title: [Study on optimizing the reimbursement scheme under the New Rural Cooperative Medical System, based on Monte Carlo simulation].
abstract: OBJECTIVE
  To explore the application of Monte Carlo simulation in optimizing and adjusting the reimbursement scheme with regard to the New Rural Cooperative Medical System (NCMS) to scientific steering practice. Optimization of the reimbursement scheme in rural areas of China was also studied.
  
  
  METHODS
  A multi-stage sampling household survey was conducted in Sihui county, with 4 433 rural residents from 1 179 households from 13 towns in Guangdong province surveyed by self-designed questionnaire. Probit Regression Model was applied in fitting data and then estimating the own-price elasticity and cross elasticity of healthcare demand for both outpatients and inpatients. Monte Carlo simulation model was constructed to estimate the reimbursement effects of various alternative reimbursement schemes, by replicated simulation for one thousand times and each sampling on five hundred households. In this way, optimization of the implemented reimbursement scheme in Sihui county was conducted.
  
  
  RESULTS
  Own-priced elasticity of demands for outpatient visit, inpatient visit in the township hospital center, secondary hospital and tertiary hospital were -0.174, -0.264, -0.675 and -0.429, respectively. Outpatient demand was affected by the per-visit price of township hospital center and secondary hospital. The cross-priced elasticity of demands for outpatient visit appeared to be 0.125 and 0.150. The reimbursement effects of Scheme B7 showed that the efficiency of NCMS fund was 17.85% , the reimbursement ratio for healthcare was 25.63%, and the decreased percentages of poverty caused by illness was 18.25%, more than 9.37%, from the implemented scheme A. So the implemented scheme was in need for optimization.
  
  
  CONCLUSIONS
  Monte Carlo simulation technique was applicable to simulate the effects of the optimized alternative reimbursement scheme of NCMS and it provided a new idea and method to optimize and adjust the reimbursement scheme.
authors.affiliation: Department of Health Service Management, Humanities and Management School, Wenzhou Medical University, Wenzhou 325000, China.
authors.forename: Xuehui
authors.initials: X
authors.lastname: Meng
authors.affiliation: Department of Health Service Management of Public Health School.
authors.forename: Yixiang
authors.initials: Y
authors.lastname: Huang
authors.affiliation: Department of Health Service Management of Public Health School.
authors.forename: Shaolong
authors.initials: S
authors.lastname: Wu
authors.affiliation: Department of Epidemiology, Cancer Center, Sun Yat-Sen University. Email: liuqingsysu@aliyun.com.
authors.forename: Qing
authors.initials: Q
authors.lastname: Liu
mesh_terms: D000293:Adolescent; D000328:Adult; D002681:China; D005260:Female; D006801:Humans; D007349:Insurance, Health, Reimbursement / Q000191:economics*; D008297:Male; D008875:Middle Aged; D009010:Monte Carlo Method; D012424:Rural Population / Q000706:statistics & numerical data*; D055815:Young Adult