Identifying Improvements in Healthcare Systems Engineering Models for Chronic Care and Precision Medicine Applications

Abstract

Over 48 million Americans are currently living with a chronic disease. To effectively manage chronic diseases, there is a need for interventions at multiple points in the care process, with integrated health information technology (HIT) systems to assist with information coordination for patients, caregivers, and providers. Systems engineering models can be useful for minimizing unintended consequences with HIT implementation; however, there are gaps in applying such models to precision medicine and chronic care management. The objective of this work was to review the key attributes of systems engineering models for chronic disease management and precision medicine applications. Several key attributes were selected to address: granularity, temporal dynamics, sociotechnical factors, chronic care applications, and HIT integration. The analysis found that the most difficult challenge is depicting granularity and temporal dynamics in systems engineering implementations so that they can still be easily applied by practitioners. Future work aims to determine appropriate systems engineering interventions and implementations that integrate information architecture, systems granularity, and event dynamics for longitudinal coordinated care activities.