The burden of household out-of-pocket health expenditures in Ethiopia: estimates from a nationally representative survey (2015-16)

In Ethiopia, little is known about the extent of out-of-pocket health expenditures and the associated financial hardships at national and regional levels. We estimated the incidence of both catastrophic and impoverishing health expenditures using data from the 2015/16 Ethiopian household consumption and expenditure and welfare monitoring surveys. We computed incidence of catastrophic health expenditures (CHE) at 10% and 25% thresholds of total household consumption and 40% threshold of household capacity to pay, and impoverishing health expenditures (IHE) using Ethiopia's national poverty line (ETB 7184 per adult per year). Around 2.1% (SE: 0.2, P < 0.001) of households would face CHE with a 10% threshold of total consumption, and 0.9% (SE: 0.1, P < 0.001) of households would encounter IHE, annually in Ethiopia. CHE rates were high in the regions of Afar (5.8%, SE: 1.0, P < 0.001) and Benshangul-Gumuz (4.0%, SE: 0.8, P < 0.001). Oromia (n = 902 000), Amhara (n = 275 000) and Southern Nations Nationalities and Peoples (SNNP) (n = 268 000) regions would have the largest numbers of affected households, due to large population size. The IHE rates would also show similar patterns: high rates in Afar (5.0%, SE: 0.96, P < 0.001), Oromia (1.1%, SE: 0.22, P < 0.001) and Benshangul-Gumuz (0.9%, SE: 0.4, P = 0.02); a large number of households would be impoverished in Oromia (n = 356 000) and Amhara (n = 202 000) regions. In summary, a large number of households is facing financial hardship in Ethiopia, particularly in Afar, Benshangul-Gumuz, Oromia, Amhara and SNNP regions and this number would likely increase with greater health services utilization. We recommend regional-level analyses on services coverage to be conducted as some of the estimated low CHE/IHE regional values might be due to low services coverage. Periodic analyses on the financial hardship status of households could also be monitored to infer progress towards universal health coverage.

The Dynamics of Catastrophic and Impoverishing Health Spending in Indonesia: How Well Does the Indonesian Health Care Financing System Perform?

Our study examines the incidence and intensity of catastrophic and impoverishing health spending in Indonesia. A panel data set was used from 4 waves of the Indonesian Family Life Surveys 1993, 1997, 2000, and 2007. Catastrophic health expenditure was measured by calculating the ratio of out-of-pocket payments to household income. Then, we calculated poverty indicators as a measure of impoverishing spending in the health care financing system. Head count, overshoot, and mean positive overshoot for each given threshold in 2000 were lower than other surveyed periods; otherwise, fraction headcount in 2007 of households were the higher. Between 1993 and 2007, the percentage of households in poverty decreased, both in gross and net of health payments. However, in each year, the percentages of households in poverty using net health payments were higher than the gross. The estimates of poverty gap, normalized poverty gap, and normalized mean positive gap decreased across the survey periods. The health care financing system performance has shown positive evidence for financial protection offerings. A sound relationship between improvements of health care financing performance and the existing health reform demonstrated a mutual reinforcement, which should be maintained to promote equity and fairness in health care financing in Indonesia.

Methodological Issues to Consider When Collecting Data to Estimate Poverty Impact in Economic Evaluations in Low-income and Middle-income Countries

Out-of-pocket spending is increasingly recognized as an important barrier to accessing health care, particularly in low-income and middle-income countries (LMICs) where a large portion of health expenditure comes from out-of-pocket payments. Emerging universal healthcare policies prioritize reduction of poverty impact such as catastrophic and impoverishing healthcare expenditure. Poverty impact is therefore increasingly evaluated alongside and within economic evaluations to estimate the impact of specific health interventions on poverty. However, data collection for these metrics can be challenging in intervention-based contexts in LMICs because of study design and practical limitations. Using a set of case studies, this letter identifies methodological challenges in collecting patient cost data in LMIC contexts. These components are presented in a framework to encourage researchers to consider the implications of differing approaches in data collection and to report their approach in a standardized and transparent way.