Construction and validation of a scoring system for the selection of high-quality data in a Spanish population primary care database (SIDIAP)
Abstract
Methods Diseases that were likely to be representative of common diagnoses seen in primary care were selected for RQS calculations. The observed/ expected cases ratio was calculated for each disease. Once we had obtained an estimated value for this ratio for each of the selected conditions we added up the ratios calculated for each condition to obtain a final RQS. Rate comparisons between observed and published prevalences of diseases not included in the RQS calculations (atrial fibrillation, diabetes, obesity, schizophrenia, stroke, urinary incontinence and Crohn's disease) were used to set the RQS cutoff which will enable researchers to select PCPs with research-usable data.
Results Apart from Crohn's disease, all prevalences were the same as those published from the RQS fourth quintile (60th percentile) onwards. This RQS cut-off provided a total population of 1 936 443 (39.6% of the total SIDIAP population).
Conclusions SIDIAP is highly representative of the population of Catalonia in terms of geographical, age and sex distributions. We report the usefulness of rate comparison as a valid method to establish research-usable data within primary care electronic medical records.
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PDFDOI: http://dx.doi.org/10.14236/jhi.v19i3.806
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