Facility data quality improvement session in Siaya County, Kenya. Credit: Stephen Wafula.
Parts of Kenya report up to 725 malaria cases per 1,000 people, but due to inconsistent and incomplete data, it’s difficult to persuade county government officials to prioritise health interventions that could save lives. Palladium’s Lillian Mageto writes on the impact of improving data quality and management.
Data-driven planning and decision-making are catchphrases in the field of public health policy and administration. And while the use of data to improve public health services and respond to crises has gained prominence during the coronavirus pandemic, this is far from the first time that data has been used to address health issues.
In Kenya, malaria presents challenges to the health system at both the national and regional levels. Highly infectious, malaria is the leading cause of mortality in the country, resulting in thousands of deaths every year. The mosquito-borne disease acutely affects western Kenya, where malaria is the principal cause of sickness and death (mainly due to climatic factors). In 2019, the Kenya national malaria incidence was reported at 125.92 cases per thousand population.
In counties that make up the Lake Endemic Region in western Kenya, however, the incidences reported were significantly higher than the national average. Bungoma and Vihiga counties reported more than 200 cases per thousand population each, while Busia County reported a staggering 725 cases per thousand.
Effective preventive measures and case management interventions are crucial to reduce malaria morbidity and mortality. However, due to inconsistent and incomplete malaria program data recorded in routine health information systems, it remains a challenge to persuade county government officials to prioritise urgent interventions at health facilities that could save lives.
Improving Data Quality and Management
The Tupime Kaunti Project supports efforts to strengthen county measurement, learning, and accountability (MLA) systems to provide high-quality data and synthesised information for planning, implementation, and decision-making for public health.
A functional MLA system consists of strong leadership and governance frameworks, adequate human and financial resources, vibrant internal and external coordination mechanisms, and health information systems that enable health leaders to use data for decision-making.
In response to the ongoing malaria crisis, the Tupime Kaunti Project partnered with eight southwestern county departments of health to build the capacity of health officers in addressing data quality gaps such as inconsistencies among indicators, incomplete primary documents and late reporting, developing data management skills, and accessing and navigating the Kenyan Health Information System (KHIS).
Health officers learned how to tap specific malaria data elements from the KHIS to analyse and visualise the data using the quality tracking tool.
Tupime Kaunti worked with the health facilities that contribute to more than 50 per cent of malaria cases per sub-county and were identified as having poor data quality performance. They developed a malaria data quality tracking dashboard to narrow down facility-level data quality issues for more focused data quality improvement interventions. By the end of the training sessions, officers could identify and prioritise sub-county health facilities for specific data quality improvement initiatives.
During the capacity building sessions, the county health officers also received training on the Kenya Malaria Strategy 2019-2023 to align their malaria surveillance with the national strategy, and improve decision-making at their respective health facilities. The officers developed a county-specific malaria indicator definition matrix to use during the facility data quality improvement activities. The matrix details the inputs of indicators such as suspected, tested, and confirmed malaria cases, as well as the data sources using the Ministry of Health registers.
“The sub-county faced a lot of discrepancies in malaria data where different data sets were not speaking the same language,” says Asuman Zuber, Health Records and Information Officer (HRIO), Gem Sub-county.
“On many occasions, the number of confirmed malaria cases were more than the suspected ones, which should not be the scenario.”
According to Zuber, the facilities have embraced data reviews before submission to the sub-counties, and Gem Sub-county has realised the importance of having the correct primary tools and enhanced mentorship on data management by the HRIO. "As a result of all these efforts, we now have more accurate data in the Kenya Health Information System," he adds.
Supporting Public Health with Data
The newly trained officers will use these skills to implement a full range of data quality assurance activities at the facility, sub-county, and county level and escalate issues that require county health leadership and National Malaria Control Program intervention.
In total, 138 officers from the county and sub-county health management teams were trained in data quality, and a total of 315 health facilities were visited in the eight focus counties.
Moving forward, the project will continue to support various data quality interventions in the focus counties, specifically to scale up use of the innovative tools, and target health facilities with very poor data quality.
The data quality assurance (DQA) digital tools have also proven to be useful during the COVID-19 pandemic, since program officers are unable to visit health facilities for face-to-face audits with health workers. The project is on track to achieve sustainability of DQA interventions as counties embrace off-site data quality checks.
These best practices for improving health data are also being developed for the Reproductive Maternal Neonatal Child and Adolescent Health program, and have provided support in strengthening the COVID-19 system in the focus counties in Kenya.
Lillian Mageto is Chief of Party of the Tupime Kaunti Project. She has experience in statistical modelling, global and reproductive health, survey design, and capacity development. Lillian is a community and social services professional with a Master of Science degree in social statistics from the University of Nairobi.
Palladium implements Tupime Kaunti (also known as the County Measurement, Learning and Accountability Program, or CMLAP) for USAID. The project supports ongoing efforts to strengthen measurement, learning, and accountability systems to provide high-quality data and synthesized information for planning, implementation, and decision-making in Kenya.