Understanding the drivers of effective supportive supervision: a realist evaluation of community health worker programs in Madhya Pradesh, India

了解有效支持性督导的驱动因素:对印度中央邦社区卫生工作者项目的现实主义评估

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Abstract

BACKGROUND: Multiple policies promote supportive supervision for community health workers (CHWs) in India. However, little is known about how it is understood and implemented by CHW supervisors, and the context within which it operates to bring about desirable outcomes. In this study, we employed a realist evaluation framework to understand the contextual factors and mechanisms influencing supportive supervision outcomes in rural healthcare settings. METHODS: We conducted direct observations of six CHW supervisors in the Raisen district of Madhya Pradesh, India, between 2020 - 2021. We assessed supervisory activities at health facilities, outreach sessions, and community sites using a competency evaluation checklist. We analyzed the observations through the lens of context-mechanism-outcome configurations (CMOC) to identify key drivers and barriers to effective supportive supervision. RESULTS: We identified five critical CMOCs associated with supportive supervision: travel constraints, resource availability, administrative burden, communication style and leadership approach. We found that the implementation and subsequent effect of supportive supervision depends on multiple interacting factors. Geographic isolation, inadequate transportation, and administrative burdens impede consistent, on-the-spot supportive supervision, particularly in remote areas. Supervisors who use structured tools and collaborative leadership approaches can provide contextually and technically sound supportive supervision to CHWs, which may lead to more optimum performance and motivation outcomes. However, chronic resource constraints coupled with authoritative workplace dynamics compromise the quality of supportive supervision and delay achieving desirable outcomes. CONCLUSIONS: Institutionalizing supportive supervision necessitates effectively addressing contextual barriers to its operationalization. Identifying and adequately training supervisors, implementing digital supervision tools, prioritizing dedicated field supervision time, and investing in leadership training can encourage wider adoption of supportive supervision.

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