| Hypertension is a chronic disease widely distributed in China and even in the world.Hypertension can easily lead to a series of cardiovascular and cerebrovascular diseases,which are not only expensive for related treatment,but also reduce the quality of life of patients,and even endanger the life of patients.Therefore,it is necessary to use antihypertensive drugs in advance to slow down the further deterioration of hypertension.However,in the face of different antihypertensive mechanisms,the choice of antihypertensive drugs is critical.This requires researchers to consider the efficacy and safety of different treatment options,but also pay attention to the economic benefits brought by the treatment plan to the patients,the medical system,and the society,so as to promote the rational allocation of medical resources.In view of this,based on the Markov model and the evaluation method of pharmacoeconomics,this paper is the first to use the Python programming language to conduct programming analysis research on this topic.From the social point of view,the pharmacoeconomics of the two first-line antihypertensive drugs,valsartan and amlodipine,are analyzed to evaluate more cost-effective treatment options,and to provide decision-making information for policy makers and patients.To understand the long-term changes and outcomes of chronic diseases such as hypertension,this study constructed a Markov model to simulate disease progression in patients taking antihypertensive drugs.Firstly,according to the evolution of hypertensive disease and the possible main progress results,we need to determine the main transfer state and transfer process of the model,Set the model simulation period to 40 years,and each year is a simulation cycle.Secondly,the relevant parameters of the model,such as transfer probability,health utility,cost,and discount rate,were determined through published relevant clinical cohort studies and published literature.Finally,according to the results of the model simulation,a pharmacoeconomic evaluation was performed to analyze the cost-effectiveness of the two drug treatment options.In order to further understand the influence of the uncertainty factors of each parameter on the model results,a single factor sensitivity analysis was performed on the model,and a probabilistic sensitivity analysis was performed using Monte Carlo simulation.95% confidence intervals for the relevant results were calculated and cost-effectiveness acceptance curves were estimated using the net benefit method.The results showed that after 40 cycles of Markov model simulation,with valsartan as the baseline,the average incremental cost of amlodipine was 739.03 yuan,the average incremental utility was 0.1016 quality-adjusted life years(QALY),and the average incremental cost-effectiveness ratio was 7273.91 yuan/QALY,that is,compared with the valsartan regimen,if the amlodipine regimen costs an extra 7273.91 yuan,one more QALY can be added.If the willingness to pay threshold is the per capita GDP(80,976yuan/QALY),it is completely worthwhile to adopt the amlodipine program.On the other hand,a sensitivity analysis was performed on the model to test the robustness of the model.Among them,the univariate sensitivity analysis shows that the parameter variation within the preset variation range does not affect the conclusion of the model.Using Monte Carlo to simulate 1000 samples of the two programs,and conduct a probability sensitivity analysis,under the set willingness to pay threshold,the possibility of choosing the amlodipine program is 61.4%.The bootstrap method is used to estimate the incremental net benefit.The estimation is 9911.38 yuan(95%CI: 5075.80 yuan ～ 14848.12yuan).After a series of studies and analysis,using Python to program the Markov model can better simulate the general progress of antihypertensive drugs,and the pharmacoeconomic evaluation results are credible.Under the premise of limited medical resources,choosing amlodipine treatment plan can maximize the clinical benefit. |
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