ArticleNPJ digital medicine2020
Outcome measures based on digital health technology sensor data: data- and patient-centric approaches.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
47 citing papers in PubMed, 93 citations in OpenAlex.
- Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease.Scientific reports · 2022Trial
- A smartphone sensor-based digital outcome assessment of multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Trial
- Smartphone-based patient-reported outcome of acute phase reaction after zoledronic acid infusion and prediction algorithm: a multicenter, prospective cohort study.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
- A scoping review on using real-world data to evaluate the effectiveness of mHealth applications.NPJ digital medicine · 2026Article
- Sensor-based digital health technologies to capture endpoints in recent clinical trials: a scoping review.NPJ digital medicine · 2026Article
- Sensor-Equipped Digital Technologies for Monitoring and Detecting Depressive Disorders: A Systematic Review.Health science reports · 2026Review
- Stride-level measurement of gait as an early sensitive marker of disability progression in ambulatory patients with multiple sclerosis.EClinicalMedicine · 2026Article
- Toward Patient-Centric Digital Monitoring of Obstructive Sleep Apnea: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Toward future diagnostics of Parkinson's disease: a perspective on multimodal motor assessment and personalized digital twins.Frontiers in aging neuroscience · 2026Article
- Preferences regarding technology to unobtrusively monitor symptoms in rheumatoid arthritis: a qualitative study using focus group discussions.Rheumatology international · 2025Article
- Digital Phenotyping of Sensation Seeking: A Machine Learning Approach Using Gait Analysis.Behavioral sciences (Basel, Switzerland) · 2025Article
- Reimagining falls prevention with insights from systems mapping on the use of millimetre-wave radar for remote health monitoring.Scientific reports · 2025Article
- Advancing the Integration of Digital Health Technologies in the Drug Development Ecosystem.Journal of medical Internet research · 2025Article
- Exploratory digital outcome measures of motor sign progression in Parkinson's disease patients treated with prasinezumab.NPJ digital medicine · 2025Article
- Recommendations for Successful Development and Implementation of Digital Health Technology Tools.Journal of medical Internet research · 2025Article
- Patient-Centric Paradigm: A Systems Thinking Approach to Enhance Healthcare.Healthcare (Basel, Switzerland) · 2025Article
- A systematic literature review of the impact and measurement of mobility impairment in rare bone diseases.Therapeutic advances in musculoskeletal disease · 2025Review
- A hybrid, iterative approach, to support the development of fit-for-purpose sensor-derived measures.Frontiers in medical technology · 2025Article
- Implementing sensor-based digital health technologies in clinical trials: Key considerations from the eCOA Consortium.Clinical and translational science · 2024Review
- Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art.NPJ digital medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital health technology tools (DHTT) are technologies such as apps, smartphones, and wearables that remotely acquire health-related information from individuals. They have the potential advantages of objectivity and sensitivity of measurement, richness of high-frequency sensor data, and opportunity for passive collection of health-related data. Thus, DHTTs promise to provide patient phenotyping at an order of granularity several times greater than is possible with traditional clinical research tools. While the conceptual development of novel DHTTs is keeping pace with technological and analytical advancements, an as yet unaddressed gap is how to develop robust and meaningful outcome measures based on sensor data. Here, we describe two roadmaps which were developed to generate outcome measures based on DHTT data: one using a data-centric approach and the second a patient-centric approach. The data-centric approach to develop digital outcome measures summarizes those sensor features maximally sensitive to the concept of interest, exemplified with the quantification of disease progression. The patient-centric approach summarizes those sensor features that are optimally relevant to patients' functioning in everyday life. Both roadmaps are exemplified for use in tracking disease progression in observational and clinical interventional studies, and with a DHTT designed to evaluate motor symptom severity and symptom experience in Parkinson's disease. Use cases other than disease progression (e.g., case-finding) are considered summarily. DHTT research requires methods to summarize sensor data into meaningful outcome measures. It is hoped that the concepts outlined here will encourage a scientific discourse and eventual consensus on the creation of novel digital outcome measures for both basic clinical research and clinical drug development.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.