Validation of preterm birth related perinatal and neonatal data in the Canadian discharge abstract database to facilitate long-term outcomes research of individuals born preterm.

Introduction: The Canadian Institute of Health Information's (CIHI) Discharge Abstract Database (DAD) contains standardised administrative data on all hospitalisations in Canada, excluding Quebec.

Objectives: We aimed to validate preterm birth related perinatal and neonatal data in DAD by assessing its accuracy against the reference standard of the Canadian Neonatal Network (CNN) database.

Methods: We linked birth hospitalization data between the DAD and CNN databases for all neonates born <33 weeks gestational age (GA) admitted to the Neonatal Intensive Care Units in Winnipeg, Canada, between 2010 and 2022. A comprehensive list of maternal and neonatal variables relevant to preterm birth was chosen a priori for validation. For categorical variables, we measured correlation using Cohen's weighted kappa (k) and for continuous variables, we measured agreement using Lin's concordance correlation coefficient (LCCC).

Results: 2084 neonates were included (mean GA 29.4 ± 2.4 weeks; birth weight 1430 ± 461g). Baseline continuous maternal and neonatal variables showed excellent accuracy in DAD [Maternal age: LCCC = 0.99 (0.99, 0.99); GA: LCCC = 0.95 (0.95, 0.96); birth weight: LCCC = 0.97 (0.96, 0.97); sex: k = 0.99 (0.98-0.99)]. In contrast, the accuracy of the maternal baseline categorical variables and neonatal outcomes and interventions ranged from very good to poor [e.g., Caesarean section: k = 0.91 (0.89-0.93), pre-gestational diabetes: k = 0.04 (0.03-0.05), neonatal sepsis: k = 0.37 (0.31-0.42), bronchopulmonary dysplasia: k = 0.26 (0.19-0.33), neonatal laparotomy: k = 0.55 (0.43-067)].

Conclusion: Neonatal variables such as gestational age and birth weight had high accuracy in DAD, while the accuracy of maternal and neonatal morbidities and interventions were variable, with some being poor. Reasons for the inaccuracy of these variables should be identified and measures taken to improve them.