Treatment‐seeking behaviour, cost burdens and coping strategies among rural and urban households in Coastal Kenya: an equity analysis

Abstract

SummaryIll-health can inflict costs on households directly through spending on treatment and indirectly through impacting on labour productivity. The financial burden can be high and, for poor households, contributes significantly to declining welfare. We investigated socio-economic inequities in self-reported illnesses, treatment-seeking behaviour, cost burdens and coping strategies in a rural and urban setting along the Kenyan coast. We conducted a survey of 294 rural and 576 urban households, 9 FGDs and 9 in-depth interviews in each setting. Key findings were significantly higher levels of reported chronic and acute conditions in the rural setting, differences in treatment-seeking patterns by socio-economic status (SES) and by setting, and regressive cost burdens in both areas. These data suggest the need for greater governmental and non-governmental efforts towards protecting the poor from catastrophic illness cost burdens. Promising health sector options are elimination of user fees, at least in targeted hardship areas, developing more flexible charging systems, and improving quality of care in all facilities. The data also strongly support the need for a multi-sectoral approach to protecting households. Potential interventions beyond the health sector include supporting the social networks that are key to household livelihood strategies and promoting micro-finance schemes that enable small amounts of credit to be accessed with minimal interest rates.

Evaluating Treatment-Seeking Behavior and the Related Factors Among the Dwellers of Safashahr City

“…Consistent with this study, Chuma et al (2007) introduced place of living among factors effective on treatment-seeking behavior, with this difference that 20.1% of people in rural regions and 9.3% of people in urban regions who reported suffering from acute illness during the 2 weeks before study, did not seek any treatment and about chronic illness a similar pattern was observed (56.9 villagers, 44.9 citizens).…”

“…Designation of sufficient resources for health section could improve mortality statistics [9]. Awareness of treatment-seeking behavior could include total rate of benefiting from health-care services and also special information in this ground that who use what kind of health-care services and this service is provided from which source [10]. Generally, 69% of total cost of health section is highly influenced by consumption behavior [11].…”

Household Catastrophic Health Expenditure Due To Tuberculosis: Analysis From Particularly Vulnerable Tribal Group, Central India

“…This emphasizes the earlier point that it is also important to explore the extent to which households do not use services because of inability to pay. It was reported that availability of services proved to be positively correlated with catastrophic spending in low and middle income countries but not in high income countries [27,28]. In many other European countries health insurance coverage is very comprehensive and OOP payments are either absent or do not differ across provider alternatives [29].…”

Sensitivity of hospital-based surveillance for severe disease: a geographic information system analysis of access to care in Kilifi district, Kenya

“…Detailed, individual-level socioeconomic data are required to examine possible interactions between travel time and socioeconomic factors that influence care-seeking behaviour, including the effect of wealth on mode of transport choice. 32,33 Such data are not currently available for our study area, justifying our use of sublocation-level maternal education variables as the best available proxy: this is an important limitation in a setting where household finances are likely to be a key determinant of access to hospital care. We do not expect any confounding by immunization status given the high levels and limited geographic variations in vaccination coverage in Kilifi.…”