Quality aspects of Dutch general practice-based data: a conceptual approach
Background. General practice–based data, collected within general practice registration networks (GPRNs), are widely used in research. The quality of the data is important but the recording criteria about what type of information is collected and how this information should be recorded differ between GPRNs. Objective. We aim to identify aspects that describe the quality of general practice-based data in the Netherlands. Methods. To investigate the quality aspects, we used the method of concept mapping, a structured conceptualization process for a complex multi-dimensional topic. We explored th... Mehr ...
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Dokumenttyp: | TEXT |
Erscheinungsdatum: | 2013 |
Verlag/Hrsg.: |
Oxford University Press
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Schlagwörter: | Original Article |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27023805 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://fampra.oxfordjournals.org/cgi/content/short/cms082v1 |
Background. General practice–based data, collected within general practice registration networks (GPRNs), are widely used in research. The quality of the data is important but the recording criteria about what type of information is collected and how this information should be recorded differ between GPRNs. Objective. We aim to identify aspects that describe the quality of general practice-based data in the Netherlands. Methods. To investigate the quality aspects, we used the method of concept mapping, a structured conceptualization process for a complex multi-dimensional topic. We explored the ideas of representatives from 10 Dutch GPRNs on the quality of general practice–based data in five steps: preparation, generation of statements, structuring, representation and interpretation. In a brainstorm session, 10 experts generated statements about good data quality from general practice, which we completed with information from the literature. In total, 18 experts participated in the ranking and clustering of the statements. These results were analysed using ARIADNE software, using a combination of principal component analysis and cluster analysis techniques. Finally, the clusters were labelled based on their content. Results. A total of 72 statements were analysed, which resulted in a two-dimensional picture with six clusters, ‘complete health record’, ‘coding of information’, ‘episode oriented recording’, ‘diagnostic validity’, ‘recording agreements’ and ‘residual category’. Conclusions. The quality of general practice–based data can be considered on five content-based aspects. These aspects determine the quality of recording.