Patient record linkage for data quality assessment based on time series matching

Alphons Eggerth*, Dieter Hayn, Karl Kreiner, Sai Veeranki, Heimo Traninger, Robert Modre-Osprian, Günter Schreier

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


Background: Huge amounts of data are collected by healthcare providers and other institutions. However, there are data protection regulations, which limit their utilisation for secondary use, e.g. research. In scenarios, where several data sources are obtained without universal identifiers, record linkage methods need to be applied to obtain a comprehensive dataset. Objectives: In this study, we had the objective to link two datasets comprising data from ergometric performance tests in order to have reference values to free text annotations for assessing their data quality. Methods: We applied an iterative, distance-based time series record linkage algorithm to find corresponding entries in the two given datasets. Subsequently, we assessed the resulting matching rate. The implementation was done in Matlab. Results: The matching rate of our record linkage algorithm was 74.5% for matching patients’ records with their ergometry records. The highest rate of appropriate free text annotations was 87.9%. Conclusion: For the given scenario, our algorithm matched 74.5% of the patients. However, we had no gold standard for validating our results. Most of the free text annotations contained the expected values.

Original languageEnglish
Title of host publicationdHealth 2019 - From eHealth to dHealth - Proceedings of the 13th Health Informatics Meets Digital Health Conference
EditorsDieter Hayn, Alphons Eggerth, Gunter Schreier
PublisherIOS Press
Number of pages8
ISBN (Electronic)9781614999706
Publication statusPublished - 1 Jan 2019
Event13th Annual Conference Health Informatics Meets Digital Health - Schönbrunn Palace, Wien, Austria
Duration: 28 May 201929 May 2019

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference13th Annual Conference Health Informatics Meets Digital Health
Abbreviated titledHealth 2019
Internet address


  • Cardiac rehabilitation
  • Data analysis
  • Ergometry
  • Exercise test
  • Medical record linkage

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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