A system for solution-orientated reporting of errors associated with the extraction of routinely collected clinical data for research and quality improvement
Michalakidis, G.; Kumarapeli, P.; Ring, A.; van Vlymen, J.; Krause, P.; de Lusignan, S.
Studies in Health Technology and Informatics 160(Pt 1): 724-728
2010
ISSN/ISBN: 0926-9630 PMID: 20841781 Document Number: 639515
We have used routinely collected clinical data in epidemiological and quality improvement research for over 10 years. We extract, pseudonymise and link data from heterogeneous distributed databases; inevitably encountering errors and problems. To develop a solution-orientated system of error reporting which enables appropriate corrective action. Review of the 94 errors, which occurred in 2008/9. Previously we had described failures in terms of the data missing from our response files; however this provided little information about causation. We therefore developed a taxonomy based on the IT component limiting data extraction. Our final taxonomy categorised errors as: (A) Data extraction Method and Process; (B) Translation Layer and Proxy Specification; (C) Shape and Complexity of the Original Schema; (D) Communication and System (mainly Software-based) Faults; (E) Hardware and Infrastructure; (F) Generic/Uncategorised and/or Human Errors. We found 79 distinct errors among the 94 reported; and the categories were generally predictive of the time needed to develop fixes. A systematic approach to errors and linking them to problem solving has improved project efficiency and enabled us to better predict any associated delays.