Table 2 Recommendations to improve data quality

 1. Enhance the data dictionary and data entry guidelines documents to standardize collection and use of data in the Registry;

 2. Clarify definitions (e.g., hypertension during pregnancy, location discharged or transferred to, labour type);

 3. Continue to monitor data quality in each organization;

 4. Communicate with hospital users regularly about data quality issues identified and support corrective strategies to reduce the occurrence of errors;

 5. Create site-specific audit tools for hospitals to monitor their own data quality and identify potentially modifiable data quality issues that could be addressed early;

 6. Continue to encourage accurate documentation in the patient health record to ensure complete information for data entry personnel (e.g., newborn pain relief);

 7. Set automatic verification checks at the time of data entry (e.g., height, weight, gestational age);

 8. Create logic checks where possible based on practice guidelines (e.g., fetal surveillance);

 9. Reassess and refine data element pick list options for problematic data elements (e.g., intention to breastfeed, newborn discharged or transferred to, hypertension during pregnancy, maternal smoking at first prenatal visit and at labour) to align these data elements with the patient health record documentation and optimize data capture;

 10. Provide ongoing training for new staff, to ensure that all data entry personnel are aware of the data elements to be entered, where to find the information and how to address issues of discrepancy when they occur.