Informatics' role in integrating population and patient-level knowledge to improve care transitions in complex chronic disease

Hospital discharges are times of increased vulnerability for people with chronic disease and often result in costly re-hospitalizations because of inadequate care coordination. Although population and patient-centered models of complexity use different data sources, definitions, and methods, they share hospitalization rates as an outcome measure. This paper proposes a Complexity Segmentation and Care Integration Model (CSCIM) that integrates population and primary-care data, using a chronic-disease algorithm that divides the population into cohorts based on complexity and comorbidity. Based on the CSCIM, opportunities to improve care transitions for complex cases using health informatics are identified at the health system, population, and primary-practice level. The goal is to improve care continuity for complex patients as they move across settings through proactive, timely, holistic, coordinated, and patient-centered care. Nurse care coordinators, supported with informatics, lead in this model; ultimately, resulting in reduced rates of hospitalization, cost savings, improved quality, and greater satisfaction with care.