Personalized Guideline-Based Treatment Recommendations Using Natural Language Processing Techniques..."Informatics for Health," Manchester, UK, April 2017

Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization. Today, electronic representation of clinical guidelines exists as unstructured text, but is not wellintegrated with patient-specific information from electronic health record...

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Publicado en:Studies in Health Technology & Informatics Vol. 235; pp. 271 - 276
Autores principales: BECKER, Matthias, BÖCKMANN, Britta
Formato: tables/charts Journal Article
Publicado: Sage Publications Inc. 2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2017
      vid: 235
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        10.3233/978-1-61499-753-5-271
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        atl: Personalized Guideline-Based Treatment Recommendations Using Natural Language Processing Techniques..."Informatics for Health," Manchester, UK, April 2017
      aug:
        au:
          BECKER, Matthias
          BÖCKMANN, Britta
        affil: Department of Medical Informatics, University of Applied Sciences and Arts, Dortmund, Germany
      sug:
        subj:
          Practice Guidelines
          Critical Path
          Individualized Medicine
          Natural Language Processing
          United Kingdom
          Congresses and Conferences United Kingdom
          Snomed
          Unified Medical Language System
      ab: Clinical guidelines and clinical pathways are accepted and proven instruments for quality assurance and process optimization. Today, electronic representation of clinical guidelines exists as unstructured text, but is not wellintegrated with patient-specific information from electronic health records. Consequently, generic content of the clinical guidelines is accessible, but it is not possible to visualize the position of the patient on the clinical pathway, decision support cannot be provided by personalized guidelines for the next treatment step. The Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) provides common reference terminology as well as the semantic link for combining the pathways and the patient-specific information. This paper proposes a modelbased approach to support the development of guideline-compliant pathways combined with patient-specific structured and unstructured information using SNOMED CT. To identify SNOMED CT concepts, a software was developed to extract SNOMED CT codes out of structured and unstructured German data to map these with clinical pathways annotated in accordance with the systematized nomenclature.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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