What Are Common Challenges in Data Quality Assurance?
Several challenges can impede data quality assurance in epidemiology:
Data Entry Errors: Human mistakes during data input can introduce inaccuracies. Missing Data: Incomplete records can skew analysis and lead to biased conclusions. Data Integration: Combining data from multiple sources can be complex and error-prone. Technological Limitations: Insufficient or outdated technology can hinder data collection and processing.
