PDF–ECG in Clinical Practice: A Model for Long–Term Preservation of Digital 12–lead ECG Data

Roberto Sassi, Raymond Bond, Andrew Cairns, Dewar Finlay, Daniel Guldenring, Guido Libretti, Lamberto Isola, Martino Vaglio, Roberto Poeta, Marco Campana, Claudio Cuccia, Fabio Badilini

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


BackgroundIn clinical practice, data archiving of resting 12-lead electrocardiograms (ECGs) is mainly achieved by storing a PDF report in the hospital electronic health record (EHR). When available, digital ECG source data (raw samples) are only retained within the ECG management system.ObjectiveThe widespread availability of the ECG source data would undoubtedly permit successive analysis and facilitate longitudinal studies, with both scientific and diagnostic benefits.Methods & ResultsPDF-ECG is a hybrid archival format which allows to store in the same file both the standard graphical report of an ECG together with its source ECG data (waveforms). Using PDF-ECG as a model to address the challenge of ECG data portability, long-term archiving and documentation, a real-world proof-of-concept test was conducted in a northern Italy hospital. A set of volunteers undertook a basic ECG using routine hospital equipment and the source data captured. Using dedicated web services, PDF-ECG documents were then generated and seamlessly uploaded in the hospital EHR, replacing the standard PDF reports automatically generated at the time of acquisition. Finally, the PDF-ECG files could be successfully retrieved and re-analyzed.ConclusionAdding PDF-ECG to an existing EHR had a minimal impact on the hospital’s workflow, while preserving the ECG digital data.
Original languageEnglish
Pages (from-to)776-780
JournalJournal of Electrocardiology
Issue number6
Early online date12 Aug 2017
Publication statusPublished online - 12 Aug 2017


  • ECG
  • data modelling
  • data structure
  • medical informatics


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