Progress in preventing malaria in pregnancy depends on good data. Bright Orji, Gladys Olisaekee, Onyinye Udenze, Enobong Umoekeyo, Chika Nwankwo, Boniface Onwe, Chibugo Okoli, and Emmanuel Otolorin of Jhpiego discussed ways to improve data quality in Nigeria at the 66th Annual Meeting of the American Society of Tropical Medicine and Hygiene with support from the USAID Maternal and Child Health Program. A summary of their points follows:
Quality data are crucial for informed decision-making to address health challenges and improve malaria service delivery among countries on the pathway to malaria elimination. This emphasis on better data quality was reflected in the World Malaria Day theme of “Counting Malaria Out” in 2009 and 2010.
In Nigeria, improving malaria data quality has been difficult due to critical health system challenges including poor coordination across different departments, institutional complexities, and a shortage of medical record officers and service providers sufficiently trained in data visualization and use of data for decision-making. In response, the Maternal and Child Health Survival Program (MCSP) in Nigeria embarked on the implementation of key activities to improve quality of malaria data in Ebonyi State.
These activities included training on record keeping and use of data for decision-making; post training follow-up; dash boards at the frontline for better data visualization; monthly data collation meetings; improved synergy among service departments; and quarterly data quality assurance visits. As a result, more than 75% of facilities graphed malaria indicators thereby increasing data visualization and use of data for decision-making.
An example of data improvements leading to service increases was Intermittent Preventive Treatment for malaria in pregnancy (IPTp). IPTp1 service statistics in MCSP-supported facilities improved from 54.1% in Oct-Dec 2015 to 81.3% by Jul-Sept 2016 compared to 54.7% to 67.8% in the same periods for non-MCSP facilities.
Data quality improvement interventions such as monthly data collation and validation meetings prior uploading data to DHIS can contribute to improved quality of malaria performance indicators, better coordination between antenatal care, outpatient and pharmacy departments and increased IPTp coverage.