Automated Detection of Patient Harm: Implementation and Prospective Evaluation of a Real-Time Broad-Spectrum Surveillance Application in a Hospital With Limited Resources
Abstract:Objectives: This study aimed to prospectively validate an application that automates the detection of broad categories of hospital adverse events (AEs) extracted from a basic hospital information system, and to efficiently mobilize resources to reduce the level of acquired patient harm.Methods: Data were collected from an internally designed software, extracting results from 14 triggers indicative of patient harm, querying clinical and administrative databases including all inpatient admissions (n = 8760) from… Show more
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