Data use and effectiveness in electronic surveillance of healthcare associated infections in the 21st century: a systematic review. (14th January 2014)

• Record Type: Journal Article
• Authors: de Bruin, Jeroen S; Seeling, Walter; Schuh, Christian
• Is Part Of: Journal of the American Medical Informatics Association. Volume 21:Number 5(2014:Sep.)
• Page Start: 942
• Page End: 951
• Publication Date: 2014-01-14
• Subjects: Review Literature as Topic -- Infection Control -- Cross Infection/methods -- Expert Systems -- Automatic Data Processing; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1136/amiajnl-2013-002089
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Objective As more electronic health records have become available during the last decade, we aimed to uncover recent trends in use of electronically available patient data by electronic surveillance systems for healthcare associated infections (HAIs) and identify consequences for system effectiveness. Methods A systematic review of published literature evaluating electronic HAI surveillance systems was performed. The PubMed service was used to retrieve publications between January 2001 and December 2011. Studies were included in the review if they accurately described what electronic data were used and if system effectiveness was evaluated using sensitivity, specificity, positive predictive value, or negative predictive value. Trends were identified by analyzing changes in the number and types of electronic data sources used. Results 26 publications comprising discussions on 27 electronic systems met the eligibility criteria. Trend analysis showed that systems use an increasing number of data sources which are either medico-administrative or clinical and laboratory-based data. Trends on the use of individual types of electronic data confirmed the paramount role of microbiology data in HAI detection, but also showed increased use of biochemistry and pharmacy data, and the limited adoption of clinical data and physician narratives. System effectiveness assessments indicate that the use of heterogeneous data sources results in higher system sensitivity at the expense of specificity. Conclusions Driven by the increased availability of electronic patient data, electronic HAI surveillance systems use more data, making systems more sensitive yet less specific, but also allow systems to be tailored to the needs of healthcare institutes' surveillance programs.