A Case Study from Ethiopia: Supportive Supervision in Monitoring and Evaluation with Community-Based Health Staff in HIV Programs


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Author(s): Marshall A, Fehringer J

Year: 2014

A Case Study from Ethiopia: Supportive Supervision in Monitoring and Evaluation with Community-Based Health Staff in HIV Programs Abstract:

Background – Supportive supervision is a facilitative approach that promotes mentorship, joint problem-solving, and communication between supervisors and supervisees. In Ethiopia, MEASURE Evaluation trained government managers on supportive supervision as part of a project to scale-up the country’s health management information system (HMIS). This report presents a case study of the project that can serve as an example for other programs wishing to use supportive supervision in monitoring and evaluation (M&E).

Methods – A single case study design was used. Data were collected through 12 key informant interviews, four observations of supervision visits, and document review. Participants were sampled purposively from three strata: MEASURE Evaluation staff, government supervisors, and community-level staff. Interview transcripts were coded in NVIVO 10 and compared with direct observation notes and documents using thematic content analysis.

Results – Findings suggest that the project was successful in promoting program ownership, standardizing supervision, and improving data quality. Participants attributed these successes to collaboration among government offices, supervision tools, and feedback and training provided to staff by supervisors. The project was less successful at promoting data use for decision making. While participants had theoretical knowledge, there was little actual use of information at health facilities.

Conclusion – Supportive supervision is a promising approach to improve routine data collection for M&E of community-based programs. Programs that wish to use this approach can adapt best practices and lessons learned from this and other projects. Specifically, programs should work in teams of supervisors, address staff motivation and confidence during visits, promote data demand and use, and create a training plan for M&E staff.