Abstract BackgroundUniversal health coverage is high on national health agendas of many countries at the moment. Absence of financial hardship is a key component of universal health coverage and should be monitored regularly. However, relevant household survey data, which is traditionally needed for this analysis is not frequently collected in most countries and in some countries, has not been collected at all. As such, proxy indicators for financial hardship would be very useful.MethodsWe use data from the World Health Survey and use multi-level modeling with national and household level characteristics to see which indicators have a consistent and robust relationship with financial hardship. To strengthen the validity of our findings, we also use different measures of financial hardship.ResultsThere are several household level characteristics that seem to have a consistent relationship with financial hardship. However there is only one strong candidate for a proxy indicator at the national level¿ the share of out-of-pocket payments in total health expenditure. Additionally, the Gini coefficient of total household expenditure was also correlated to financial hardship in most of our models.ConclusionThe national level indicators related only weakly to the risk of financial hardship. Hence, there should not be an over-reliance on them and collecting good quality household survey data is still a superior option for monitoring financial hardship.

Inputs for universal health coverage: a methodological contribution to finding proxy indicators for financial hardship due to health expenditure

TEDIOSI, FABRIZIO
2014

Abstract

Abstract BackgroundUniversal health coverage is high on national health agendas of many countries at the moment. Absence of financial hardship is a key component of universal health coverage and should be monitored regularly. However, relevant household survey data, which is traditionally needed for this analysis is not frequently collected in most countries and in some countries, has not been collected at all. As such, proxy indicators for financial hardship would be very useful.MethodsWe use data from the World Health Survey and use multi-level modeling with national and household level characteristics to see which indicators have a consistent and robust relationship with financial hardship. To strengthen the validity of our findings, we also use different measures of financial hardship.ResultsThere are several household level characteristics that seem to have a consistent relationship with financial hardship. However there is only one strong candidate for a proxy indicator at the national level¿ the share of out-of-pocket payments in total health expenditure. Additionally, the Gini coefficient of total household expenditure was also correlated to financial hardship in most of our models.ConclusionThe national level indicators related only weakly to the risk of financial hardship. Hence, there should not be an over-reliance on them and collecting good quality household survey data is still a superior option for monitoring financial hardship.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11565/3953320
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