Willingness-to-pay for community-based insurance in Burkina Faso.
OBJECTIVE
To study the willingness-to-pay (WTP) for a proposed community-based health insurance (CBI) scheme in order to provide information about the relationship between the premium that is required to cover the costs of the scheme and expected insurance enrollment levels. In addition, factors that influence WTP were to be identified.


METHODS
Data were collected from a household survey using a two-stage cluster sampling approach, with each household having the same probability of being selected. Interviews were conducted with 2414 individuals and 705 household heads. The take-it-or-leave-it (TIOLI) and the bidding game were used to elicit WTP.


RESULTS
The average individual was willing to pay 2384 (elicited by the TIOLI) or 3191 (elicited by the bidding game) CFA (3.17 US dollars or 4.25 US dollars) to join CBI for him/herself. The head of household agreed to pay from 6448 (elicited by the TIOLI) or 9769 (elicited by the bidding game) CFA (8.6 US dollars or 13.03 US dollars) to join the health insurance scheme for his/her household. These results were influenced by household and individual ability-to-pay, household and individual characteristics, such as age, sex and education. The two methods yielded similar patterns of estimated WTP, in that higher WTP was obtained for higher income level, higher previous medical expenditure, higher education, younger people and males. A starting point bias was found in the case of the bidding game.


CONCLUSIONS
Both TIOLI and bidding game methods can elicit a value of WTP for CBI. The value elicited by the bidding game is higher than by the TIOLI, but the two approaches yielded similar patterns of estimated WTP. WTP information can be used for setting insurance premium. When setting the premiums, it is important to consider differences between the real market and the theoretical one, and between the WTP and the cost of benefits package. The beneficiaries of CBI should be enrolled at the level of households or villages in order to protect vulnerable groups such as women, elders and the poor.
D000328:Adult; D000368:Aged; D001294:Attitude to Health; D002050:Burkina Faso; D002391:Catchment Area, Health; D003657:Decision Making; D003906:Developing Countries; D005191:Family Characteristics; D005249:Fees and Charges; D005260:Female; D005382:Financing, Personal / Q000706:statistics & numerical data*; D006801:Humans; D007348:Insurance, Health / Q000191:economics*; D007407:Interviews as Topic; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D019035:Rural Health Services / Q000191:economics; D026712:Value of Life / Q000191:economics*