RESUMEN
Arden Syntax, a medical knowledge representation and processing language for clinical decision support tasks supervised by Health Level Seven International (HL7), was extended with HL7's Fast Healthcare Interoperability Resources (FHIR) constructs to allow standardized data access. The new version, Arden Syntax version 3.0, was successfully balloted as part of the audited, consensus-based, iterative HL7 standards development process.
Asunto(s)
Estándar HL7 , Lenguaje , ConsensoRESUMEN
BACKGROUND: The diagnosis - and hence definitions - of healthcare-associated infections (HAIs) rely on microbiological laboratory test results in specific constellations. OBJECTIVES: To construct a library that provides interoperable building blocks for the analysis of microbiological laboratory test results. METHODS: We used Java for preprocessing raw microbiological laboratory test results and Arden Syntax for knowledge-based querying of data based on microbiology information elements used in European surveillance criteria for HAIs. To test the library and quantify how often these information elements occur in the data, we performed a retrospective cohort study on adult patients admitted for at least 24 hours to an intensive care unit at the Vienna General Hospital in 2013. RESULTS: We identified eleven information elements for which information was electronically available. These elements were identified positively 1,239 times in 1,184 positive microbiology tests from 563 patients. DISCUSSION: The availability of a library for the analysis of microbiology laboratory test results in HAI terms facilitates electronic HAI surveillance.
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Infección Hospitalaria , Bases del Conocimiento , Programas Informáticos , Humanos , Vigilancia de la Población , Estudios RetrospectivosRESUMEN
The creation of clinical decision support systems has received a strong impulse over the last years, but their integration into a clinical routine has lagged behind, partly due to a lack of interoperability and trust by physicians. We report on the implementation of a clinical foundation framework in Arden Syntax, comprising knowledge units for (a) preprocessing raw clinical data, (b) the determination of single clinical concepts, and (c) more complex medical knowledge, which can be modeled through the composition and configuration of knowledge units in this framework. Thus, it can be tailored to clinical institutions or patients' caregivers. In the present version, we integrated knowledge units for several infection-related clinical concepts into the framework and developed a clinical event monitoring system over the framework that employs three different scenarios for monitoring clinical signs of bloodstream infection. The clinical event monitoring system was tested using data from intensive care units at Vienna General Hospital, Austria.
Asunto(s)
Sistemas de Apoyo a Decisiones Clínicas , Unidades de Cuidados Intensivos , Austria , Humanos , Proyectos PilotoRESUMEN
An increasing body of raw patient data is generated on each day of a patient's stay at a hospital. It is of paramount importance that critical patient information be extracted from these large data volumes and presented to the patient's 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.