As Medicare fees decrease, risk plans may gain favor.

This paper studies the relationship between health status and insurance participation, and between insurance status and medical use in the context of a social health insurance with an equalization fund (SHIEF). Under this system, revenues from a mandatory payroll tax are collected into a single pool (equalization fund) that reimburses for-profit insurance companies according to a capitated formula. Although competition should induce insurers to control costs without reducing the quality of service necessary to attract consumers, limitations in the capitation formula might induce insurers to select against bad risks, and limitations in the contribution system might induce more healthy individuals to evade enrollment. A three-equation model having social health insurance, private health insurance, and using medical services is estimated using a 1997 Colombian household survey. Consistent with similar studies, participation in SHIEF increases medical care use. On the other hand, the evidence on selection is somewhat mixed: individuals who report good health status are more likely to participate in SHIEF, while those without a chronic condition are less likely to participate in SHIEF.

Capitation Fee↗

PubMed2003

Modelling supply and demand influences on the use of health care: implications for deriving a needs-based capitation formula.

Many health-care systems allocate funding according to measures of need. The utilisation approach for measuring need rests on the assumptions that use of health care is determined by demand and supply and that need is an important element of demand. By estimating utilisation models which allow for supply it is possible to isolate the socio-economic and health characteristics which affect demand. A subset of these variables can then be identified by a combination of judgement and further analysis as needs variables to inform funding allocations. We estimate utilisation models using newly assembled data on admissions to acute hospitals, measures of supply, morbidity and socio-economic characteristics for 8414 small geographical areas in England. We make a number of methodological innovations including deriving additional measures of specific morbidities at small area level from individual level survey data. We compare models with different specifications for the effect of waiting times and provider characteristics, with total, planned and unplanned hospital admissions, and estimated at small area (ward) and primary care organisation (general practice) level. After allowing for waiting times, distance, capacity and the availability of private health care, measures of mortality, self-reported morbidity, low education and low income increase the use of health care. We find evidence of horizontal inequity with respect to ethnicity and employment and suggest a method for reducing its effects when deriving a needs-based allocation formula.

Capitation Fee↗