Evidence map›Paper›PMID 39261911›Full record

ArticleInternational journal for equity in health2024

Equity considerations for the implementation of health insurance benefit package in Ethiopia: result of expert Delphi exercise.

Solomon Tessema Memirie, Muluken Argaw, Mieraf Taddesse Tolla, Frehiwot Abebe, Wubaye Walelgne Dagnaw, Ole F Norheim, Amanuel Yigezu

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Article in International journal for equity in health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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7 authors.

Solomon Tessema MemirieAddis Center for Ethics and Priority Setting, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia. tess_soul@yahoo.com.
Muluken ArgawEthiopian Health Insurance Service, Addis Ababa, Ethiopia.
Mieraf Taddesse TollaAddis Center for Ethics and Priority Setting, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia.
Frehiwot AbebeEthiopian Health Insurance Service, Addis Ababa, Ethiopia.
Wubaye Walelgne DagnawCenter for Integration Science, Department of Global Health Equity, Brigham and Women's Hospital, Boston, MA, USA.
Ole F NorheimBergen Centre for Ethics and Priority Setting, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Amanuel YigezuEthiopian Health Insurance Service, Addis Ababa, Ethiopia.

Funding

Ethiopian Health Insurance Service None
6 · The paper itself

Abstract

backgroundEfficiency, equity and financial risk protection are key health systems objectives. Equitable distribution of health care is among the priority strategic initiative of the government of Ethiopia. However, data on the distribution of interventions benefits or on disease burden disaggregated by subpopulations to guide health care priority setting is not available in Ethiopia.

methodsAligned with policy documents, we identified the following groups to be the worse off in the Ethiopian context: under-five children, women of reproductive age, the poor, and rural residents. We used the Delphi technique by a panel of 28 experts to assign a score for 253 diseases/conditions over a period of two days, in phases. The expert panel represented different institutes and professional mix. Experts assigned a score 1 to 4; where 4 indicates disease/condition predominantly affecting the poor and rural residents and 1 indicates a condition more prevalent among the wealthy and urban residents. Subsequently, the average equity score was computed for each disease/condition.

resultsThe average scores ranged from 1.11 (for vitiligo) to 3.79 (for obstetric fistula). We standardized the scores to be bounded between 1 and 2; 1 the lowest equity score and 2 the highest equity score. The scores for each disease/condition were then assigned to their corresponding interventions. We used these equity scores to adjust the CEA values for each of the interventions. To adjust the CEA values for equity, we multiplied the health benefits (the denominator of the cost-effectiveness value) of each intervention by the corresponding equity scores, resulting in equity adjusted CEA values. The equity adjusted CEA was then used to rank the interventions using a league table.

conclusionsThe Delphi method can be useful in generating equity scores for prioritizing health interventions where disaggregated data on the distribution of diseases or access to interventions by subpopulation groups are not available.

Indexed as

Delphi TechniqueInsurance, HealthEthiopiaFemaleHealth EquityHumansInsurance BenefitsMalePovertyRural PopulationCost-effectiveness analysisEquityEthiopiaHealth benefit packageUniversal health coverage

Identifiers

PMID39261911
PMCPMC11389339

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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.