Inconsistency or unstable implementation policies in electronic records management systems are likely to create discrepancy in data which may distorts facts as quality of information is compromised. This leads to taking misleading decisions and actions which may be life threatening circumstances in health settings, business losses, misplacement of priorities and wrong interventions for development. Identifying the causes of data discrepancies should be a priority in driving efforts to improve quality at different levels of data ecosystem. This paper investigated the implication of frequent changes in electronic health records management system implementation policy on data quality in an organization supporting health facilities providing HIV/AIDS services across twelve states in Nigeria through the application of divide and conquers and lot quality assurance sampling methods. Large data discrepancies were discovered using the combined methods and there was tremendous data quality improvement six-month after the intrinsic and contextual data quality validation. The study concluded that frequent changes in electronic data management systems are likely to breed distortions in data quality that may greatly affect effective delivery of the most needed quality services.

Electronic Medical Records Public Health Data Quality Policy Changes.