A road map for remote digital health technology for motor neuron disease

Ruben P. A. van Eijk, Anita Beelen, Esther T. Kruitwagen, Deirdre Murray, Ratko Radakovic, Esther Hobson, Liam Knox, Jochem Helleman, Tom Burke, Miguel Ángel Rubio Pérez, Evy Reviers, Angela Genge, Frederik J. Steyn, Shyuan Ngo, John Eaglesham, Kit C. B. Roes, Leonard H. van den Berg, Orla Hardiman, Christopher J. McDermott

Research output: Contribution to journalArticlepeer-review

Abstract

Despite recent and potent technological advances, the real-world implementation of remote digital health technology in the care and monitoring of patients with motor neuron disease has not yet been realized. Digital health technology may increase the accessibility to and personalization of care, whereas remote biosensors could optimize the collection of vital clinical parameters, irrespective of patients’ ability to visit the clinic. To facilitate the wide-scale adoption of digital health care technology and to align current initiatives, we outline a road map that will identify clinically relevant digital parameters; mediate the development of benefit-to-burden criteria for innovative technology; and direct the validation, harmonization, and adoption of digital health care technology in real-world settings. We define two key end products of the road map: (1) a set of reliable digital parameters to capture data collected under free-living conditions that reflect patient-centric measures and facilitate clinical decision making and (2) an integrated, open-source system that provides personalized feedback to patients, health care providers, clinical researchers, and caregivers and is linked to a flexible and adaptable platform that integrates patient data in real time. Given the ever-changing care needs of patients and the relentless progression rate of motor neuron disease, the adoption of digital health care technology will significantly benefit the delivery of care and accelerate the development of effective treatments.
Original languageEnglish
Article numbere28766
JournalJournal of Medical Internet Research
Volume23
Issue number9
DOIs
Publication statusPublished - 22 Sep 2021

Keywords

  • Amyotrophic lateral sclerosis
  • Digital health care technology
  • E-health

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