Preference elicitation approach for measuring the willingness to pay for liver cancer treatment in Korea.

BACKGROUND/AIMS: The Korean government has expanded the coverage of the national insurance scheme for four major diseases: cancers, cardiovascular diseases, cerebrovascular diseases, and rare diseases. This policy may have a detrimental effect on the budget of the national health insurance agency. Like taxes, national insurance premiums are levied on the basis of the income or wealth of the insured. METHODS: Using a preference elicitation method, we attempted to estimate how much people are willing to pay for insurance premiums that would expand their coverage for liver cancer treatment. RESULTS: We calculated the marginal willingness to pay (MWTP) through the marginal rate of substitution between the two attributes of the insurance premium and the total annual treatment cost by adopting conditional logit and mixed logit models. CONCLUSIONS: The effects of various other terms that could interact with socioeconomic status were also estimated, such as gender, income level, educational attainment, age, employment status, and marital status. The estimated MWTP values of the monthly insurance premium for liver cancer treatment range from 4,130 KRW to 9,090 KRW.

Size prediction of recombinant human growth hormone nanoparticles produced by supercritical fluid precipitation.

Solution-enhanced dispersion by supercritical fluids (SEDS) was applied to produce nano-sized recombinant human growth hormone (hGH) particles. Ethanol was used to help the supercritical carbon dioxide to extract water from the aqueous protein solution. Various sizes of hGH nanoparticles were successfully prepared with a narrow particle size distribution from aqueous ethanol solution without using any additive. The theoretical particle sizes were deduced from the calculated droplet sizes based on a modified Jasuja's equation. The calculated mean particle sizes and the experimentally obtained ones were compared and the results showed an excellent correlation coefficient (R (2)) of 0.995.