Evidence map›Paper›PMID 41146283›Full record

ArticleCost effectiveness and resource allocation : C/E2025

Direct medical cost analysis of breast cancer treatment at Jimma University Medical Center: a provider perspective.

Gebeyehu Jeldu Edessa, Kidist Adamu Kare, Aleka Jeldu Edessa, Dawit Wolde Daka

Abstract read
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Article in Cost effectiveness and resource allocation : C/E, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Gebeyehu Jeldu EdessaInstitute of Health, Faculty of Public Health, Department of Health Policy, and Management, Jimma University, Jimma, Ethiopia. jalduucaalii@yahoo.com.
Kidist Adamu KareInstitute of Health, Faculty of Public Health, Department of Health Policy, and Management, Jimma University, Jimma, Ethiopia.
Aleka Jeldu EdessaCollege of Business and Economics, Jimma University, Jimma, Ethiopia.
Dawit Wolde DakaInstitute of Health, Faculty of Public Health, Department of Health Policy, and Management, Jimma University, Jimma, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBreast cancer is an evolving non-communicable disease and a global disease burden, which accounts for a momentous portion of worldwide mortality and morbidity with significant economic impacts. In low- and middle-income countries like Ethiopia, the most common problem with cancer treatment is scarcity of medical resources, and financial supply, for providing care, which includes expensive medical costs, cost of service provision, and medical equipment. In Ethiopia, the cost of breast cancer care increased and imposed an enormous financial burden on healthcare providers and the healthcare system. The study aimed to estimate the annual total direct medical cost of breast cancer and identify the cost drivers of breast cancer treatment at Jimma University Medical Center (JUMC).

methodsA facility-based retrospective medical record review was employed using the provider's perspective. Both mixed bottoms-up and top-down costing approaches were used to estimate the cost. Medical records of 130 breast cancer patients who were diagnosed between September 2022 and August 2023 were reviewed retrospectively.

resultsThe mean age of patients was 41.9 (SD + 10.4) years. The total direct medical cost incurred at the hospital per patient to treat breast cancer across all stages was US$24,727 at JUMC. The total median cost per patient at the hospital to treat breast cancer at stages I, II, III, and IV could have been US$218.6, US$638.7, US$846.2, and US$753.4 respectively. At JUMC, the major cost drivers were the cost of drugs for chemotherapy accounts for 47.2%, followed by laboratory tests at 14.8%, and radiotherapy at 14.2%.

conclusionThe hospital's direct medical costs associated with breast cancer disease were extensive. The highest medical cost was incurred in stage III of the disease. The main cost drivers at JUMC were drugs for chemotherapy, laboratory tests, and radiotherapy (radiologic imaging) added higher direct medical costs followed by surgery and pathology. The stage-specific cost analysis study focused on cost identification and valuation that provides profound information related to the estimation of direct medical cost, and the main cost drivers of the disease, and helps to encourage the treatment and diagnosis of breast cancer at an early stage of the disease.

Indexed as

Breast cancerChemotherapyDirect medical costEthiopiaJUMCRetrospective analysisStage-specific

Identifiers

PMID41146283
PMCPMC12560421

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LicenceCC BY-NC-ND
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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.