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Background: Public health authorities and healthcare professionals are obliged to ensure high quality health service. Because of the high variability of the utilisation of blood and blood components, benchmarking is indicated in transfusion medicine., Objectives: Implementation and validation of a benchmarking framework for Patient Blood Management (PBM) based on the report from the second Austrian Benchmark trial., Methods: Core modules for automatic report generation have been implemented with KNIME (Konstanz Information Miner) and validated by comparing the output with the results of the second Austrian benchmark trial., Results: Delta analysis shows a deviation <0.1% for 95% (max. 1.4%)., Conclusion: The framework provides a reliable tool for PBM benchmarking. The next step is technical integration with hospital information systems.

The goal of this study was to examine whether Schematron schemas can be generated from archetypes. The openEHR Java reference API was used to transform an archetype into an object model, which was then extended with context elements. The model was processed and the constraints were transformed into corresponding Schematron assertions. A prototype of the generator for the reference model HL7 v3 CDA R2 was developed and successfully tested. Preconditions for its reusability with other reference models were set. Our results indicate that an automated generation of Schematron schemas is possible with some limitations.

To increase the patient's acceptance of electronic health records and understanding for their laboratory findings a web application was developed which presents all parameters and possible deviations of standard values in a clear way and visualizes the time based trend of all recorded parameters graphically. Documents corresponding to the Clinical document architecture (CDA) R2 laboratory reports standard and a rapid prototyping framework called Groovy on Grails were used. This work shows, that it is possible to create a useful, standards based tool for patients and physicians with comparatively few resources - an application that could be in similar form a part of an electronic Health Record (EHR) system like the Austrian electronic Health Record (ELGA).

Expectations and requirements concerning the identification and surveillance of healthcare-associated infections (HAIs) are increasing, calling for differentiated automated approaches. In an attempt to bridge the "definition swamp" of these infections and serve the needs of different users, we improved the monitoring of nosocomial infections (MONI) software to create better surveillance reports according to consented national and international definitions, as well as produce infection overviews on complex clinical matters including alerts for the clinician's ward and bedside work. MONI contains and processes surveillance definitions for intensive-care-unit-acquired infections from the European Centre for Disease Prevention and Control, Sweden, as well as the Centers for Disease Control and Prevention, USA. The latest release of MONI also includes KISS criteria of the German National Reference Center for Surveillance of Nosocomial Infections. In addition to these "classic" surveillance criteria, clinical alert criteria--which are similar but not identical to the surveillance criteria--were established together with intensivists. This is an important step to support both infection control and clinical personnel; and--last but not least--to foster co-evolution of the two groups of definitions: surveillance and alerts.