Abstract Background Community-based health insurance (CBHI) is a part of the health system in Bangladesh, and overcoming the obstacles of CBHI is a significant policy concern that has received little attention. The purpose of this study is to analyze the implementation barriers of voluntary CBHI schemes in Bangladesh and the strategies to overcome these barriers from the perspective of national stakeholders. Methods This study is exploratory qualitative research, specifically case study design, using key informant interviews to investigate the barriers of CBHI that are faced during the implementation. Using a topic guide, we conducted thirteen semi-structured in-depth interviews with key stakeholders directly involved in the CBHI implementation process. The data were analyzed using the Framework analysis method. Results The implementation of CBHI schemes in Bangladesh is being constrained by several issues, including inadequate population coverage, adverse selection and moral hazard, lack of knowledge about health insurance principles, a lack of external assistance, and insufficient medical supplies. Door-to-door visits by local community-health workers, as well as regular promotional and educational campaigns involving community influencers, were suggested by stakeholders as ways to educate and encourage people to join the schemes. Stakeholders emphasized the necessity of external assistance and the design of a comprehensive benefits package to attract more people. They also recommended adopting a public–private partnership with a belief that collaboration among the government, microfinance institutions, and cooperative societies will enhance trust and population coverage in Bangladesh. Conclusions Our research concludes that systematically addressing implementation barriers by including key stakeholders would be a significant reform to the CBHI model, and could serve as a foundation for the planned national health protection scheme for Bangladesh leading to universal health coverage.
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|Date made available||23 May 2023|
|Date of data production||2022|