基于机器学习的中老年冠心病共病病人医疗费用影响因素研究OA

Objective:To analyze the influencing factors of medical expenses of middle-aged and elderly patients with coronary heart disease complicated with comorbidities based on machine learning model.Methods:A total of 3 002 patients with coronary heart disease complicated with complications hospitalized in the 27 public hospitals in a provincial capital city in central China was selected as subjects from January 2022 to January 2023.The patient data were collected.The influencing factors of medical expenses of middle-aged and elderly patients with coronary heart disease complicated with comorbidities were analyzed based on four machine learning models,namely ridge regression,Lasso regression,random forest,and decision tree.Results:Compared with other models,the random forest model had better fitting effect.The material cost(27.72%)and western medicine cost(19.43%)accounted for relatively high proportion of the patient's medical expenses,while the nursing cost(4.02%)and consultation cost(1.15%)accounted for relatively low proportion.The hospitalization days,the level of medical institution(tertiary hospital),gender(female),age(>50～70 years old),discharge department(cardiology),admission department(cardiology),and common complication(hypertension)were the main influencing factors of medical expenses of middle-aged and elderly patients with coronary heart disease complicated with comorbidities.Conclusions:Managers should formulate effective measures according to the influencing factors of medical expenses in middle-aged and elderly patients with coronary heart disease with complication to eliminate the waste of medical resources and reduce the burden of middle-aged and elderly patients with coronary heart disease complicated with comorbidities.