programme to prevent mother-to-child HIV transmission in South Africa.

Challenges for routine health system data management in a large public programme to prevent mother-to-child HIV transmission in South Africa.

Recent changes to South Africa’s prevention of mother-to-child transmission of HIV (PMTCT) guidelines have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. Mate and colleagues assessed the completeness and accuracy of routine PMTCT data submitted to the District Health Information System in three districts of Kwazulu-Natal province, South Africa. They surveyed the completeness and accuracy of data reported for six key PMTCT data elements between January and December 2007 from all 316 clinics and hospitals in three districts. Through visits to randomly selected sites, they reconstructed reports for the same six PMTCT data elements from clinic registers and assessed accuracy of the monthly reports previously submitted to the District Health Information System. Data elements were reported only 50.3% of the time and were “accurate” (i.e. within 10% of reconstructed values) 12.8% of the time. The data element “Antenatal Clients Tested for HIV” was the most accurate data element (i.e. consistent with the reconstructed value) 19.8% of the time, while “HIV PCR testing of baby born to HIV positive mother” was the least accurate with only 5.3% of clinics meeting the definition of accuracy. Data collected and reported in the public health system across three large, high HIV-prevalence districts was neither complete nor accurate enough to track process performance or outcomes for PMTCT care. Systematic data evaluation can determine the magnitude of the data reporting failure and guide site-specific improvements in data management. Solutions are currently being developed and tested to improve data quality.

the finding of data missing at source, the weakest link in this data chain is the actual data collation at the clinic level, followed by lack of submission of data to the district level. Unless health workers are supported and supervised in the execution of data management tasks and unless data collection is designed in the first instance to be used locally to improve patient care, front line staff will not have the capacities nor perceive the value of data collection. Effective health information systems are simple, acceptable, timely, accurate, flexible, and useful. Only then do staff, who can improve clinical practice locally through analysis of performance and outcomes data, truly value them. This foundation stone is key to a health information system that helps national health systems assess progress towards established goals and plan future resource allocations.