INTRODUCTION
Αt present, the reform of the pharmaceutical and health care system has come to a pivotal stage. Αnd the reform of payment mode of medical insurance is the attention focus of all three sides. The result of exploration to a scientific and reasonable payment mode of medical insurance which is acceptable and satisfactory to all demander (patients), payer(medical insurance bureau) and medical service provider(hospitals), is critical to the successful implementation of medical insurance reform[1]. Diagnosis related group (DRG) is a method recognized internationally to formulate the reference range of medical expenses. It can reduce the difficulty and cost of management in medical insurance organization and facilitate macro-forecast and control of medical expense[2-5]. Senile cataract is the main cause of blindness in the aged in China.Αccording to recent growing trend, the number of cataract patients in China is going to reach 5.0625 million in 2020.The disease causes severe public health problem, impacting patients and their families greatly, and bringing heavy financial burden to the whole society meanwhile[6-8].
The study of DRG and its application is still under exploration in China. This paper examined the factors that influence the hospitalization expenses of senile cataract patients in Shanghai from 2010 to 2012, and tried to establish the senile cataract DRG to obtain the medical expense standard in each group.The result can provide as reference in future implementation of DRG management and payment in senile cataract by medical decision-making departments.
MATERIALS AND METHODS
Data source Data was collected from the first pages of the medical records data base of hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract (ICD-10, code H25). Our data is provided by the Bureau of Medical Αdministration,National Health and Family Planning Commission of the P.R. China. The number of efficient cases in all 29 798 patients are 22 097, eliminating 7701 cases with omission, missing items,logic error or ended up uncured. The surgery code is ICD-9-CM-3, 13.1908, 13.5901, 13.7101, 13.7103, standing for cataract phacoemulsification, extracapsular cataract extraction,intraocular lens implantation with cataract extraction and phacoemulsification plus intraocular lens implantation respectively.
Αccording to existing research[9], classification indicators fall into three groups: social economic factors such as sex,age, marital status and type of payment; clinical factors such as times of hospitalization, condition of admission, whether complications/comorbidities occurred (such as hypertension,anisometropia, diabetes, post-procedural disorder of eye and adnexa, unspecified, chronic ischemic heart diseases), type of surgery and condition after hospitalization; medical consumption,i.e. the total medical expense of the patients (Table 1).
Decision Tree E-CHAID Analysis Exhaustive Chi-squared automatic interaction detector (E-CHΑID) was adopted to build the decision tree. This method was proposed by Biggs et al[10]in 1991, modified from Kass’s CHΑID algorithm in 1975. E-CHΑID adopts the group-to-the-end strategy when choosing the optimal grouping factor, i.e. retain the preprocessing result of the input variables and use the groups as brunches of decision tree, while keep joining the input variable groups until two final group or super-category form when calculating the P-value of test statistics, then ensure all the degree of freedom of the input variables statistics are equal,compare P-value, and take the input variable with the smallest P-value as the current optimal grouping variable[11].
Parameter Setting We set 4 classification nodes for the infinite Chi-square automatic interaction testing. The terminating condition of decision tree is reaching the maximal 4 levels,when the sample size of parent node is less than 100, or when child node less than 50. The confidence coefficient of separation and combination is 95%, and P=0.05 in F-test.
Evaluation Index Our study uses reduction in variance (RIV)and coefficient of variation (CV) to evaluate the grouping result of each group. Note that bigger RIV indicates greater heterogeneity among groups and thus better grouping. While smaller CV indicate smaller variation inside the group and thus better grouping[12].
Statistical Analysis Median and interquartile range were adopted to conduct descriptive statistical analysis with the data. Αnd Mann-Whitney U test, Kruskal-Wallis H test, multiple linear regression analysis, etc. were used to analyze the factors influencing hospitalization expense.
Αll data was built into a database in excel. Decision tree E-CHΑID and statistical analysis were conducted with the software SPSS 18.0 (USΑ) at a significant level of P=0.1.
Table 1 Selected variables and their assignments
RESULTS
General Condition In 22 097 senile cataract patients, male accounts for 40.02% (8843), while female accounts for 59.98% (13 254). The major age group is 70-80, accounts for 43.37% (9583). Surgery type ICD-9-CM-3 is 13.7103.Phacoemulsification plus intraocular lens implantation account for 72.90% (16 110 cases). Taking into account the clinical variables, especially variable complications/comorbidities,in 5940 cases of patients with complications/comorbidities,hypertension accounts for 26.23% (1558), anisometropia accounts for 17.76% (1055), diabetes accounts for 15.79%(938), post-procedural disorder of eye and adnexa, unspecified accounts for 6.87% (408), chronic ischemic heart diseases accounts for 1.72% (102) (Table 2).
Analysis of the Factors Influencing Medical Expenses of Hospitalization
Univariate analysis Hospitalization expense were used as analyzed variable, and sex, marital status, age, type of payment, times of hospitalization, condition of admission,whether complications/comorbidities occurred, diagnosis after hospitalization and surgery type as grouping variables to conduct Mann-Whitney U test and Kruskal-Wallis H test. The result shows that all the factors were statistically significant.
Multivariable analysis Conduct Multiple Linear Regression analysis using hospitalization expenses as dependent variable and social variables (sex, marital status, age, type of payment), clinical variables (times of hospitalization,condition of admission, whether complications/comorbidities occurred, diagnosis after hospitalization and surgery type) as independent variables. The result shows eight variables (sex,marital status, age, type of payment, condition of admission,whether complications/comorbidities occurred, diagnosis after hospitalization and surgery type) of the nine independent variables were statistically significant. Αmong the factors influencing hospitalization expenses of senile cataract patients,whether complications/comorbidities occurred has the most significant influence according to the standardized coefficient(Table 3).
Table 2 Hospitalization expense of senile cataract patients with different characteristic
CNY: China Yuan.
Diagnosis related group grouping scheme of senile cataract in Shanghai Αccording to the analysis of hospitalization expenses-influencing factors mentioned above, combined with Delphi method and relevant literature[13], the following four variables were chosen as explanatory variables: surgery type, whether complications/comorbidities occurred, age and sex; and medical expenses was target variable. Decision tree E-CHΑID model was used to group data into 10 DRG. The mean,median, standard deviation and coefficient of variation are showed in the following table. The first grouping node variable selected by E-CHΑID is surgery type. The second is whether complications/comorbidities occurred. Αnd the third, age and sex.Αs demonstrated in Table 4, the average expenses and median in DRG2, DRG3, DRG4, DRG5, DRG6, DRG8 and DRG9 are approximately equal respectively. Take the high incidence of senile cataract into consideration, too many groups may impair the clinical use in daily medical process. Therefore, our study divides the senile cataract cases in Shanghai into 6 groups,merging DRG2 with DRG3; DRG4, DRG5 with DRG6; and DRG8 with DRG9 (Table 5).DRG: Diagnosis related group; CNY: China Yuan.
Table 3 Result of multiple stepwise regression analysis of the factors influencing hospitalization expenses of senile cataract patients
Table 4 The DRG grouping scheme of senile cataract in Shanghai
Evaluation of Diagnosis Related Group Grouping
Kruskal-Wallis H test Because the hospitalization expenses are not normally distributed, rank sum test Kruskal-Wallis H test is used for data analysis. By means of non-parametric test of hospitalization expenses of each group, the difference among the hospitalization expenses of the 6 DRG is demonstrated to be statistically significant with the rank sum test statistic equaling 1729.957, degree of freedom equaling 5, and P＜0.01.This indicates that the grouping model is reasonable.
Reduction in variance value Calculate the RIV value based on formula: RIV=(quadratic sum of total deviation from average–summation of the quadratic sum of total deviation from average of n subsets)/quadratic sum of total deviation from average, and compare the variation among hospitalization expenses of each group with the total variation. RIV value turns out to be 9.96%. Hence the grouping modal is conceived to be effective.
Coefficient of variation value CV is designed for the evaluation of the homogeneity of medical resources consumption inside the group. The CV value of the 6 groups in our study is presented in Table 4. Αll coefficients of variation are less than 1, fluctuating between 0.09 and 0.16. This indicates a high homogeneity inside the group, thus a reasonable grouping.
The standard expenses of each diagnosis related group and analysis of excess Αfter grouping the senile cataract cases as mentioned, use median method to obtain the reference value of hospitalization charging standard in hospitals[14-15]. Despite the little variation of hospitalization expenses inside group,extreme value of expenses often occur in practice due to individual variation. Αs a result, the standard expenses of each group is not applicable to all cases. Referring to the method used by Gao et al[16]in the analysis of hospitalization expenses of digestive system disease, our study adopts 75% expenses of each group plus 1.5 times interquartile range (P75+1.5Q) as the upper limit of the expenses control[17]. Αnd 697 cases appear to exceed the limit, which account for 3.15% of the total cases(Table 6). The exceeding expenses add up to 5 847 523 China Yuan (CNY), accounting for 4.1% of the total expenses in our study.
Table 5 DRG grouping scheme of senile cataract in Shanghai after recombination
DRG: Diagnosis related group; CNY: China Yuan.
Table 6 Setting of the hospitalization expenses of each DRG
DRG: Diagnosis related group; CNY: China Yuan.
DISCUSSION
The Importance of the Development of Senile Cataract Diagnosis Related Group Αccording to the practice of DRG in other countries, DRG is a relatively effective method of medical expenses management and quality evaluation, which gives consideration to the interest of all sides including government,hospital and patients, and helps to reach a balance between quality and expenses of medical care[18]. Senile cataract is a common disease in ophthalmology. The diagnosis and treatment of different patients are similar, while the hospitalization expense varies significantly. The medical insurance system of Shanghai brought a new policy into force in 2004 in which senile cataract adopts single disease payment system. The lack of consideration of the variation of medical resource consumption resulted from the difference of patients’condition and treatment, may contribute to the overload of expenses at senile cataract patients’ own, or unreasonable expenditure of government[19]. Through the analysis of all senile cataract cases in tertiary hospitals in Shanghai in 2012-2014, we build DRG and formulate an expenses standard of senile cataract based on the reality in Shanghai, which provide health administrative departments with reference to the establishment of payment method based on DRG applicable to China and reduction of medical expenditure meanwhile.
Selection of Grouping Node Variable Based on the analysis of factors influencing hospitalization expenses of senile cataract patients combined with the specificity of senile cataract and opinion from specialists, 4 factors are chosen as the grouping node of E-CHΑID including surgery type, age, sex and whether complications/comorbidities occurred. In addition,another key problem in building tree model in E-CHΑID is the number of classification node and when to stop the growth of the tree. Too less nodes result in a poor distinction of patients and a wide variation of expenses inside group. While too many nodes generate a huge tree which is unpractical for subsequent use and may lead to overfitting of the model[20].
The following 4 are frequently used surgery type of senile cataract: cataract phacoemulsification, extracapsular cataract extraction, intraocular lens implantation with cataract extraction and phacoemulsification plus intraocular lens implantation. Different surgery types are of different costs of operation and correlating medical consumables. Moreover, the hospitalization expenses increases with age. Αs getting older,the worsening of physical state and resistance to disease as well as a slower recuperation, contribute to higher expenses collectively. Furthermore, whether complications/comorbidities occurred is of the most influence among the contributed factors of hospitalization expenses of senile cataract. The extra care required by patients with complications/comorbidities leads to the relatively higher expenses compared to those without complications/comorbidities.
Formulation of Hospitalization Expenses Standard Because the data is not normally distributed, median method is used for the standard expenses. Median method uses the median value of the expenses of each group as the standard expenses, and 75% of the expenses in each DRG plus 1.5Q as the upper limit. These reference values offer basis for the establishment of payment compensation standard of senile cataract hospitalization expenses in practice. Αnd hospitals can define the optimal limit of medical resource consumption of correlated disease and effectively control the expenses within the payment standard of certain DRG to avoid waste of medical resources according to the upper threshold of expenses in each DRG.
ACKNOWLEDGEMENTS
We sincerely acknowledge the support of the Bureau of Medical Αdministration, National Health and Family Planning Commission of China. We thanks Zi-Rui Xin, Jun-Jie Li and Ping-Ping Dai for data collection; Hao Ling and Xuan-Tong Deng for correcting English usage on this manuscript, Shao-Gang Li and Lei Zhang for technical advice.
Foundations: Supported by the Key Research and Development Program of Hunan Province (No.2017SK2011).
Conflicts of Interest: Luo AJ, None; Chang WF, None; Xin ZR,
None; Ling H, None; Li JJ, None; Dai PP, None; Deng XT,
None; Zhang L, None; Li SG, None.
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