Evidence map›Paper›PMID 36037203›Full record

ArticlePloS one2022

A mixed methods study of community-based health insurance enrollment trends and underlying challenges in two districts of northeast Ethiopia: A proxy for its sustainability.

Mohammed Hussien, Muluken Azage, Negalign Berhanu Bayou

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Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mohammed HussienDepartment of Health Systems Management and Health Economics, School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia.ORCID 0000-0002-5747-8967
Muluken AzageDepartment of Environmental Health, School of Public Health, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia.
Negalign Berhanu BayouDepartment of Health Policy and Management, Faculty of Public Health, Institute of Health, Jimma University, Jimma, Ethiopia.ORCID 0000-0002-0975-8358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe term "community-based health insurance" refers to a broad range of nonprofit, prepaid health financing models designed to meet the health financing needs of disadvantaged populations, particularly those in the rural and informal sectors. Due to their voluntary nature, such initiatives suffer from persistently low coverage in low- and middle-income countries. In Ethiopia, the schemes' membership growth has not been well investigated so far. This study sought to examine the scheme's enrollment trend over a five-year period, and to explore the various challenges that underpin membership growth from the perspectives of various key stakeholders.

methodsThe study employed a mixed methods case study in two purposively selected districts of northeast Ethiopia: Tehulederie and Kallu. By reviewing the databases of health insurance schemes, quantitative data were collected retrospectively from 2017 to 2021 to examine enrollment trends. Trends for each performance indicator were analyzed descriptively for the period under study. Face-to-face interviews were conducted with nine community members and 19 key informants. Study participants were purposely selected using the maximum variation technique. Interviews were audio recorded, transcribed verbatim, and translated into English. Thematic analysis was employed with both deductive and inductive coding approaches.

resultsOver the course of the study period, enrollment in the scheme at both districts exhibited non-linear trends with both positive and negative growth rates being identified. Overall, the scheme in Tehulederie has a relatively higher population coverage and better membership retention, which could be due to the strong foundation laid by a rigorous public awareness campaign and technical support during the pilot phase. The challenges contributing to the observed level of performance have been summarized under four main themes that include quality of health care, claims reimbursement for insurance holders, governance practices, and community awareness and acceptability.

conclusionsThe scheme experienced negative growth ratios in both districts, indicating that it is not functionally viable. It will fail to meet its mission unless relevant stakeholders at all levels of government demonstrate political will and commitment to its implementation, as well as advocate for the community. Interventions should target on the highlighted challenges in order to boost membership growth and ensure the scheme's viability.

Indexed as

Healthcare FinancingInsurance, HealthDelivery of Health CareEthiopiaHumansRetrospective Studies

Identifiers

PMID36037203
PMCPMC9423627

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.