Detalle Publicación


Validity of type 2 diabetes diagnosis in a population-based electronic health record database

Autores: Moreno Iribas, C. ; Sayon Orea, María del Carmen; Delfrade, J. ; Ardanaz, E.; Gorricho, J.; Burgui, R. ; Nuin, M.; Guevara, M.
ISSN: 1472-6947
Volumen: 17
Páginas: 34
Fecha de publicación: 2017
Background: The increasing burden of type 2 diabetes mellitus makes the continuous surveillance of its prevalence and incidence advisable. Electronic health records (EHRs) have great potential for research and surveillance purposes; however the quality of their data must first be evaluated for fitness for use. The aim of this study was to assess the validity of type 2 diabetes diagnosis in a primary care EHR database covering more than half a million inhabitants, 97% of the population in Navarra, Spain. Methods: In the Navarra EPIC-InterAct study, the validity of the T90 code from the International Classification of Primary Care, Second Edition was studied in a primary care EHR database to identify incident cases of type 2 diabetes, using a multi-source approach as the gold standard. The sensitivity, specificity, positive predictive value, negative predictive value and the kappa index were calculated. Additionally, type 2 diabetes prevalence from the EHR database was compared with estimations from a health survey. Results: The sensitivity, specificity, positive predictive value and negative predictive value of incident type 2 diabetes recorded in the EHRs were 98.2, 99.3, 92.2 and 99.8%, respectively, and the kappa index was 0.946. Overall prevalence of type 2 diabetes diagnosed in the EHRs among adults (35-84 years of age) was 7.2% (95% confidence interval [CI] 7. 2-7.3) in men and 5.9% (95% CI 5.8-5.9) in women, which was similar to the prevalence estimated from the health survey: 8.5% (95% CI 7.1-9.8) and 5.5% (95% CI 4.4-6.6) in men and women, respectively. Conclusions: The high sensitivity and specificity of type 2 diabetes diagnosis found in the primary care EHRs make this database a good source for population-based surveillance of incident and prevalent type 2 diabetes, as well as for monitoring quality of care and health outcomes in diabetic patients.