gms | German Medical Science

Brücken bauen – von der Evidenz zum Patientenwohl: 19. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin e. V.

Deutsches Netzwerk Evidenzbasierte Medizin e. V.

08.03. - 10.03.2018, Graz

Methods for the evaluation of data quality in medical registries

Meeting Abstract

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  • author presenting/speaker Andreas Dorn - Medizinische Universität Graz, Institut für Medizinische Informatik, Statistik und Dokumentation
  • Andrea Berghold - Medizinische Universität Graz, Institut für Medizinische Informatik, Statistik und Dokumentation

Brücken bauen – von der Evidenz zum Patientenwohl. 19. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin. Graz, Österreich, 08.-10.03.2018. Düsseldorf: German Medical Science GMS Publishing House; 2018. Doc18ebmP3-10

doi: 10.3205/18ebm092, urn:nbn:de:0183-18ebm0924

Veröffentlicht: 6. März 2018

© 2018 Dorn et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Background: Medical registries are systematically collected and clearly defined sets of health and demographic data of patients with specific health characteristics [1]. They play an important role in clinical-epidemiological, health services and etiology research, quality assurance and health policy. Furthermore, concerns about the conclusions of Randomized Controlled Trials which are designed under strict and controlled conditions to provide information on the efficacy of treatments refer mostly to their generalizability to broader patient populations. The evidence should be supported by real-world data. Medical registries can be a source for real-world data [2]. However, the value strongly depends on the quality of the data. High data quality in these registries is a crucial requirement for correct interpretation, thus for the results gained from them. This project aims at identifying methods for the evaluation of data quality and to evaluate their applicability to the special requirements of a medical registry.

Methods: Characteristics and terminology of data quality and medical registries were examined. Completeness, comparability, validity and timeliness were found as particularly vital criteria for the measurement of data quality [3]. Based on these findings a thorough literature review about methods for the evaluation of data quality is performed. 104 papers were identified by the literature search and after examination of the titles and abstracts, 78 papers were found to meet the inclusion criteria. The methods for the evaluation of data quality are now extracted from the papers. As a case study these methods will be applied to the data of a registry, namely the Austrian Breast Cancer Screening Program. The methods will be compared and evaluated on their suitability for the application on medical registries.


References

1.
Arts DGT, De Keizer NF, Scheffer GJ. Defining and improving data quality in medical registries: a literature review, case study, and generic framework. J Am Med Inform Assoc. 2002 Nov-Dec;9(6):600-11.
2.
Annemans L, Aristides M, Kubin M. Real-life data: A growing need. ISPOR Connections. 2007;13:8-12.
3.
Parkin DM, Bray F. Evaluation of data quality in the cancer registry: Principles and methods Part II. Completeness. Eur J Cancer. 2009;45(5):756-64.