External Validation of EPICON: A Grouping System for Estimating Morbidity Rates Using Electronic Medical Records
- Marion CJ Biermansa,
- Geert H Elbersa,
- Robert A Verheijb,
- Willem Jan van der Veenc,
- Gerhard A Zielhuisd,
- Pieter F de Vries Robbéa
- aDepartment of Medical Informatics, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
- bNetherlands Institute for Health Services Research, Utrecht, the Netherlands
- cUniversity Medical Centre, University of Groningen, sector F (Department of General Practice), Groningen, the Netherlands
- dDepartment of Epidemiology, Biostatistics and Health Technology Assessment, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
- Correspondence: Marion Biermans, Department of Medical Informatics, Radboud University Nijmegen Medical Centre, 152 MI, P.O. box 9101, 6500 HB Nijmegen, The Netherlands; (e-mail: <m.biermans{at}mi.umcn.nl>)
- Received 28 February 2008
- Accepted 14 August 2008
Abstract
Objective To externally validate EPICON, a computerized system for grouping diagnoses from EMRs in general practice into episodes of care. These episodes can be used for estimating morbidity rates.
Design Comparative observational study.
Measurements Morbidity rates from an independent dataset, based on episode-oriented EMRs, were used as the gold standard. The EMRs in this dataset contained diagnoses which were manually grouped by GPs. The authors ungrouped these diagnoses and regrouped them automatically into episodes using EPICON. The authors then used these episodes to estimate morbidity rates that were compared to the gold standard. The differences between the two sets of morbidity rates were calculated and the authors analyzed large as well as structural differences to establish possible causes.
Results In general, the morbidity rates based on EPICON deviate only slightly from the gold standard. Out of 675 diagnoses, 36 (5%) were considered to be deviating diagnoses. The deviating diagnoses showed differences for two main reasons: “differences in rules between the two methods of episode construction” and “inadequate performance of EPICON.”
Conclusion The EPICON system performs well for the large majority of the morbidity rates. We can therefore conclude that EPICON is useful for grouping episodes to estimate morbidity rates using EMRs from general practices. Morbidity rates of diseases with a broad range of symptoms should, however, be interpreted cautiously.
Footnotes
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↵* Operationally, an episode is a row of diagnoses that carry the same episode number. The first diagnosis of a new episode number was characterized as new; all other diagnoses were marked as ongoing.
