Reporting of Gestational Diabetes and Other Maternal Medical Conditions: Validation of Routinely Collected Hospital Data from New South Wales, Australia

Introduction: Hospital datasets are a valuable resource for examining prevalence and outcomes of medical conditions during pregnancy. To enable effective research and health planning, it is important to determine whether variables are reliably captured.

Objective: To examine the reliability of reporting of gestational and pre-existing diabetes, hypertension, thyroid conditions, and morbid obesity in coded hospital records that inform the population-level New South Wales Admitted Patient Data Collection.

Methods: Coded hospital admission data from two large tertiary hospitals in New South Wales, from 2011 to 2015, were compared with obstetric data, collected by midwives at outpatient pregnancy booking and in hospital after birth, as the reference standard. Records were deterministically linked and sensitivity, specificity, positive predictive values and negative predictive values for the conditions of interest were obtained.

Results: There were 36,051 births included in the analysis. Sensitivity was high for gestational diabetes (83.6%, 95% CI 82.4-84.7%), pre-existing diabetes (88.2%, 95% CI 84.1-91.6%), and gestational hypertension (80.1%, 95% CI 78.2-81.9%), moderate for chronic hypertension (53.5%, 95% CI 47.8-59.1%), and low for thyroid conditions (12.9%, 95% CI 11.7-14.2%) and morbid obesity (9.8%, 95% CI 7.6-12.4%). Specificity was high for all conditions (≥97.8%, 95% CI 97.7-98.0) and positive predictive value ranged from 53.2% for chronic hypertension (95% CI 47.5-58.8%) to 92.7% for gestational diabetes (95% CI 91.8-93.5%).

Conclusion: Our findings suggest that coded hospital data are a reliable source of information for gestational and pre-existing diabetes and gestational hypertension. Chronic hypertension is less consistently reported, which may be remedied by grouping hypertension types. Data on thyroid conditions and morbid obesity should be used with caution, and if possible, other sources of data for those conditions should be sought.