Data quality assessment in the routine health information system: an application of the Lot Quality Assurance Sampling in Benin

Abstract

Health information systems in developing countries are often faulted for the poor quality of the data generated and for the insufficient means implemented to improve system performance. This study examined data quality in the Routine Health Information System in Benin in 2012 and carried out a cross-sectional evaluation of the quality of the data using the Lot Quality Assurance Sampling method. The results confirm the insufficient quality of the data based on three criteria: completeness, reliability and accuracy. However, differences can be seen as the shortcomings are less significant for financial data and for immunization data. The method is simple, fast and can be proposed for current use at operational level as a data quality control tool during the production stage.