Secondary Clinical Pathway Planning For Cardiovascular Disease With Complications

The prevalence and mortality of cardiovascular diseases are increasing year by year,which has seriously threatened human health.With the complication and diversification of the disease,the medical expenses are gradually increasing,and the medical quality are gradually declining.As a standardized diagnosis and treatment process,the clinical pathway can effectively improve the medical quality of cardiovascular diseases,reduce the number of treatment days and medical expenses.However,the standard clinical pathway diagnosis and treatment process is only for a single disease.Cardiovascular disease has complexity and fuzzy uncertainty,often followed by one or more complications on clinically.When the clinical pathway are carried out,once the patient has complications,the patient can only withdraw from the clinical pathway.This has led to the clinical pathway for cardiovascular disease an increase in the variation and a decline in the medical quality,which is violating the original purpose of the clinical pathway.This is the current research focus for clinical pathway optimization to optimized the clinical pathway for cardiovascular disease with complications.This research project proposes a secondary clinical pathway optimization method for the clinical pathway of optimized the cardiovascular disease with complications.Using this method to optimize the clinical pathway is advantageous to expanding the coverage of cardiovascular diseases,reducing the clinical pathway variation caused by complications.The main research contents of this paper are as follows:(1)Analysis the large number of medical data,selection of Department of Cardiovascular Medicine diabetes plus hypertension as the original disease of the study.By calculating the concurrency rate of complications,the highest concurrency rate of angina was selected as the diseases of the study.(2)Using the division method of the treatment unit,the clinical pathway of the original disease and the complications are divided and merged according to themedical order and the treatment efficacy,then completed clinical pathway of the original disease and the complications.(3)Taking diabetes and hypertension and angina as an example,the clinical pathway optimization prediction model was established based on BP neural network,and the number of treatment days in the clinical pathway is the final indicator.By analyzing the error between the model output value and the expected value,it is verified that the Optimization method of BP neural network can reduce the number of treatment days of the clinical pathway.(4)The clinical pathway optimization model was established by using different numbers of hidden neurons.It was verified by experiments that the relative error of the training model decreased by 0.2% when the number of neurons is increased,and the relative error of the test model decreased by 0.35%.The experiments have verified that BP neural network is reasonable and feasible in clinical pathway optimization in this research project.Simultaneously,the treatment unit is used to divide the medical order project of clinical pathway,which further improves the reliability of clinical pathway optimization.The condition from the clinical pathway due to variation of complications has been effectively controlled,thereby effectively reducing the number of treatment days and medical expenses,and improving the medical quality,accelerating the further development of the clinical pathway.