Decentralising data-driven decision-making in Kenya: Opportunities and challenges
Edgar Okoth is the SUN Civil Society Alliance Coordinator in Kenya, hosted at Nutrition International, and a nutrition and public health specialist with experience in supporting sub-national governments in health system strengthening and use of data for decision-making.
Murage Samuel Mahinda is the Health Records and Information Management Officer in the Nutrition Division in the Ministry of Health, Kenya. He has over 20 years’ experience in health information management from facility level to national level in monitoring and evaluation.
Since Kenya devolved authority to its 47 counties in 2013, it has been undergoing something of a nutrition data revolution in developing its information systems. In realisation of the relationship between improved information, data demand and use, there is a growing appetite for more and better-quality data for decision-making at the county level. National government is in charge of policy formulation, setting standards and providing technical assistance to the counties, as well as national referral and health information systems, but the counties are in charge of demand creation and service delivery. This responsibility requires quality data to inform decision-making for effective and sustainable health and nutrition systems.
Opportunities presented by a devolved health system
Devolution has provided the opportunity for counties to generate data to closely monitor key health and nutrition indicators and, to inform specific county-level integrated development plans, the blueprint for their development.
Devolved government also offers opportunities to further enhance governance not only at the sector level, but down to the grassroots community level. This is where citizen participation mechanisms, such as organised chief’s meetings, community dialogue and action days, are already in place to facilitate and strengthen joint accountability for health and nutrition. Systems such as supply end-user monitoring for nutrition programmes involve reporting on the availability of nutrition commodities and the quality of care provided. Data supplied by counties on their particular disease burden also enables the Kenya Medical Supplies Authority to use the information to prioritise drug procurement for an individual county, based on actual need and their ability to utilise these supplies1.
Strengthening county-level data capacity
The main aim of using decentralised data is to improve technical and social accountability2 of health and nutrition interventions by focusing on strengthening county capacity in information generation, validation, analysis, dissemination and use. This is achieved through five different approaches: improving facility reporting systems; scale-up of birth, death and cause of death reporting; scale-up of disease surveillance and response; carrying out routine surveys, such as Nutrition SMART surveys; and strengthening capacity for health research.
Support systems have been put in place to establish a common data architecture, known as Kenya Health Information Systems, components of which are the Community Health System and the Health Commodity Information System. Nutrition Information Technical Working Groups and data clinic forums have also been created and enhanced at national and county level, where data and statistics are validated and shared. To improve performance, monitoring and review processes are carried out on a quarterly basis at county level, and on a monthly basis at health facility and community level. These are usually done through supportive supervision, data-review processes, and quarterly data and quality audits. At the community level, routine community dialogue and action days give citizens the opportunity to interrogate the data. Community radio is also used to disseminate results and to increase community engagement as part of a community health strategy.
Increasing data demand and use
Decentralisation of decision-making at county level provides a unique opportunity to push for data demand and its use closer to service delivery points. With technical and financial support from various development partners, all 47 counties have gone through a three-stage process to help improve data quality and ownership. The data flows from the community (via health and nutrition information collected by community health volunteers at household level) and the health facility and is fed into the health information system, where it is aggregated and analysed. The data is then relayed back to the county, health facility and community level for action.
The use of data to make programme decisions and the involvement of the county leadership and the community should enable the community to be more informed and involved in implementation of various activities, which in turn should lead to greater sustainability. For example, surveillance data is used to map wasting ‘hot spots’ in the community, which in turn is informing implementation of integrated outreach including additional mass screening of vulnerable children, the up-scale of Kenya’s integrated management of acute malnutrition (IMAM) programme and pre-positioning of nutrition commodities for the management of children with wasting. The analysis of IMAM coverage data is also used to try and trace ‘defaulters’ from the programme and it is used in the implementation of the IMAM surge model, which scales up services when levels of wasting increase above a particular threshold in particularly vulnerable counties, such as those in the arid and semi-arid areas of Kenya that are prone to drought.
Using data to develop costed plans
A number of implementing partners have helped to build the capacity of county officials through training programmes; setting up nutrition technical working groups at the county and sub-county level and implementing monthly data reviews and quarterly data audits (in all 47 counties). As a result of support from the SUN Movement Civil Society Alliance through the United Nations Office for Project Services (UNOPS), Nutrition International and the Technical Assistance to Nutrition (TAN) project, ten counties have so far developed costed Nutrition Action Plans, drawing on a range of data sources (for example, routine data audits, monthly health facility meetings, community dialogue and action days). These plans prioritise services and activities and aim to ensure to-scale implementation of key interventions.
Counties are at different stages in terms of building their own data systems. Real-time reporting is still a challenge, especially at lower levels of care (community, dispensary and health centres), where intermittent electricity and internet connectivity make it difficult to build the necessary infrastructure. There is currently insufficient expertise and capacity for fully data-driven decision-making, with only one health records and information officer in post at county level. Collating nutrition data and information from various sectors is also a challenge, especially given the current proliferation of data collection systems and parallel systems (from users and donors, encompassing political as well as commercial interests). Other barriers include: poor data quality and prioritising of data use; low reporting levels and lack of data capture tools at health facilities in some counties; and inadequate capacity to handle data and use information.
Plans for next steps
The remaining 37 county governments are working to finalise costing of their Nutrition Action Plans by the end of 2020, with further support from development partners, to allow for full implementation of costed plans. The national government, through the Kenya National Bureau of Statistics, has also hired staff to implement the National Information Platform for Nutrition (NIPN)3 to support analysis and use of data to improve decision-making. Finally, the government’s last-mile project aims to ensure that all health facilities have access to electricity to enable real-time data transmission by 2022.
1 Previously, counties might be supplied with drugs for diseases and conditions that were not reported within their area (for example, drugs for treating malaria in non-endemic zones that might expire), at the expense of other areas with greater need.
2 Social accountability is driven by the citizen/user/society perspective to ensure that the quality of service is maintained.
3 NIPN is rooted within existing institutions and national multi-sector coordination systems for nutrition. From the analysis of available and shared data, it generates evidence that is used by sub-national stakeholders for developing policy, designing programmes and allocating investments. http://www.nipn-nutrition-platforms.org/Kenya-202
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Reference this page
Edgar Okoth, Murage Samuel Mahinda (). Decentralising data-driven decision-making in Kenya: Opportunities and challenges. Nutrition Exchange 13, March 2020. p22. www.ennonline.net/nex/13/kenya