Data Quality Management and Query Resolution: Summary and Assessment

A multicentre neonatal sepsis study is being conducted in six hospitals. The primary outcome is survival status at day 28. Key secondary outcomes include length of hospital stay, antibiotic exposure, blood culture result, and readmission within 28 days. The study uses REDCap, and all sites enter data directly into the database. After two months, the central data manager runs the weekly data quality report and finds 640 open queries across 420 enrolled participants. The query metrics show that 40 percent of open queries relate to antibiotic name and dose, 25 percent relate to missing blood culture results, 15 percent relate to inconsistent admission and discharge dates, 10 percent relate to missing day 28 outcomes, and the remaining 10 percent relate to miscellaneous fields. One site has a much higher query rate than the others. Another site has very few adverse events compared with sites enrolling similar patients. Several queries have been open for more than 21 days. The data manager reviews the CRFs and finds that antibiotic information is entered as free text. Some users write brand names, others write generic names, and dose units are inconsistent. Blood culture results are delayed because the laboratory sends paper reports weekly. The high-query site has recently hired new nurses who were not included in the original REDCap training. The site with very few adverse events reports that staff were unsure whether minor clinical deterioration should be recorded as an adverse event. This case illustrates that high query burden is often a symptom of system problems rather than individual failure. The antibiotic queries suggest a CRF design issue that could be improved with coded medication options, structured dose fields, and clearer units. Missing blood culture results suggest a workflow and reconciliation issue with the laboratory. Date inconsistencies may require validation rules and refresher training. Missing day 28 outcomes are critical because they affect the primary outcome and should be escalated quickly. The site with few adverse events may have under-reporting due to unclear definitions. The appropriate response should combine immediate query resolution with process improvement. Critical queries related to day 28 survival should be prioritized. The high-query site should receive targeted retraining. The antibiotic form should be revised under version control if the study team approves the change. A laboratory transfer log should be created to reconcile expected and received culture results. Adverse event definitions should be clarified with examples. Query metrics should be monitored after these interventions to assess whether quality improves. ### Case Study Questions 1. Which query categories should be prioritized and why? 2. Which problems appear to be CRF design issues rather than site performance issues? 3. What additional validation rules or coded fields could reduce future queries? 4. How should the data manager investigate the site with unusually few adverse events? 5. What query metrics should be reviewed over the next month to determine whether interventions worked?