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目的通过Apriori算法分析高额医疗费用患者相关指标之间的关系,试图找到影响医疗费用的因素,利用R扩展医学统计的工作思路。方法利用R软件中的arules包对2015年某院出院的高额治疗费用患者做关联规则分析,探索出院科室、住院天数与总费用,出院科室与性别,出院科室与药费,出院科室与有无手术的关联规则,并分析其原因。结果某些科室住院天数越多,费用越高;而某些科室的住院天数与费用没有太大关系;胸外、心内、神外、ICU、心外五个病区出院的高额费用患者通常为男性;呼吸、ICU、心外、胸外、神外五个病区出院的高额费用患者的药费一般大于2万元;心外、胸外、骨科等病区的高额医疗费用的出院患者通常要行手术治疗手段。结论 Apriori算法可以挖掘数据间内在的关系,为临床决策提供一定的理论支持,R语言可以快捷的完成医学统计工作。
Objective To analyze the relationship between the related indicators of patients with high medical costs through Apriori algorithm and try to find out the factors that affect the medical costs and use R to expand the work idea of medical statistics. Methods The arules package in R software was used to analyze the association rules of high cost patients who discharged in a hospital in 2015. The relationship between discharge department, length of hospital stay and total cost, discharge department and gender, discharge department and drug expenses, Association rules without surgery, and analyze the reasons. Results The longer the hospitalization days in some departments, the higher the cost. In some departments, the days of hospitalization were not significantly related to the expenses. The patients with high expenses discharged in the chest, heart, Usually male; respiratory, ICU, extracardiac, extrathoracic, divorced five wards discharged high cost patients with drugs generally more than 20,000 yuan; extra-cardiac, extra-chest, orthopedic and other wards of high medical costs Discharged patients usually require surgical treatment. Conclusion Apriori algorithm can mine the intrinsic relationship between data and provide some theoretical support for clinical decision making. R language can quickly complete the medical statistics.