An increasing body of raw patient data is generated on each day of a patients stay at a hospital.It is of paramount importance that critical patient information be extracted from these large data volumes and presented to the patients clinical caregivers as early as possible.Contemporary clinical alert systems attempt to provide this service with moderate success.The efficacy of the systems is limited by the fact that they are too general to fit specific patient populations or healthcare institutions.In this study we present an extendable alerting framework implemented in Arden Syntax,which can be configured to the needs and preferences of healthcare institutions and individual patient caregivers.We illustrate the potential of this alerting framework via an alert package that analyzes hematological laboratory results with data from intensive care units at the Vienna General Hospital,Austria.The results show the effectiveness of this alert package and its ability to generate key alerts while avoiding over-alerting.
Decision Support Systems,Clinical Laboratory Critical Values Infection Control
Julia Zeckl Katharina Adlassnig Renate Fossler Alexander Blacky Jeroen S.de Bruin Walter Koller Andrea Rappelsberger Klaus-Peter Adlassnig
University of Applied Sciences Technikum Wien,H(o)chst(a)dtplatz 6,A-1200 Vienna,Austria;Medexter He Medexter Healthcare GmbH,Borschkegasse 7/5,A-1090 Vienna,Austria Vienna Regional Health Insurance Fund,Karl-Aschenbrenner-Gasse 3,A-1210 Vienna,Austria VAMED-KMB Hospital Management and Operation GmbH,Spitalgasse 23,A-1090 Vienna,Austria Medexter Healthcare GmbH,Borschkegasse 7/5,A-1090 Vienna,Austria;Vienna Regional Health Insurance Fu Department of Hospital Epidemiology and Infection Control,Medical University of Vienna and Vienna Ge Section for Artificial Intelligence and Decision Support,Center for Medical Statistics,Informatics,a