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Background: The use of CHWs is a proven method for creating demand and promoting best practices for health services [1]; however while effective, supervision of CHWs has also proven to be the most challenging program element to implement [2].To address this gap, Society for Family Health (SFH) designed and implemented an electronic dashboard tool with the aim to better evaluate, monitor and provide feedback on the performance of CHWs at health facilities under the Gates VMMC Project.
Description: Between February and December 2015, 232 CHWs were deployed to 107 health facilities in three provinces. Key indicators were defined in order to measure the monthly performance of each CHW as well as inform effective program decisions. Tableau® reader software was used to import Excel spreadsheets containing CHW performance, segregated the information by creating a dashboard and presented data in graphical form. Reports generated provide information on CHWs and clients. Based on the data captured, we were able to determine the proportion of men who successfully came for VMMC services.
Lessons learned: During the first half of the year 11,732 clients were booked by 65 CHWs, 6,111 (52%) of whom came for MC services; whilst in the later months when the dashboard was fully operational, 43,835 clients were booked by 232 CHWs and 20,555 (47%) came for MC services. Each CWH worked an average of 19 days in each month, and made an average of 53 bookings per month. An average of 25 clients turned up per CHW per month.
Conclusions/Next steps: The electronic dashboard is an efficient tool for supervising CHW performance, assuring adherence to quality standards and promoting fluid information sharing between community and organization. The application of robust M&E systems for monitoring demand creation activities should be in place at genesis of programs, particularly for improving supervision and feedback to CHWs. Based on our observations, improvements are underway to employ a more sophisticated data validation system on the backend in order allow for real time data collection and more accurate analysis of program data.