Collecting information on the quality of prescribing in primary care using semi-automatic data extraction from GPs' electronic medical records
(2005) International Journal of Medical Informatics — Vol. 74, n° 5, p. 367-376 (2005)
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- Abstract
- Objectives: To evaluate a semi-automatic data extraction from the electronic medical record (EMR) of general practitioners (GPs) through a comparison with a paper sheets data collection simultaneously used in a primary care research project on the quality of prescribing for osteoarthritis in the elderly. Subjects: One hundred and fifty-two GPs using five different EMR-software systems participated with the semi-automatic data extraction from the EMR and 233 GPs collected data with paper registration sheets. Methods: The proportion of patients with respectively a drug prescription, paracetamol, a non-steroidal anti-inflammatory drug (NSAID) and ibuprofen were compared between the semi-automatic extraction and the paper data collection and among the EMR-software systems. Results: Using the semi-automatic data extraction, a significantly lower proportion of patients on drugs was obtained compared to the paper data collection (adjusted OR: 0.31; 95% CI 0.25-0.39). However, the proportion of patients on a specific type of drug was comparable. Within the results from the semi-automatic extraction, the results were heterogeneous among the different EMR-software systems. Conclusions: The semi-automatic data extraction with multiple EMR-software systems proposed in this study seems suitable for quality of prescribing assessment in primary care. However, it may be less reliable when only a single EMR-software is used. (c) 2005 Elsevier Ireland Ltd. All rights reserved.
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Vandenberghe, H., Van Casteren, V., Jonckheer, P., Bastiaens, H., Van der Heyden, J., Lafontaine, M., & De Clercq, E. (2005). Collecting information on the quality of prescribing in primary care using semi-automatic data extraction from GPs’ electronic medical records. International Journal of Medical Informatics, 74(5), 367-376. https://doi.org/10.1016/j.ijmedinf.2005.02.004 (Original work published 2005)