Abstract
Background: Economic theory and earlier empirical evidence suggest that patients will use fewer health services when they have to pay more for them. However, that copayment had little or no effect on visits to physicians. Objectives: This study exploits a natural experiment in Taiwan to estimate the effect of an increase in copayment on the demand for physician services and prescription drugs across the different dimensions of age, illness severity and patient behavior. Methods: Data were taken from the National Health Research Institute (NHRI) in Taiwan for the period of 1998 to 2000 and contained enrollment and claims files from a randomly chosen 0.2% of Taiwan’s population. The deletion of observations with missing values for any of the dependent or independent variables resulted in a final sample size of 69 768 individuals. The basic empirical strategy is to pool the data over the two years in question and estimate the effects of the reform by comparing the expected number of visits before and after the reform. We explored several alternatives stratifying the treatment in order to improve the quality of the identification. Results: We found that the reduction in visits was rather conservative with the DD estimates ranging from -0.08 to -0.17 compared to the estimate of -0.38 without stratification. The reform effect will most likely be exaggerated if the unobserved heterogeneity of the individual, such as health status and behavior, is not considered in the model.
Highlights
This study constructed two trajectories of patient’s medical cost incurred and his/her predicted morbidity respectivelyin assessing the effect of health policy
Most literature relied on a natural experiment under a National Health Insurance (NHI) scheme where certain groups of the population exempted
We provide a brief description of the copayment reform under Taiwan’s NHI and the data that was employed in this study
Summary
This study constructed two trajectories of patient’s medical cost incurred and his/her predicted morbidity respectivelyin assessing the effect of health policy. It is well known that randomly assigning a control group is important in the assessment of policy reforms or new interventions [1] It may not always be possible for researchers to implement a randomized experiment. The candidates for the control group may be too different to provide good matches for those in the treatment group [3] This type of heterogeneity is important in assessing the reform effect for two reasons. An unobserved individual’s health risk may generate significant influences on health care demand, which should not be attributed to the price effect of the increases in cost sharing Behavioral idiosyncrasies such as the propensity to seek health care given the same morbidity level might differ in unobservable but systematic ways between individuals. That copayment had little or no effect on visits to physicians
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