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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Using connected objects in clinical research.

Jean-François Dhainaut1, Laure Huot2, Valérie Bouchara Pomar3

  • 1Laboratoire santé Ile-de-France, 75014 Paris, France.

Therapie
|February 27, 2018
PubMed
Summary
This summary is machine-generated.

Connected objects (COs) enhance clinical research by improving data quality and patient compliance. However, risks like data misuse necessitate robust security measures and clear data flow documentation for safe implementation.

Keywords:
Clinical researchConnected objectsRegulatorySecurityValidation

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Area of Science:

  • Clinical Research Technology
  • Medical Device Validation
  • Data Science in Healthcare

Background:

  • Connected objects (COs) are increasingly utilized in clinical research for diverse functions, including data collection and specific activities.
  • Validation of COs requires a multi-faceted approach encompassing technical/clinical reliability, data protection, and cybersecurity.
  • Understanding CO typology, uses, and limitations is crucial for effective implementation in research settings.

Purpose of the Study:

  • To outline the benefits and risks associated with using connected objects in clinical research.
  • To provide recommendations for the validation and secure implementation of COs in clinical studies.
  • To emphasize the importance of data protection, cybersecurity, and user involvement in CO-based research.

Main Methods:

  • The study is based on recommendations from a round table discussion involving experts in connected objects and clinical research.
  • Analysis of CO applications in various clinical study designs (observational, randomized single-group, randomized dual-group).
  • Identification and assessment of societal limits and risks associated with CO use, particularly concerning data privacy and security.

Main Results:

  • COs offer significant benefits, including improved data quality, enhanced patient compliance and pharmacovigilance, and streamlined e-cohort implementation.
  • Key risks involve the potentially intrusive nature of collected data and the possibility of data misuse.
  • A risk analysis, secure data transmission, qualified data hosts, and vulnerability assessments are essential for mitigating risks.

Conclusions:

  • Implementing COs in clinical research requires a thorough understanding of their capabilities and limitations.
  • Proactive measures, including robust security protocols, transparent data flow documentation, and regulatory anticipation, are vital.
  • Involving users from the study design phase and ensuring data security are recommended for successful and ethical CO integration.