Willingness to Pay for Health Insurance among Urban Poor: An Evidence from Urban Primary Health Care Project in Bangladesh

Background and Objective: With the growing concern over treatment cost in health care and the desire to improve the effectiveness and equality of healthcare financing and the quality of the care, policy-makers have turned their attention to health insurance, especially, for the poor. This study attempted to determine the willingness to pay for health insurance among the mothers who utilized the urban primary health care clinic (UPHCC) for maternal and child health. Methods: This cross-sectional study was carried out in the working areas of UPHC Project in Bangladesh following two-stage cluster sampling technique to select the participants. Data were collected from 3949 women aged 15-49 years having at least one child aged two years or less. The data on willingness to pay for health insurance was collected using the contingent valuation method with bidding style. Data analysis was done by SPSS 22.0 version. Two generalized linear models with binary logit link function and normal identity link function were developed to identify the potential predictors for willingness to pay for monthly health insurance. Results: Three-fifths (67.5%) of the respondents agreed to pay for monthly health insurance. The median monthly premium for health insurance was BDT 15.5. Multivariate analysis revealed that utilization of UPHC clinic, quality of life, family size, age, wealth index, level of education, husband and respondent's occupation, ownership status of the house, religion and family income appeared to be potential predictors for health insurance (p<0.05). However, utilization of UPHC clinic and quality of life appeared to be important predictors across all the models. Conclusion: A large proportion of the community agreed to pay premium for health insurance. Based on the finding of the current study the policy makers might consider introducing a scheme for health insurance especially among the urban poor.