title: Accessing complex patient data from Arden Syntax Medical Logic Modules.
abstract: Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden Syntax Medical Logic Modules must be able to retrieve patient data from the electronic medical record in order to enable automated decision making. For patient data with a simple structure, for instance a list of laboratory results, or, in a broader view, any patient data with a list or table structure, this mapping process is straightforward. Nevertheless, if patient data are of a complex nested structure the mapping process may become tedious. Two clinical requirements - to process complex microbiology data and to decrease the time between a critical laboratory event and its alerting by monitoring Health Level 7 (HL7) communication - have triggered the investigation of approaches for providing complex patient data from electronic medical records inside Arden Syntax Medical Logic Modules.
  
  
  
  The data mapping capabilities of current versions of the Arden Syntax standard as well as interfaces and data mapping capabilities of three different Arden Syntax environments have been analyzed. We found and implemented three different approaches to map a test sample of complex microbiology data for 22 patients and measured their execution times and memory usage. Based on one of these approaches, we mapped entire HL7 messages onto congruent Arden Syntax objects.
  
  
  
  While current versions of Arden Syntax support the mapping of list and table structures, complex data structures are so far unsupported. We identified three different approaches to map complex data from electronic patient records onto Arden Syntax variables; each of these approaches successfully mapped a test sample of complex microbiology data. The first approach was implemented in Arden Syntax itself, the second one inside the interface component of one of the investigated Arden Syntax environments. The third one was based on deserialization of Extended Markup Language (XML) data. Mean execution times of the approaches to map the test sample were 497ms, 382ms, and 84ms. Peak memory usage amounted to 3MB, 3MB, and 6MB.
  
  
  
  The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with an appropriate XML data format.
authors.affiliation: Center for Communication and Information Technology, University Hospital Erlangen, Glückstraße 11, 91054 Erlangen, Germany; Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuremberg, Wetterkreuz 13, 91058 Erlangen-Tennenlohe, Germany. Electronic address: stefan.kraus@uk-erlangen.de.
authors.forename: Stefan
authors.initials: S
authors.lastname: Kraus
authors.affiliation: Center for Communication and Information Technology, University Hospital Erlangen, Glückstraße 11, 91054 Erlangen, Germany. Electronic address: martin.enders@uk-erlangen.de.
authors.forename: Martin
authors.initials: M
authors.lastname: Enders
authors.affiliation: Center for Communication and Information Technology, University Hospital Erlangen, Glückstraße 11, 91054 Erlangen, Germany; Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuremberg, Wetterkreuz 13, 91058 Erlangen-Tennenlohe, Germany. Electronic address: ulli.prokosch@imi.med.uni-erlangen.de.
authors.forename: Hans-Ulrich
authors.initials: HU
authors.lastname: Prokosch
authors.affiliation: Department of Anaesthesiology, University Hospital Erlangen, Krankenhausstraße 12, 91054 Erlangen, Germany. Electronic address: ixchel.castellanos@kfa.imed.uni-erlangen.de.
authors.forename: Ixchel
authors.initials: I
authors.lastname: Castellanos
authors.affiliation: Department of Computer Science, Chair of Computer Science 6 (Data Management), Martensstraße 3, 91058 Erlangen, Germany. Electronic address: richard.lenz@fau.de.
authors.forename: Richard
authors.initials: R
authors.lastname: Lenz
authors.affiliation: Department of Medical Informatics, Biometrics and Epidemiology, Chair of Medical Informatics, Friedrich-Alexander-University Erlangen-Nuremberg, Wetterkreuz 13, 91058 Erlangen-Tennenlohe, Germany. Electronic address: martin.sedlmayr@fau.de.
authors.forename: Martin
authors.initials: M
authors.lastname: Sedlmayr
mesh_terms: D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D057286:Electronic Health Records / Q000458:organization & administration* / Q000592:standards; D005103:Expert Systems; D006801:Humans; D007256:Information Systems / Q000458:organization & administration* / Q000592:standards; D008490:Medical Informatics; D008828:Microbiological Techniques; D011381:Programming Languages; D013997:Time Factors
keywords: Arden Syntax; Clinical decision support; Curly braces problem; Medical Logic Modules; Microbiology data