Analysis of clinical documents to enable semantic interoperability

Barbara Traxler, Andreas Hannes Schuler, Emmanuel Helm

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

2 Citations (Scopus)


While there is a wealth of information available for each patient in an Electronic Health Record (EHR), information is not optimally organized for efficient use in patient care and there is still a large gap to achieve semantic and process interoperability. Current researches focus either on fully structured or non-structured clinical documents. A pre-analysis of 1000 real-world clinical documents showed, that most clinical documents are provided in a semi-structured way as level 2 HL7 Clinical Document Architecture (CDA) documents. Thus, an analysis framework is presented which also uses this semi-structure in combination with underlying models and metadata provided by the exchanging infrastructures, allowing summarization, comparison and integration of clinical information. The approach was tested using an IHE compliant EHR system. The analysis framework offers good response times and high accuracy levels. However, there is room for improvement considering processing of non-structured text and non-CDA documents.

Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications - 24th International Conference, DEXA 2013, Proceedings
Number of pages8
EditionPART 2
ISBN (Print)9783642401725
Publication statusPublished - 2013
Event24th International Conference on Database and Expert Systems Applications, DEXA 2013 - Prague, Czech Republic
Duration: 26 Aug 201329 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8056 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference24th International Conference on Database and Expert Systems Applications, DEXA 2013
Country/TerritoryCzech Republic


  • Clinical Document Architecture
  • Electronic Health Record
  • Semantic interoperability


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