Upgrading the ESSENCE Health Monitoring System for Increased Epidemiological Relevance and User Participation

Current implementations of the Electronic Surveillance System for the Enhancement of Community-based Epidemics (ESSENCE) are limited in data sources employed and do not use data fields related to case severity. In some contexts, staff members monitoring many conditions and locations thus see nonspecific, sometimes excessive alerting, which reduces system usage. This effort exploits additional information from system data sources and more specific information from new sources to filter alerts adjustably by clinical relevance. This information is taken directly from disposition and evaluation codes, procedure codes and test orders and is also inferred from age distributions and temporal visit patterns. The goal is to combine statistical aberration detection and clinical knowledge according to available data characteristics to display anomalies with viewable criteria indicating that they should not be ignored. The validation approach is to evaluate criteria on large datasets with known outbreaks. The first study stage was restricted to outpatient visit records; subsequent stages include laboratory and radiology test results and filled prescription records. First-stage results were that alert flags are reduced by 50% at full service facilities and by much more at smaller ones. Severity criteria for remaining flags are readily inspected. In evaluation with datasets taken from five known outbreak datasets, detection timeliness and sensitivity were retained. The presentation will also discuss operational concepts for improved user training and acceptance.