Graph-Representation of Patient Data: a Systematic Literature Review.

Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data a...

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Publicado en:Journal of Medical Systems Vol. 44; no. 4; pp. 1 - 8
Autores principales: Schrodt, Jens, Dudchenko, Aleksei, Knaup-Gregori, Petra, Ganzinger, Matthias
Formato: research systematic review tables/charts Journal Article
Publicado: Springer Nature Apr2020
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-020-1538-4
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          Schrodt, Jens
          Dudchenko, Aleksei
          Knaup-Gregori, Petra
          Ganzinger, Matthias
        affil: Institute for Medical Biometry and Informatics, Heidelberg University, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany
      sug:
        subj:
          Electronic Health Records
          Data Management
          Graphics
          Databases
          Conceptual Framework
          Human
          Systematic Review
          Medline
          Descriptive Statistics
          Data Mining
      ab: Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs. This systematic literature review aims to investigate the frontiers of the current research in the field of graphs representing and processing patient data. We want to show, which areas of research in this context need further investigation. The databases MEDLINE, Web of Science, IEEE Xplore and ACM digital library were queried by using the search terms health record, graph and related terms. Based on the "Preferred Reporting Items for Systematic Reviews and Meta-Analysis" (PRISMA) statement guidelines the articles were screened and evaluated using full-text analysis. Eleven out of 383 articles found in systematic literature review were finally included for analysis in this literature review. Most of them use graphs to represent temporal relations, often representing the connection among laboratory data points. Only two papers report that the graph data were further processed by comparing the patient graphs using similarity measurements. Graphs representing individual patients are hardly used in research context, only eleven papers considered such kind of graphs in their investigations. The potential of graph theoretical algorithms, which are already well established, could help increasing this research field, but currently there are too few papers to estimate how this area of research will develop. Altogether, the use of such patient graphs could be a promising technique to develop decision support systems for diagnosis, medication or therapy of patients using similarity measurements or different kinds of analysis.
      pubtype: Academic Journal
      doctype:
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        systematic review
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    language: English
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