The accuracy of population health data for monitoring trends and outcomes among women with diabetes in pregnancy

Abstract Aim To assess the accuracy of routinely collected population birth and hospital datasets in identifying maternal pregestational diabetes mellitus (PDM) and gestational diabetes mellitus (GDM). Methods Information on maternal diabetes status was obtained from the medical records of a random sample of 1200 women and compared with routinely collected, population-based birth and hospital data. PDM and GDM are reported in both databases. Sensitivity, specificity, positive predictive value (PPV), negative predictive value and the kappa statistic were determined. Results Medical records were available for 1184 of the 1200 women sampled. 0.3% of women were classified with PDM and 4.8% with GDM. ‘True’ PDM was under-reported and misclassified in the birth data, but all cases were reported in the hospital data. GDM was also more completely and more accurately reported in the hospital data than in the birth data. Diabetes requiring insulin was more likely to be reported than non-insulin dependent diabetes. Conclusions Hospital data were more sensitive and accurate (higher PPVs) than birth data and these measures were not improved by ascertaining diabetes from either of the two datasets. More severe forms of diabetes were more likely to be reported than less severe.