What is Connected Health and why will it change your practice?

Area of Science:

• Digital Health
• Health Informatics
• Gerontology

Background:

• Societal need to adapt health and social care for an aging population with increasing chronic diseases.
• The digital revolution presents opportunities for proactive, patient-centered 'connected' health and social care models.
• Current technological integration efforts have faced challenges, indicating technology alone is insufficient.

Purpose of the Study:

• To explore the challenges and potential of leveraging technological innovations for connected health and social care.
• To propose a framework for optimizing data sensing and analysis in home and community settings.
• To facilitate the design, implementation, and evaluation of new technology-enabled care models.

Main Methods:

• Focus on optimizing data sensing from end-users in home and community environments.
• Emphasis on person-centered monitoring protocols for accurate data harvesting.
• Analysis of large datasets to understand the relationship between community-acquired data and health status.

Main Results:

• Technological innovation is crucial but requires overcoming specific challenges in data acquisition and analysis.
• Person-centered data sensing is essential for reliable health monitoring.
• Understanding complex data relationships is a prerequisite for effective technology-enabled care models.

Conclusions:

• A successful connected health and social care model necessitates optimizing data sensing and analysis.
• Technology can transform wellness and health management across the lifespan when integrated effectively.
• Future models must prioritize patient needs and robust data strategies.