UNSTRUCTURED
Introduction:
Since the start of the COVID-19 pandemic there has been a rapid transition to and uptake of telehealth across the US, primarily involving virtual clinic visits. The promise of technology in health, however, involves more than virtual visits to a clinician and includes sensors and devices surrounding a person in their home and community to facilitate health and well-being. One ideal impact of technology on health is one where environments in which people are born, live, play, work, and grow old are networked, intelligent, and responsive, automatically promoting health and preventing disease in a way that is personalized to each individual within it. How can we rationally and systematically architect such connected environments for health?
In this viewpoint paper we propose a methodology to engineer connected health systems around patients that is rooted in the pathophysiology of disease familiar to clinicians and providers. We apply the approach to a hypothetical patient with diabetes and discuss the significance of the methodology to health in an increasingly networked world.
Methods:
A systematic methodology to use the pathophysiologic basis of disease to guide architecture of connected health systems is given below:
1. Identify the intended level of intervention and practice level of the system
2. Develop personas that represent the lived experience of the individual
3. Map initial pathophysiologic pathways
4. Expand pathophysiologic map to include determinants
5. Identify targets for sensing and intervening
6. Connect system of sensors and devices through tailored machine intelligence
Results:
This methodology resulted in the development of personas for obesity and pre-diabetes, development of an initial map of pathophysiologic pathways, an expanded pathophysiologic map that included determinants, and usage of the pathophysiologic maps to identify targets for sensing and intervening, and description of architectural requirements for a connected system of sensors and devices with tailored machine intelligence for deployment around the patient.
Discussion:
The above methodology allows a systematic, clinically based thought process to be employed in deploying a responsive and intelligent connected health system around a given patient. It helps to organize existing technologies and can also be used to reveal gaps where innovation can complete the arc of a complete system for patients with a permutation of conditions.