Data Quality

How it works

Benefits

Comparisons

Evidence quality

Highlighted claims

• Studies that do not report data quality using the WHO definition, or that assess it only subjectively, will be excluded from the review. — Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol
• The comparator in eligible studies is low-quality routine health data, such as data that is incomplete, delayed, inconsistent, or inaccurate. — Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol
• Complete, consistent, accurate, and timely data enables policymakers to identify service gaps, design targeted interventions, and monitor progress toward Universal Health Coverage and the Sustainable Development Goals. — Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol
• Eligible studies may assess one, some, or all data quality dimensions including completeness, accuracy, timeliness, and consistency. — Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol
• Data quality may include one or more dimensions of completeness, accuracy, timeliness, and consistency. — Impact of quality routine health data utilisation on health service delivery outcomes in low-income and middle-income countries: a systematic review protocol