University of Birmingham, Birmingham, United Kingdom.
  • Cedarbaum JM; Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Stephenson D; UCB Biopharma, Brussels, Belgium.
  • Neville J; Machine Learning and Healthcare Laboratory, Departments of Computer Science, Statistics, and Health Policy, Malone Center for Engineering in Healthcare, and Armstrong Institute for Patient Safety and Quality, Johns Hopkins University, Baltimore, Maryland, USA.
  • Maetzler W; Biogen, Cambridge, Massachusetts, USA.
  • Espay AJ; Critical Path Institute, Tucson, Arizona, USA.
  • Bloem BR; Clinical Data Interchange Standards Consortium, Austin, Texas, USA.
  • Simuni T; Department of Neurology, Christian Albrecht University, Kiel, Germany.
  • Karlin DR; James J. and Joan A. Gardner Family Center for Parkinson's Disease and Movement Disorders, University of Cincinnati, Cincinnati, Ohio, USA.
Digit Biomark ; 3(3): 116-132, 2019.
Article em En | MEDLINE | ID: mdl-32175520
ABSTRACT
Digital health technologies (smartphones, smartwatches, and other body-worn sensors) can act as novel tools to aid in the diagnosis and remote objective monitoring of an individual's disease symptoms, both in clinical care and in research. Nonetheless, such digital health technologies have yet to widely demonstrate value in clinical research due to insufficient data interpretability and lack of regulatory acceptance. Metadata, i.e., data that accompany and describe the primary data, can be utilized to better understand the context of the sensor data and can assist in data management, data sharing, and subsequent data analysis. The need for data and metadata standards for digital health technologies has been raised in academic and industry research communities and has also been noted by regulatory authorities. Therefore, to address this unmet need, we here propose a metadata set that reflects regulatory guidelines and that can serve as a conceptual map to (1) inform researchers on the metadata they should collect in digital health studies, aiming to increase the interpretability and exchangeability of their data, and (2) direct standard development organizations on how to extend their existing standards to incorporate digital health technologies. The proposed metadata set is informed by existing standards pertaining to clinical trials and medical devices, in addition to existing schemas that have supported digital health technology studies. We illustrate this specifically in the context of Parkinson's disease, as a model for a wide range of other chronic conditions for which remote monitoring would be useful in both care and science. We invite the scientific and clinical research communities to apply the proposed metadata set to ongoing and planned research. Where the proposed metadata fall short, we ask users to contribute to its ongoing revision so that an adequate degree of consensus can be maintained in a rapidly evolving technology landscape.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Digit Biomark Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Guideline Idioma: En Revista: Digit Biomark Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Reino Unido