• Imputation: Use statistical methods like mean, median, or mode imputation for numeric fields (e.g., average age).
• Deletion: For substantial gaps, consider removing incomplete records if doing so doesn't bias results.
• Follow-up: If feasible, revisit schools to collect missing information. For critical fields, prioritize completeness during data collection. For example, if 20% of oral health records lack caries status, imputing based on the school’s average caries prevalence might help.

Citation: Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177.