Mapping the Entire Record-An Alternative Approach to Data Access from Medical Logic Modules.

OBJECTIVES: This study aimed to describe an alternative approach for accessing electronic medical records (EMRs) from clinical decision support (CDS) functions based on Arden Syntax Medical Logic Modules, which can be paraphrased as "map the entire record." METHODS: Based on an experimental Arden Syntax processor, we implemented a method to transform patient data from a commercial patient data management system (PDMS) to tree-structured documents termed CDS EMRs. They are encoded in a specific XML format that can be directly transformed to Arden Syntax data types by a mapper natively integrated into the processor. The internal structure of a CDS EMR reflects the tabbed view of an EMR in the graphical user interface of the PDMS. RESULTS: The study resulted in an architecture that provides CDS EMRs in the form of a network service. The approach enables uniform data access from all Medical Logic Modules and requires no mapping parameters except a case number. Measurements within a CDS EMR can be addressed with straightforward path expressions. The approach is in routine use at a German university hospital for more than 2 years. CONCLUSION: This practical approach facilitates the use of CDS functions in the clinical routine at our local hospital. It is transferrable to standard-compliant Arden Syntax processors with moderate effort. Its comprehensibility can also facilitate teaching and development. Moreover, it may lower the entry barrier for the application of the Arden Syntax standard and could therefore promote its dissemination.

An Abstraction Layer to Facilitate Technical Interoperability Between Medical Records and Knowledge Modules.

Integrating clinical decision support (CDS) functions into an existing hospital information system (HIS) is often a tedious task. This problem area is so pervasive that the Arden Syntax, a widely used standard for CDS functions, assigned a specific designation, the so-called "curly braces problem". It derives from a pair of curly braces used to encapsulate any parameters required for the interactions with a HIS. The traditional approach is to leave the problem area of technical interoperability entirely to the specific institution, possibly entailing a considerable amount of initial programming work. This study describes a reusable and expandable solution to this problem in the form of an abstraction layer. Our study comprised an analytical phase in which we investigated the data source access capabilities of five Arden Syntax environments. Building on the results, we implemented a working prototype that is capable of querying heterogeneous data sources, which facilitates a straightforward connection of new data sources with existing and future communication protocols and standards. From our point of view, the technical aspects of the "curly braces problem" with respect to data source access have changed over the years, insofar as technical progress lead to defacto standards for data storage, data querying and inter-system communication. An agreement on such a convention, together with the supply of commonly used data source adapters could promote the further dissemination of the Arden Syntax as a standard for representing and sharing medical knowledge.

Using Arden Syntax for the Generation of Intelligent Intensive Care Discharge Letters.

Discharge letters are an important means of communication between physicians and nurses from intensive care units and their colleagues from normal wards. The patient data management system (PDMS) used at our local intensive care units provides an export tool to create discharge letters by inserting data items from electronic medical records into predefined templates. Local intensivists criticized the limitations of this tool regarding the identification and the further processing of clinically relevant data items for a flexible creation of discharge letters. As our PDMS supports Arden Syntax, and the demanded functionalities are well within the scope of this standard, we set out to investigate the suitability of Arden Syntax for the generation of discharge letters. To provide an easy-to-understand facility for integrating data items into document templates, we created an Arden Syntax interface function which replaces the names of previously defined variables with their content in a way that permits arbitrary custom formatting by clinical users. Our approach facilitates the creation of flexible text sections by conditional statements, as well as the integration of arbitrary HTML code and dynamically generated graphs. The resulting prototype enables clinical users to apply the full set of Arden Syntax language constructs to identify and process relevant data items in a way that far exceeds the capabilities of the PDMS export tool. The generation of discharge letters is an uncommon area of application for Arden Syntax, considerably differing from its original purpose. However, we found our prototype well suited for this task and plan to evaluate it in clinical production after the next major release change of our PDMS.

PresCont: predicting protein-protein interfaces utilizing four residue properties.

An important task of computational biology is to identify those parts of a polypeptide chain, which are involved in interactions with other proteins. For this purpose, we have developed the program PresCont, which predicts in a robust manner amino acids that constitute protein-protein interfaces (PPIs). PresCont reaches state-of-the-art classification quality on the basis of only four residue properties that can be readily deduced from the 3D structure of an individual protein and a multiple sequence alignment (MSA) composed of homologs. The core of PresCont is a support vector machine, which assesses solvent-accessible surface area, hydrophobicity, conservation, and the local environment of each amino acid on the protein surface. For training and performance testing, we compiled three nonoverlapping datasets consisting of permanently formed or transient complexes, respectively. A comparison with SPPIDER, ProMate, and meta-PPISP showed that PresCont compares favorably with these highly sophisticated programs, and that its prediction quality is less dependent on the type of protein complex being considered. This balance is due to a mutual compensation of classification weaknesses observed for individual properties: For PPIs of permanent complexes, solvent-accessible surface and hydrophobicity contribute most to classification quality, for PPIs of transient complexes, the assessment of the local environment is most significant. Moreover, we show that for permanent complexes a segmentation of PPIs into core and rim residues has only a moderate influence on prediction quality. PresCont is available as a web service at http://www-bioinf.uni-regensburg.de/.