Published in:
Open Access 01-12-2018 | Research
Evaluating the quality of routinely reported data on malaria commodity stocks in Guinea, 2014–2016
Published in: Malaria Journal | Issue 1/2018
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Background
Ensuring malaria commodity availability at health facilities is a cornerstone of malaria control. Since 2013, the Guinea National Malaria Control Programme has been routinely collecting data on stock levels of key malaria commodities through a monthly routine malaria information system (RMIS). In parallel, biannual end-user verification (EUV) surveys have also assessed malaria commodity availability at a subset of health facilities, potentially representing a duplication of efforts.
Methods
Data on 12 malaria commodity stock levels verified during four EUV surveys conducted between 2014 and 2016 was compared to data for the corresponding months submitted by the same health facilities through the RMIS. The sensitivity and specificity of the RMIS in detecting stock-outs was calculated, as was the percent difference between average stock levels reported through the two systems.
Results
Of the 171 health facilities visited during the four EUV surveys, 129 (75%) had data available in the RMIS. Of 351 commodity stock-outs observed during the EUV in the sampled reporting health facilities, 256 (73%) were also signaled through the corresponding RMIS reports. When the presence of malaria commodity stocks was confirmed during the EUV surveys, the RMIS also reported available stock 87% (677/775) of the time. For all commodities, the median percent difference in average stock levels between the EUV and RMIS was 4% (interquartile range − 7 to 27%).
Conclusion
The concordance between stock levels reported through the RMIS and those verified during the EUV visits provides certain evidence that RMIS data can inform quantification and procurement decisions. However, lower than acceptable rates of reporting and incomplete detection of stock-outs from facilities that do report suggest that further systems strengthening is needed to improve RMIS reporting completeness and data quality.