Sensor Data Integration: How can a situational awareness data integration approach in health data platforms lead to better-informed outcomes in healthcare (Preprint)

UNSTRUCTURED Data integration, the processes by which data is aggregated, interpreted, combined, and made available for use, has been key to the development and growth of many technological solutions. In health care, we are experiencing a revolution in the use of sensors to collect data on patient behaviors and experiences. Yet, the potential of these data to transform health outcomes has been limited to date. Deficits in standards, use of different terminology, different metric systems, data rights, permissioning, privacy, and security have been well documented as challenges to digital innovation. However, the cultural adoption of sensor data integration as a priority for large-scale deployment and impact on patient lives has yet to be examined. In this paper, we take an in-depth look at case studies of sensor data integration into health data platforms for clinical research and patient care to advance key considerations in order to achieve the promise of digital health to improve clinical research and patient care at scale. These considerations are designed to support optimized, holistic (i.e. anchored in value for end consumers and patients) decision making and enable more effective sensor data integration by increasing accessibility, reliability, and trustworthiness to multiple users. We share intermediate insights from our multi-stakeholder project focused on putting forward an early framework and toolkit for sensor data integration and enable more situational awareness, thereby ensuring the future success of healthcare data integration as a whole.