High-quality data are essential to monitor and evaluate the performance, quality and equity of community health programmes. However community health information system data quality in low- and middle-income countries is poor. Community-level health data is not used in decision-making and little has been done to explore the barriers to reporting high-quality community-level health data.
We conducted research in Kenya and Malawi and found there are large discrepancies in the values reported by Community Health Workers and those reported by their supervisors. This is due to the fact that official data reporting forms are not always available and not designed with the end user in mind. There is no specific training for Community Health Workers on how to record data and they have inconsistent understandings of health indicators. This is exacerbated by a lack of supervision and mentorship from their supervisors and poor linkage between communities and primary healthcare facilities. Often parallel reporting systems are a burden and confusion to Community Health Workers.
Community Health Workers should have standardized data collection tools designed with their needs in mind. Training on data management should be a component of the standard training package they and their supervisors receive. Primary healthcare facilities should store and track referrals received from Community Health Workers and data quality and management should be a standing agenda item in their meetings with their supervisors. Finally, Data Quality Assessments should be carried out periodically to identify gaps in data quality and inform management decisions.