Data Integrity-Based Methodology and Checklist for Identifying Implementation Risks of Physiological Sensing in...

Area of Science:

• Digital Health
• Biomedical Engineering
• Public Health

Background:

• Mobile health (mHealth) technologies offer expanded healthcare access, but integrating physiological sensors presents implementation challenges.
• A systematic methodology is needed to evaluate these challenges and mitigate associated risks in mHealth projects.

Purpose of the Study:

• To develop a systematic methodology for evaluating potential challenges and implementation risks in mHealth initiatives.
• The goal is to facilitate the deployment of mHealth with mobile physiological sensing in resource-constrained health systems.

Main Methods:

• Quantitative analysis of physiological data (pulse oximetry, respiratory rate app) from a trial with 317 children in rural Peru.
• Qualitative analysis of usability and interviews with field workers and healthcare staff to identify causes of low data integrity.
• Development of a risk assessment checklist based on identified themes and expert review.

Main Results:

• Pulse oximetry data captured in 78.36% of visits; signal quality varied among field workers.
• Qualitative analysis identified 5 key challenge categories: environment, technology, user skills, user motivation, and subject engagement.
• An actionable checklist was created to identify and evaluate potential implementation risks in mHealth projects.

Conclusions:

• A data integrity-focused methodology was developed to assess challenges and risks in sensor-based mHealth projects.
• The methodology and checklist aid implementers in focusing on critical areas like environment, technology, user factors, and engagement.
• Provides a structured evaluation protocol for planning and preparing mHealth initiatives.