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Analysis On The Direct Economic Burden Of Patients With Chronic Obstructive Pulmonary Disease Using Association Rules Mining

Posted on:2018-06-21Degree:MasterType:Thesis
Country:ChinaCandidate:Y T GuoFull Text:PDF
GTID:2334330536486605Subject:Epidemiology and Health Statistics
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Objective: To understand the basic information of the insured patients with chronic obstructive pulmonary disease(COPD)and their constitutions of the hospitalization expense in Tianjin from 2009 to 2013,to explicate the internal structures and the distribution characteristics of the hospitalization expense,in order to provide the foundation to study the internal factors influencing the hospitalization expense and their tendency of development.Through the analysis of the data information,exploring the direct and indirect external factors influencing the hospitalization expense in patients with COPD in Tianjin,and mining in-depth the patterns of the influential factors for the excessive hospitalization expense in patients with COPD.Consequently,offering the theoretical support and practical basis which aimed to control the excessive growth of the medical expense specifically,thus reducing the economic burden of inpatients with COPD and providing the feasible suggestions to improve the health care reform further.Methods: A retrospective analysis was performed on the total 9 199 patients which were hospitalized from January 2009 to December 2013 in the Tianjin Urban Employees' Basic Medical Insurance Register System database.Sampling 50% cases of all randomly,collecting the cases whose primary diagnosis discharged were COPD(ICD-10 codes were J44,J44.0,J44.1,J44.8 and J44.9),and excluding the days of hospitalization less than one day or hospitalization expense exceeded(7)(8)SX ±3.Using the Microsoft Office Excel 2007 software,the method of new grey relational analysis was used to analyze the degree of correlation among each hospitalization expense.The value of structure variation(VSV),degree of structure variation(DSV)and contribution rate of DSV were used to evaluate the change of each hospitalization expense and their effect on the total expense in 5 years.Using the SAS 9.2 statistical analysis software,the multiple linear stepwise regression analysis was utilized to fit the path analysis model of the external factors influencing the hospitalization expense.After the model effect was decomposed,the direct effect of the hospitalization expense and the indirect effect of the hospitalization expense through the days of hospitalization were calculated.Using the Amos Graphics 17.0 software,the path diagram of the external factors influencing the hospitalization expense was mapped after sorting the total effect of each influential factor.Using the SPSS Clementine 12.0 statistical software,the association rules data mining technology based on the Apriori algorithm was used to excavate the condition attributes which had strong association rules with the excessive hospitalization expense,then to reveal the implicit association rules.Results: Among the 9 199 patients included in the study,there were 5 573 males and 3 626 females,aged from 24 to 105 years old with the median 75.00(13.00)years old,449 cases on the job,8 622 retired and 128 old workers,5 127 cases accompanied by the acute exacerbation and 4 072 cases not,190 cases treated in the primary hospitals,3 532 cases in the secondary hospitals and 5 477 cases in the tertiary hospitals,570 cases performed operations and 8 629 cases not,the days of hospitalization ranged from 1 to 89 days with the median 11.00(6.00)days.Among the hospitalization expense in patients with COPD from 2009 to 2013,the medicine expense was most closely linked to the hospitalization expense(1.0000),followed by the examination expense(0.7253),treatment expense(0.6853)and medical materials expense(0.6451).The medicine expense contributed mostly to the DSV(44.56%),and there was a decrease on its proportion of the hospitalization expense,then followed by the examination expense(39.40%),medical materials expense(10.45%)and treatment expense(4.56%),and there were increases on their proportions of the hospitalization expense on the first two and a decrease on the last one oppositely.The accumulated contribution rates of these four items were up to 98.97%.The days of hospitalization were the most important factor influencing the hospitalization expense directly(0.650).Accompanied by the acute exacerbation,tertiary hospitals and performing operations could affect the hospitalization expense directly and indirectly through the days of hospitalization,and the sort of the total effect were the tertiary hospitals(0.295),performing operations(0.219)and accompanied by the acute exacerbation(0.004).The effect of other variables on the hospitalization expense was only a direct effect,and the sort of the total effect were the primary hospitals(-0.153),age(0.067),retired(0.022)and gender(0.019).Finally,the sort of the total effect of factors influencing the hospitalization expense were the days of hospitalization(0.650),tertiary hospitals(0.295),performing operations(0.219),primary hospitals(-0.153),age(0.067),retired(0.022),gender(0.019)and accompanied by the acute exacerbation(0.004).There were 14 significant association rules in the association rules model.For the patients with the days of hospitalization more than 29 days,the probability of developing the excessive hospitalization expense accompanied by the acute exacerbation and retired was 11.56 times than before,accompanied by the acute exacerbation was 11.50 times than before,accompanied by the age ranged from 70 to 79 years old was 11.20 times than before,accompanied by the age ranged from 70 to 79 years old and retired was 11.14 times than before,accompanied by the retired was 11.12 times than before,accompanied by treated in the tertiary hospitals was 11.00 times than before,accompanied by treated in the tertiary hospitals and retired was 10.97 times than before.For the patients with the days of hospitalization ranged from 22 to 28 days,the probability of developing the excessive hospitalization expense accompanied by the age ranged from 70 to 79,acute exacerbation and retired was 8.98 times than before,accompanied by the acute exacerbation and retired was 8.88 times than before,accompanied by the age more than 80 years old and retired was 8.81 times than before,accompanied by the acute exacerbation was 8.80 times than before,accompanied by the age more than 80 years old was 8.78 times than before,accompanied by treated in the tertiary hospitals,the acute exacerbation and retired was 8.53 times than before,accompanied by treated in the secondary hospitals was 8.22 times than before.Conclusions: The control of the medicine expense could be expected as a key breakthrough point to reduce the burden of the hospitalization expense in patients with COPD,then by standardizing the examinations,strengthening the regulations of the medical materials and attaching a great importance to the labor values of the medical staff,we could optimize the internal structures of the hospitalization expense.The path analysis model showed that the days of hospitalization were the most important direct factor influencing the hospitalization expense.Therefore,we should focus on the controlling and shortening of the average days of hospitalization,and take a comprehensive strategy to control the hospitalization expense in patients with COPD.And these strong association rules could be used to identify the warning information about the excessive hospitalization expense,reminding that the hospitals should shorten the average days of hospitalization and do a good job of the hierarchical diagnosis and treatments.Consequently,improving the strength on the supervision of the controllable factors,we could manage to reduce the excessive growth of the hospitalization expense effectively,thereby reducing the economic burden of the insured patients with COPD.
Keywords/Search Tags:Chronic obstructive pulmonary disease, Hospitalization expense, Grey relational analysis, Degree of Structure Variation, Path analysis, Data mining, Association rules, Apriori Algorithm
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