The Cost of Survival: Economic Barriers to Trauma Care in Ethiopia

Trauma is a leading cause of global mortality, accounting for over five million deaths annually, with nearly 90% disproportionately occurring in low- and middle-income countries (LMICs)[1-3]. The lack of emergency medical personnel, prehospital trauma protocols, integrated trauma systems, health services infrastructure, community awareness, and economic barriers collectively compromise standards of care, as well as reinforce trauma-related inequities worldwide.

Ethiopia, one of Africa’s most populous and rapidly developing nations, faces significant barriers to healthcare, with nearly a quarter of its population living below the poverty line (set at 7,184 ETB per adult annually)[4, 5]. Trauma injuries pose a significant public health challenge among these conditions, where the most common cases in Ethiopia result from road traffic collisions (21.0-62.5%), falls (20.8-33.2%), and interpersonal violence (19.2-30.1%)[6-13]. In 2019 alone, there was an estimated 8.1 million new trauma cases nationwide, underscoring the urgent need for improved trauma care access[14].

The country’s total health expenditure has grown steadily over the past decade through different financing sources, including the government treasury (federal, regional, and woreda/district levels), donations (bilateral and multilateral), household out-of-pocket (OOP) expenditure, community-based health insurance (voluntary prepayment), and private employers[15]. Despite increased health sector investment, OOP expenditures remain a substantial financial burden, accounting for nearly one-third of total healthcare costs and pushing close to a million people into poverty annually[16-18].

High injury burdens and OOP costs deepen poverty in the nation, as well as reinforce trauma-related inequities and chronic barriers to care in LMICs. Addressing these economic barriers is critical to achieving Ethiopia’s Health Sector Transformation Plan (HSTP-II) and aligning with global initiatives such as the United Nations Sustainable Development Goals (SDG 1: No Poverty, SDG 3: Good Health & Well-Being)[19-22]. With limited research available on the economic barriers to trauma care in Ethiopia and Sub-Saharan Africa more broadly, there is an urgent need to fill this knowledge gap to inform effective policies and improve access to care across the region.

This study evaluated the financial impact of trauma care on a cross-sectional sample of patients at the Hawassa University Comprehensive Specialized Hospital (HUCSH), a public tertiary hospital in Southern Ethiopia. Key objectives included assessing (1) the proportion of trauma patients facing economic barriers and (2) the financial impact of trauma-care expenditures. The findings will inform policy development, guide interventions, and strengthen Ethiopia’s trauma-care infrastructure.

Survey Development 

A validated survey from Hawassa University School of Public Health was adapted[23]. It included up to 78 items, with 12 branching questions and three enrollment descriptors, collectively utilized to assess demographics, household income and expenditure, healthcare expenditures, and financial coping strategies. All costs were recorded in Ethiopian Birr (ETB), with an exchange rate of approximately 55 ETB to 1 USD during the study period.

Recruitment

Between June and August 2023, adult trauma patients presenting to the Emergency Department at HUCSH were recruited through convenience sampling. Exclusion criteria were active pregnancy, imprisonment, and age < 18 years. As a primary trauma center in Hawassa, the capital of Sidama, and the Southern Nations, Nationalities, and Peoples' Region, HUCSH serves over 20 million people across four provinces, making it an essential referral center for trauma care in Ethiopia[24].

Data Acquisition

Informed consent and survey responses were obtained through interviews conducted by local emergency department personnel fluent in Amharic. Interviews were conducted in the participants’ primary or preferred language, with responses documented in English-on-paper surveys. For incapacitated patients, family members provided consent and responses. Inpatient expenditures were tracked daily, with participants reporting care-related payments verbally or via hospital receipts. Surveys were completed upon patient discharge, with total hospital expenditures documented for transportation, registration, admission, bed occupancy, doctor fee, investigations, medication, bandages, surgery, and food.

Data Management and Statistics

Study data were digitized and managed using Research Electronic Data Capture (REDCap), hosted by the Epidemiology Division at the Medical College of Wisconsin. Statistical analyses were performed using REDCap and Stata SE 18.0. Categorical variables were reported as N (%) and continuous variables as median (IQR). Statistical significance was set at P < 0.05.

Total Cost of Care Associations

Univariate associations between categorical variables and total care costs were assessed using the Mann-Whitney U or Kruskal-Wallis test, with Dunn’s post-hoc test for pairwise comparisons. Linear regression was used to analyze associations with continuous variables. Significant factors from the univariate analysis were included in a stepwise multivariable regression model to predict total care costs using forward selection (P < 0.1). Model adequacy was evaluated using R-squared and adjusted R-squared values to account for multicollinearity.

Catastrophic Health Expenditure

Catastrophic health expenditure (CHE) was defined as total care costs exceeding 10% of annual household income per SDG 3.8.2. Univariate associations with CHE were assessed using the chi-square test for categorical variables and Mann-Whitney U test for continuous variables. Significant factors from univariate analysis were included in a logistic regression model to predict CHE, with results reported as Odds Ratios (OR) and 95% Confidence Intervals (CI).

Ethical Approval

The study was approved by the International Review Boards of the Medical College of Wisconsin and Hawassa University College of Medicine and Health Sciences.

Demographics

A total of 97 patients were enrolled over 62 days (June 15 to August 15, 2023). Most were aged 18–39 years (N=79, 79.4%), with 79 (81.4%) being male (Table 1). More than half (55.7%) had formal education. The most common occupations were farming (N=24, 24.7%), daily labor (N=14, 14.3%), and student or private sector employment (N=12, 12.4% each). Of all respondents 86 (88.7%) were uninsured. Insurance status was not associated with any demographic variables.

Mechanism of Injuries

Blunt injuries accounted for 86.6% (n=84), penetrating injuries (N=11, 11.3%), and other injuries (N=2, 2.1%). Motor vehicle collisions were the leading cause (64.9%), followed by violence-related blunt force (10.3%), falls (9.3%), and violence-related penetrating force (7.2%). The less common causes included gunshots (3.1%), unspecified blunt (2.1%) and penetrating (1%) injuries, electrical burns (1%) and strangulation (1%)[25].

Healthcare Expenditure

The median total cost of care was 10,428 ETB [IQR: 4,507–22,417] (Figure 1A). As can be seen in figure 2, admission fees were the highest median cost at 3,500 ETB, with the exception of one ICU admission (9,500 ETB) and one direct-to-OR case (4,000 ETB). Medication supplies had the next highest median cost (2,427 ETB [IQR: 1,020–7,654]), followed by food (1,600 ETB [IQR: 400-3000]), transportation (1,000 ETB [IQR: 200-4000]), and investigations/tests (960 ETB [IQR: 580-2960]). Registration fees were uniformly 60 ETB, except for one insured patient (0 ETB). Fifteen patients incurred costs below 3,500 ETB due to partial hospital reimbursement.

Predictors of Cost

Demographic factors associated with cost included patients from the Sidama region (7,254 vs. 19,298 ETB; P < 0.001, Table 2), rural patients (15,676 vs. 7,732 ETB; P = 0.011), and total household members (coefficient = 1,253.8; 95% CI: 374.1-2,133.4; P = 0.006, Table 3). Hospital stay factors included surgical patients (20,459 vs. 7,033 ETB; P < 0.001) and length of stay (coefficient = 2,158.5; 95% CI: 1,854.4-2,462.7; P < 0.001).

The final stepwise regression model (adjusted R² = 0.7498) identified rural residence (coefficient = 3,094.1; P = 0.026), surgical treatment (coefficient = 2,884.2; P = 0.039), and length of stay (coefficient = 2,034.5; P < 0.001) as cost-increasing factors, whereas Sidama residency was associated with lower costs (coefficient = -6,132.1; P < 0.001) (Figure 2).

Analysis of Predictors

Figure 3 and Supplement 1 shows hospitalization costs stratified by predictors in the multivariable model. Rural patients had significantly higher median medication (4,313.5 vs 1,420 ETB) and transportation (2,000 vs 200 ETB) costs. Patients undergoing surgery incurred increased costs across most categories, except for transportation. Non-Sidama patients had higher hospital bed, food, and transportation costs. Longer hospital stays were associated with increased costs in all categories, except transportation (Table 4).

Catastrophic Health Expenditure

Of the 91 patients (93.8%) reporting annual household income, 4 (4.4%) had zero income. The median income was 113,000 ETB. CHE affected 50.5% of patients (Figure 4), with 35 (38.0%) patients spending 10–39.9% of their income on care, 4 (4.4%) patients spending 40–99.9%, and 3 (3.3%) exceeding 100%. CHE was more common in rural patients (61.8% vs. 39.6%; P = 0.044) and surgical patients (70.0% vs. 29.8%; P < 0.001; Supplement 2). Patients with CHE had significantly lower median head income (57,000 vs. 180,000 ETB; P < 0.001), total household income (180,000 vs. 86,500; P < 0.001), shorter travel times (2 vs. 4 h; P = 0.0245), longer hospital stays (4.5 vs. 2 days; P < 0.001), and lower monthly expenses (31,625 vs. 40,179 ETB; P = 0.0076, Supplement 3). On multivariate analysis, length of stay (OR = 3.22; 95% CI: 1.54–6.78; P = 0.002), and total household income (OR = 0.99; 95% CI: 0.99-0.99; P = 0.037) were associated with CHE (Table 5).

Coping Mechanisms

Nearly half (N = 46, 47.4%) of the patients took out loans for healthcare expenses (Table 6). Most loans were from family (N = 32, 69.6%) or friends/neighbors (N = 10, 21.7%). Three patients did not specify the source. Additionally, 39 people (40.3%) sold belongings or property to cover costs. Most (N = 95, 97.9%) did not disrupt their children’s education or reduce payments to afford care.

This study highlights persistent economic barriers to trauma care in Ethiopia, emphasizing the financial burden on patients at HUCSH. Nearly 90% of participants lacked health insurance, underscoring out-of-pocket (OOP) payments as a key determinant of access to care. The median total cost per patient was 10,428 ETB (190 USD), with daily hospital expenses being about 2,158 ETB—approximately 1.9% of annual household income (113,000 EB, data not shown). Half of the cohort (50.5%) experienced CHE, which disproportionately affected lower-income households.

The key cost drivers included rural residence, surgical treatment, and prolonged length of stay each adding approximately 2,000 – 3,000 ETB to the total expenses. Rural patients incurred greater travel costs as well as higher medication costs, for reasons that are not entirely clear. Residence within the Sidama region, where this study was performed, provided a protection from higher costs by nearly 6,100 ETB. This was due to less transportation costs – given that patients were local – as well as lower food costs, seemingly due to the fact that patient family members could likely bring them food from home. Expanding financial risk protection should be prioritized through insurance reforms and trauma care subsidies, particularly for rural patients, while improving access in rural areas through mobile medical units and regional trauma centers. Hospital-level strategies, including Enhanced Recovery After Surgery (ERAS) pathways, can optimize resource use, reduce hospitalization duration, and alleviate financial constraints[26].

Trauma care imposes a significant financial burden on patients in Southern Ethiopia, reinforcing global health inequities that disproportionately impact LMICs. The Federal Democratic Republic of Ethiopia has long demonstrated an active pursuit of addressing disparity gaps, pioneering innovative strategies that consider the country’s global commitments and align with its overall macro-economic development framework[27]. While initiatives such as the HSTP-II outline comprehensive strategies to improve national healthcare systems, significant challenges remain in targeting and prioritizing areas for improvement without reliable documentation and a comprehensive understanding of the care provided at the patient level[28].

Addressing trauma-related health inequities is essential to Ethiopia’s broader healthcare and economic development. Our findings underscore the need for targeted interventions to expand healthcare access, strengthen emergency services, and mitigate CHE.  Expanding this research nationally will enhance understanding of patient-level care and guide sustainable policy reforms to improve equitable access to trauma care. Future studies should assess cost variability across multiple centers and explore sustainable financing models for trauma care in Ethiopia.

Limitations

This study had several limitations. Convenience sampling, while appropriate for recruitment within the study period and resource constraints, may have introduced selection and volunteer bias. As a single-center study, results may not fully capture regional cost variations or differences in care delivery across other LMIC settings. Additionally, the use of English surveys risked translation discrepancies, as interviews in Amharic could lead to inconsistencies in question delivery. Lastly, while missing data were minimal, they may still have influenced specific subgroup analyses.

This study illustrates the substantial economic burden associated with trauma care in Southern Ethiopia, with over half of patients incurring catastrophic health expenditures. Rural residence, surgical intervention, and longer hospital stays were key cost drivers, while limited insurance coverage forced many to rely on loans or asset sales. Although residence in the Sidama region offered some cost protection, the overall reliance on out-of-pocket spending underscores broader systemic gaps in financial risk protection.

These findings reflect wider challenges faced in many low- and middle-income countries, where trauma disproportionately affects lower-income populations and deepens health inequities. Strengthening trauma systems through regional investment, mobile care delivery, and hospital-based cost-reduction strategies is critical. As Ethiopia advances toward national health goals under HSTP-II and broader global targets like the Sustainable Development Goals, addressing the economic barriers to trauma care will be vital. Future research across multiple centers can further inform equitable and sustainable financing models for trauma care in similar settings.

We acknowledge Hawassa University Comprehensive Specialized Hospital, Medical College of Wisconsin Office of Global Health, and the Dr. Elaine Kohler Summer Academy of Global Health Research Fellowship. We also extend our gratitude to the participants, their families, and the emergency department staff, especially Abiyot Gete and Wondimagegn Abebe, for their support in data collection.