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

*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

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.

Originalspracheenglisch
TiteldHealth 2019 - From eHealth to dHealth - Proceedings of the 13th Health Informatics Meets Digital Health Conference
Redakteure/-innenDieter Hayn, Alphons Eggerth, Gunter Schreier
Herausgeber (Verlag)IOS Press
Seiten210-217
Seitenumfang8
ISBN (elektronisch)9781614999706
DOIs
PublikationsstatusVeröffentlicht - 1 Jan. 2019
VeranstaltungdHealth 2019 - Schönbrunn Palace, Wien, Österreich
Dauer: 28 Mai 201929 Mai 2019
http://www.ehealth2017.at

Publikationsreihe

NameStudies in Health Technology and Informatics
Band260
ISSN (Print)0926-9630
ISSN (elektronisch)1879-8365

Konferenz

KonferenzdHealth 2019
KurztiteldHealth 2019
Land/GebietÖsterreich
OrtWien
Zeitraum28/05/1929/05/19
Internetadresse

ASJC Scopus subject areas

  • Biomedizintechnik
  • Gesundheitsinformatik
  • Gesundheits-Informationsmanagement

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