Determinants of catastrophic healthcare expenditure in Peru

Abstract

The aims of this study were to assess factors associated with catastrophic healthcare expenditure (CHE) and the burden of out-of-pocket (OOP) payments for specific healthcare services in Peru. We used data from 30,966 households that participated in the 2016 National Household Survey (Encuesta Nacional de Hogares, ENAHO). Participants reported household characteristics and expenditure on ten healthcare services. CHE was defined as healthcare spending equal to or higher than 40% of the household's capacity to pay. The associations of various household characteristics and OOP payments for specific healthcare services with CHE were assessed in logistic regression models. Poorer, rural and smaller households as well as those with older adults and individuals with chronic conditions had greater odds of facing CHE. According to the estimates from the adjusted regression model, healthcare services could be grouped into three groups. Medical tests, surgery and medication were in the first group with odds ratios (ORs) between 6.43 and 4.72. Hospitalisation, outpatient, dental and eye care were in the second group with ORs between 2.61 and 1.46. Child care, maternity care and other healthcare services (such as contraceptives, rehabilitation, etc.) were in the third group with non-significant ORs. Many Peruvian households are forced to finance their healthcare through OOP payments, burdening their finances to the extent of affecting their living standards.

The catastrophic and impoverishing effects of out-of-pocket healthcare payments in Kenya, 2018

“…Similarly, the bigger the household, the lower was the probability to incur catastrophic payments. This result might seem counterintuitive and differs from previous results for Kenya18 but is confirmed by similar findings for Peru28 and Ghana 29. The results also suggested that living in urban areas was positively correlated with the probability of incurring catastrophic payments (but statistically significant only for the indicator referring to 10% of total budget).…”

“…The explanatory variables of the model, similar to related literature,18 28 29 include a set of characteristics of the head of the household (age, gender, level of education, marital status, employment status), and a set of characteristics of the household, including the presence of at least one member enrolled into a health insurance scheme, total consumption expenditure in quintiles, household size, presence of chronic illness in the household, area of residence (urban/rural), presence of elderly people (aged 60 and more). The empirical analyses were performed in Stata V.14.…”

Gasto de bolsillo en salud en adultos mayores peruanos: análisis de la Encuesta Nacional de Hogares sobre Condiciones de Vida y Pobreza 2017

“…Estos hallazgos son consistentes con los resultados de Bock et al (6) , Gong et al (7) , Turi et al (10) y Corrieri et al (13) . La fuerte asociación reportada entre el nivel de GBS y los quintiles de gasto per cápita sugiere que la proporción GBS/gasto per cápita es desfavorable para los socialmente desaventajados, como Proaño y Bernabé lo señalan en su estudio (26) . Investigaciones de tipo longitudinal se requieren para evaluar a fondo los efectos del GBS en el riesgo financiero de los adultos mayores.…”

Aseguramiento universal en salud en el Perú: una aproximación a 10 años de su implementación

“…De similar forma, en los últimos 10 años, el gasto de bolsillo (pago al recibir el servicio en forma de medicamentos, copagos o deducibles) se ha mantenido por encima del 20% del gasto total en salud hasta el año 2016 11 . Asimismo, el gasto catastrófico en salud (gastos en salud que exceden el 40% de la capacidad de pago del hogar) no se ha reducido significativamente en el periodo 2006 -2016, pasó de un 5% a 4% de hogares afectados 13 .…”