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The purpose of this study was to classify determinants of cost increases into two categories, negotiable factors and non-negotiable factors, in order to identify the determinants of health care expenditure increases and to clarify the contribution of associated factors selected based on a literature review.
The data in this analysis was from the statistical yearbooks of National Health Insurance Service, the Economic Index from Statistics Korea and regional statistical yearbooks. The unit of analysis was the annual growth rate of variables of 16 cities and provinces from 2003 to 2010. First, multiple regression was used to identify the determinants of health care expenditures. We then used hierarchical multiple regression to calculate the contribution of associated factors. The changes of coefficients (R2) of predictors, which were entered into this analysis step by step based on the empirical evidence of the investigator could explain the contribution of predictors to increased medical cost.
Health spending was mainly associated with the proportion of the elderly population, but the Medicare Economic Index (MEI) showed an inverse association. The contribution of predictors was as follows: the proportion of elderly in the population (22.4%), gross domestic product (GDP) per capita (4.5%), MEI (-12%), and other predictors (less than 1%).
As Baby Boomers enter retirement, an increasing proportion of the population aged 65 and over and the GDP will continue to increase, thus accelerating the inflation of health care expenditures and precipitating a crisis in the health insurance system. Policy makers should consider providing comprehensive health services by an accountable care organization to achieve cost savings while ensuring high-quality care.
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The goal of this study was to perform an economic analysis of a primary stenting with drug-eluting stents (DES) compared with bare-metal stents (BMS) in patients with acute myocardial infarction (AMI) admitted through an emergency room (ER) visit in Korea using population-based data.
We employed a cost-minimization method using a decision analytic model with a two-year time period. Model probabilities and costs were obtained from a published systematic review and population-based data from which a retrospective database analysis of the national reimbursement database of Health Insurance Review and Assessment covering 2006 through 2010 was performed. Uncertainty was evaluated using one-way sensitivity analyses and probabilistic sensitivity analyses.
Among 513 979 cases with AMI during 2007 and 2008, 24 742 cases underwent stenting procedures and 20 320 patients admitted through an ER visit with primary stenting were identified in the base model. The transition probabilities of DES-to-DES, DES-to-BMS, DES-to-coronary artery bypass graft, and DES-to-balloon were 59.7%, 0.6%, 4.3%, and 35.3%, respectively, among these patients. The average two-year costs of DES and BMS in 2011 Korean won were 11 065 528 won/person and 9 647 647 won/person, respectively. DES resulted in higher costs than BMS by 1 417 882 won/person. The model was highly sensitive to the probability and costs of having no revascularization.
Primary stenting with BMS for AMI with an ER visit was shown to be a cost-saving procedure compared with DES in Korea. Caution is needed when applying this finding to patients with a higher level of severity in health status.
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