World Immunization Week is a perfect time to reflect on global priorities and our commitment to the Global Vaccine Action Plan (GVAP). This framework guides the work of organizations around the world to reach every child with life-saving vaccines. It is also a way to measure our collective success. Accurately measuring our progress against GVAP targets is central to moving the needle globally, but we need to be confident in the data.
I recently heard a ministry official summarize the challenges to increasing immunization in an area suspected to have a high number of unimmunized children. This was very different from the story told by the numbers. The administrative coverage rates (based on census numbers and the reported number of administered vaccine doses) for the region were well over 100%. Surveys designed to provide a baseline comparison in the same area reported lower numbers, but the data still showed surprisingly high coverage – above 80%. People at this meeting quickly said they were ‘tired’ of hearing about coverage rates because of the well-known data quality issues. This frustration with data quality has echoed at nearly every immunization stakeholder meeting I’ve attended. Clearly inaccurate data is less meaningful – and less useful. It could be worse than no data at all.
An example of data comparing administrative vaccine coverage and survey data.
We define and measure our success using indicators like coverage rates. Vaccine coverage targets exist for every region, country, and community. We use such data to inform decision-makers about our programs. When coverage rates are artificially high, they hide the real need for further funding and support. These coverage rates give the impression that immunization programs are performing beyond expectation and undermine our efforts to achieve equitable vaccine coverage. We must do a better job of ensuring the data accurately represent reality. So what it will take to solve the challenge of inaccurate coverage data?
There is no simple solution. But, there are new things we can try and lessons we can learn from other global health programs. Evidence coming out of maternal and child health programs in South Africa show an important link between heath worker competence, behavior, and data quality[1]. Training curriculums and data quality assessment tools from other global health sectors could potentially be adapted to vaccine programs. Some countries are considering electronic immunization registers, which will go a long way to alleviate some data problems. Programs like the BID Initiative focus on combining many of these approaches to provide a holistic suite of interventions that include technology, people, and processes to improve data quality. We also must work directly with ministries of health to build a stronger culture of data use and better train the people doing this important work.
As we apply new approaches and new technologies to reach every child with vaccines, we must also find new ways to improve data quality. At VillageReach, we have a deep commitment to quality data and its role in effective decision-making. Tools like OpenLMIS support data collection, allowing more accurate and timely data to reach all levels of the supply chain. Our partnerships with ministries of health enable us to increase the capacity for and commitment to a data-driven culture. Together we are working towards our goal of 100% vaccine coverage. It is important to achieve that goal with certainty.
[1] Nicol et al. (2013) Human Factors Affecting the Quality of Routinely Collected Data in South Africa. Studies in health technology and informatics 192(1):788-92.