Proactive population health management in the context of a regional health information exchange using standards-based decision support.

The clinic-based healthcare model does not deliver high quality, cost-effective care to populations of patients. Despite public perception that aggressive investment in information technology will lead to improvements in the safety and quality of healthcare delivery, there is little evidence that health information technology can be used to promote population-based health management. This paper describes the use of a standards-based clinical decision support system to facilitate proactive population health management using data from a regional health information exchange (HIE) network. The initial release of this system was designed to detect ten sentinel health events related to hospitalization, emergency department (ED) utilization, and care coordination in a population of 36,000 individuals. In an analysis of 11,899 continuously enrolled patients from a single county over a six-month period, 2,285 unique patients experienced 7,226 sentinel health events. The most common events were ED utilization for low severity conditions (2,546), two or more missed appointments within a 60-day period (1,728), ED encounters for patients with asthma (1,220), and three or more ED encounters within 90 days (731). Logistic regression analysis identified patients aged 19-64 as the population most likely to have sentinel health events. In addition to presenting data demonstrating the feasibility of population health management in the context of an HIE, this paper also includes lessons learned from the development, implementation, and operational support of the population health management system.

Duke Scholars

Author David Franklin Lobach Family Medicine and Community Health

Author Kevin J. Anstrom Biostatistics & Bioinformatics, Division of Biostatistics

Author Eric Leo Eisenstein Medicine, Cardiology

Author Frederick Salvatore Johnson Family Medicine and Community Health, Community Health