Household Size and the Decision to Purchase Health Insurance in Cambodia: Results of a Discrete-Choice Experiment with Scale Adjustment

Background Community-based health insurance (CBHI) schemes have been introduced in low-and middle-income countries to increase health service utilization and provide financial protection from high healthcare expenditures. Objective We assess the impact of household size on decisions to enroll in CBHI and demonstrate how to correct for group disparity in scale (i.e. variance differences). Methods A discrete choice experiment was conducted across five CBHI attributes. Preferences were elicited through forced-choice paired comparison choice tasks designed based on D-efficiency. Differences in preferences were examined between small (1-4 family members) and large (5-12 members) households using conditional logistic regression. Swait and Louviere test was used to identify and correct for differences in scale. Results One-hundred and sixty households were surveyed in Northwest Cambodia. Increased insurance premium was associated with disutility [odds ratio (OR) 0.61, p< 0.01], while significant increase in utility was noted for higher hospital fee coverage (OR 10.58, p< 0.01), greater coverage of travel and meal costs (OR 4.08, p< 0.01), and more frequent communication with the insurer (OR 1.33, p< 0.01). While the magnitude of preference for hospital fee coverage appeared larger for the large household group (OR 14.15) compared to the small household group (OR 8.58), differences in scale were observed (p< 0.05). After adjusting for scale (k, ratio of scale between large to small household groups = 1.227, 95 % confidence interval 1.002-1.515), preference differences by household size became negligible. Conclusion Differences in stated preferences may be due to scale, or variance differences between groups, rather than true variations in preference. Coverage of hospital fees, travel and meal costs are given significant weight in CBHI enrollment decisions regardless of household size. Understanding how community members make decisions about health insurance can inform low-and middle-income countries' paths towards universal health coverage.