Data Integrity-Based Methodology and Checklist for Identifying Implementation Risks of Physiological Sensing in Mobile Health Projects: Quantitative and Qualitative Analysis.

Jia Zhang Laura Tüshaus Nestor Nuño Monica Moreo Hector Verastegui Stella Maria Hartinger Daniel Mäusezahl Walter Karlen

Published in: JMIR mHealth and uHealth (2018)

We developed a data integrity-based methodology to assess the potential challenges and risks of sensor-based mHealth projects. Aiming at improving data integrity, implementers can focus on the evaluation of environment, technology, user skills, user motivation, and subject engagement challenges. We provide a checklist to assist mHealth implementers with a structured evaluation protocol when planning and preparing projects.

Keyphrases

quality improvement
electronic health record
big data
human health
randomized controlled trial
healthcare
primary care
social media
systematic review
high resolution
machine learning
mass spectrometry
artificial intelligence
clinical evaluation