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  2. Continuous Improvement Of Digital Health Applications Linked To Real-world Performance Monitoring: Safe Moving Targets?
  1. Home
  2. Continuous Improvement Of Digital Health Applications Linked To Real-world Performance Monitoring: Safe Moving Targets?

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Continuous Improvement of Digital Health Applications Linked to Real-World Performance Monitoring: Safe Moving

Stephen Gilbert1,2, Andreia Pimenta2, Ashley Stratton-Powell3

  • 1Else Kröner Fresenius Center for Digital Health, Technische Universität Dresden, Dresden, Germany.

Mayo Clinic Proceedings. Digital Health
|April 10, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

High-quality real-world data is crucial for optimizing digital health applications and ensuring patient safety. This study explores methods for gathering this data, identifying key challenges and policy gaps.

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Area of Science:

  • Digital Health
  • Health Informatics
  • Regulatory Science

Background:

  • Real-time, high-quality performance data is essential for digital health applications, especially with on-market updates.
  • Developers need to ensure applications function accurately in real-world settings.
  • Regulatory bodies increasingly recognize the importance of real-world performance monitoring.

Purpose of the Study:

  • To describe real-world data gathering practices for digital health applications.
  • To identify challenges and uncertainties in current data collection methods.
  • To highlight health policy gaps related to real-world data.

Main Methods:

  • Utilizing patient-reported outcomes (PROs) and clinician-reported outcomes (CROs).
  • Employing high-quality surveys for data collection.
  • Analyzing postmarket surveillance data distinct from clinical investigations.
  • Main Results:

    • Real-world data offers insights from broader patient populations than clinical studies.
    • Postmarket surveillance surveys can vary in quality and be subject to bias if poorly designed.
    • Current practices highlight a need for standardized, high-quality data gathering.

    Conclusions:

    • Effective real-world data collection is vital for digital health application safety and efficacy.
    • Addressing challenges in data quality and bias is necessary for reliable insights.
    • Policy development is needed to support robust real-world data gathering and utilization.