What about Zhou? , ginger 1,
Abstract: purpose? To evaluate and analyze the hospital's medical efficiency with multiple indicators, and provide scientific basis for hospital management decision-making. Method? TOPSIS method was used to comprehensively evaluate 8 indexes reflecting hospital medical efficiency from 2005 to 2008. And the result? The efficiency of medical work in 2008 was the best. The medical efficiency in 2005 was the worst, which is consistent with the actual work of the hospital in recent years. Conclusion? Using TOPSIS method to comprehensively evaluate many indexes reflecting medical efficiency can objectively reflect the quality of hospital medical efficiency in different periods and find out the reasons, which has important practical value for improving the level of hospital performance management.
Keywords: TOPSIS method? Medical efficiency? Comprehensive evaluation? empirical analysis
China classification number R 197? Document identification number b commodity number
It is of great significance to comprehensively understand the medical efficiency of hospitals by using objective and accurate evaluation methods to improve the performance management level of hospitals. The actual situation of medical and health work is complex and influenced by many internal and external factors, so it is difficult for a single evaluation method to fully reflect the real situation of hospital management. Therefore, the comprehensive evaluation method can be selected for multi-dimensional evaluation. Comprehensive evaluation based on hospital raw data is an important symbol of hospital information management and an important means of modern hospital management. TOPSIS method? (technique? For what? Order? Preference? By who? Similarity? Where to? Ideal? Solution) is an important comprehensive evaluation method. This paper mainly discusses the application and empirical analysis of TOPSIS method in comprehensive evaluation of medical efficiency, which provides scientific basis for hospital management decision-making and helps to improve hospital medical efficiency.
That? Synthetic? Apply? And then what? Empirical? Analysis? By who? TOPSIS？ Method? Are you online? Evaluation? Yes? Medicine? Efficiency/week? Xiaojian? Jiang? Guan-Xu? Zhao? Koharu? //Chinese? Hospital? manage
Abstract and objective? Where to? Provide? Science? Foundation? For what? Making? Strategy? Decide? Are you online? Hospital? Management? By who? Synthetic? Evaluation? Yes? Are you sure? Hospital? Medicine? Efficiency? With what? Multiple indexes. ? Method? Apply? By who? TOPSIS？ Method? Are you online? Synthetic? Evaluation? Yes? Medicine? Efficiency? With what? 8? Index? Between 2005 and 2008. The result? Optimal? Medicine? Efficiency? Are you online? 2008,? On the contrary? That? 2005,? Keep? With what? That? The truth? Work? What's the situation Are you online? The nearest? How many years? . Conclusion? Apply? By who? TOPSIS？ Method? Are you online? Synthetic? Evaluation? Yes? Multiple indices? Is it okay? Objectively? Reflection? That? Quality? Level? And then what? Found it? Out? That? Why? Yes? Quality? Is it? Yes? Does it matter? Utility? Value? Where to? Raise? That? Hospital? Performance? Management.
Keys? wordsTOPSIS？ Method,? Medicine? Efficiency? Synthetic? Evaluation,? Empirical? analyse
The first author's Address graduate student? School? Yes? Anhui? Medicine? University? Hefei,? 230032,? China ?
Basic theory of 1TOPSIS method
1. 1? The basic principle and thought of TOPSIS method
TOPSIS method is a common method for multi-objective decision analysis of limited schemes in system engineering, and hospital management is a multi-factor and multi-objective system engineering. How to evaluate the actual medical efficiency scientifically, comprehensively and correctly is the key link to ensure and improve medical efficiency [1]. Its basic principle is to sort the evaluation objects by detecting the distance between them and the optimal solution and the worst solution. If the evaluation object is closest to the optimal solution and farthest from the worst solution, it is optimal. Otherwise, it is the worst. Among them, each index value of the optimal solution reaches the optimal value of each evaluation index, and each index value of the worst solution reaches the worst value of each evaluation index. Its basic idea is based on the normalized original data matrix. The positive ideal solution and negative ideal solution in the finite scheme form a space, and the scheme to be evaluated can be regarded as a point in the space, from which the distance Di+ between the point and the positive ideal solution and negative ideal solution can be obtained. And Di-, so as to obtain the relative closeness Ci value between the scheme to be evaluated and the positive ideal solution. Ci value to evaluate the advantages and disadvantages of the scheme [2].
1.2? Significance of positive ideal solution and negative ideal solution in TOPSIS method
The so-called positive ideal solution is an imaginary optimal solution (scheme), and all its attribute values reach the optimal value in each alternative scheme; Negative ideal solution is a hypothetical worst solution (scheme), and its attribute value reaches the worst value in all schemes. The rule of ranking schemes is to compare schemes with positive ideal solutions and negative ideal solutions. If one of the schemes is closest to the positive ideal solution but far from the negative ideal solution, it is the best scheme.
2.2. Basic methods of empirical analysis. TOPSIS method
2. 1 Collect the original data and establish the judgment matrix. The original data mainly comes from the information management department of a general hospital in Hefei in 2005. Annual health statistics report from 2008 to 2008, patient registration book inside and outside the hospital, medical records of inpatients and medical records database. With n evaluation objects and m evaluation indexes, n*m original data matrices can be obtained, as shown in table 1.
Table 1 original data matrix
Evaluation object? Indicator 1? Indicator 2? ... indicator m
Object 1? x 1 1x 12？ x 1m
Object 2? x2 1x22？ x2m
....
Object n? xn 1xn2？ xnm
2.2? Select evaluation indicators and determine their weights.
Select the hospital bed utilization rate (%)x 1? , bed turnover rate (%)x2, average hospitalization days of discharged patients (days) x3, annual outpatient visits per health technician (person-time/person-year) x4, annual discharge visits per health technician (person-time/person-year) x5, annual operation visits per health technician (person-time/person-year) x6, the proportion of surgical patients to discharged patients (%)x7, and every 100 outpatient patients. In this paper, analytic hierarchy process is used to determine the weight of these eight indicators. Analytic hierarchy process (analytic? Hierarchy? Process (AHP) is a systematic analysis method combining qualitative analysis with quantitative analysis, which was put forward by American scientist T.L.Saaty in 1970s. Analytic Hierarchy Process (AHP) uses the principle of system engineering to decompose research problems and establish low-level structures. Constructing a pairwise comparison judgment matrix; Calculating the relative weight of each element from the judgment matrix; And calculating the combined weight of each layer of elements; Take the lowest level as the evaluation index to measure the degree of goal realization; Calculate the comprehensive score index, evaluate the total evaluation index of the evaluation object, and determine the advantages and disadvantages of the evaluation object according to its size [3]. Compare and score the evaluation indicators, and the scoring criteria are shown in Table 2:
Table 2 Evaluation Criteria of Target Tree Diagram Hierarchy
Compare scores? Description of relative importance
1
three
five
seven
nine
(2、4、6、8)? be of equal importance
Slightly important
Basic importance
very important
Absolutely important
Two adjacent degrees
The median of? Both contribute the same to the goal.
According to experience, one evaluation is slightly better than the other.
According to experience, one evaluation is more favorable than the other.
According to experience, one evaluation is more favorable than the other, and it has been proved in practice.
The importance is obvious.
Used when compromise is needed.
According to the analytic hierarchy process (AHP), the index weights are calculated, the hierarchical performance indicators in each dimension are compared in pairs, and the judgment matrix is formed by the proportional scale method of 1-9. Calculate the maximum characteristic root of the judgment matrix and its corresponding characteristic vector, and then check the consistency. The formula is: CI=? (λmax-m)/(m- 1)？ , where λmax=λi/m,? λi=？ aijWj/Wi？ . Where m is the number of sub-targets of the inspected level; λmax is the largest characteristic root; λi is the characteristic root of the optimal matrix for paired comparison and judgment of sub-objectives in this layer. After calculating the normalized weight coefficient, it is necessary to check whether the calculated weight coefficient is logical. When the matrix ordering is judged.
2.3 According to the selected indicators, the original matrix is established and the trend analysis is carried out.
Accordingly, eight indexes, x 1 and x2, are selected to reflect the medical efficiency. X3, x4, x5, x6, x7 and x8. As shown in Table 3.
Table three? The original matrix reflecting the medical efficiency of a hospital from 2005 to 2008
index
Year? x 1？ x2？ x3x4x5？ x6x7？ x8
2005? 78.34? 24.8 1 1.62? 5 13.3? 22. 145.7626.04? 4.32
2006? 82.65? 26.3 10.94? 535.2? 24.096.5627.25? 4.52
2007? 83.2 1? 27. 19.05540.6? 23.966.4026.7 1? 4.86?
2008? 85.46? 28.77.86525. 1? 22.096.0627.42? 5.02?
In the comprehensive evaluation of medical efficiency by TOPSIS method, some indicators are high-quality indicators (that is, the higher the index value, the higher the efficiency, such as bed utilization rate and bed turnover times, etc. ), and some indicators are low-quality indicators (that is, the lower the index value, the higher the efficiency, such as the average length of stay of discharged patients). At this time, we need to treat indicators with consistent trends (that is, we will convert them into high-quality indicators or low-quality indicators). In this paper, the reciprocal method is used to transform all indicators into high-quality indicators. The formula is: x, nm= 1/xnm? According to this formula, the low quality index is converted into high quality index, and the common trend matrix table is obtained, as shown in Table 4.
Table four? Chemotaxis matrix table
index
Year? x 1？ x2？ x3x4x5x6x7x8
2005? 78.3424.88.65 13.3? 22. 145.7626.04? 4.32
2006? 82.6526.39. 1535.2? 24.096.5627.25? 4.52
2007? 83.2 127. 1 1 1. 1? 540.6? 23.966.4026.7 1? 4.86?
2008? 85.4628.7 12.7? 525. 1? 22.096.0627.42? 5.02?
2.4 Normalize the trend matrix and establish a normalized matrix Z. ..
When the original data is a high-quality index, its normalization formula is: Znm=? xnm？ /? (? x2nm) 1/2？ ; When the original data is low quality index, its normalization formula is: Znm=? x，nm？ /? [? (x，nm)2] 1/2？ ; After normalization, the normalized matrix z is obtained. As shown in Table 5.
Table 5? Standardized matrix table
index
Year? x 1？ x2？ x3？ x4x5x6x7？ x8
20050.002880.00870.0 195? 0.000460.0 10380.03740.009020.049 1
20060.003040.00920.0206? 0.00 1870.0 1 1300.04260.009440.05 14
20070.003060.00950.0252? 0.000480.0 1 1240.04 160.009260.0553
20080.003 140.0 1000.0288? 0.000470.0 10360.03940.009500.057 1
2.5 according to the normalized matrix z, determine the positive ideal solution and negative ideal solution and their distances Di+ and Di- from the index values of each evaluation object.
Positive ideal solution Z+= (? zi 1+，zi2+...zim+？ ); Negative ideal solution Z-= (? Zi 1-, zi2- ... Zim-? ), where i= 1, 2? …? n； ? j= 1，2？ …? m？ . Zij+？ And then what? Zij-？ Respectively represent the maximum and minimum values of the evaluation object in the j-th index. Positive ideal solution Z+(0.003 14, 0.0 100, 0.0288, 0.00 187, 0.0130, 0.0426, 0.00955) Negative ideal solution Z-(0.00288, 0.0087, 0.055) The distances Di+ and Di- between the index value of each evaluation object and the positive ideal solution and negative ideal solution can be calculated by the following formulas respectively: Di+=? {? [wj(Zij-Zj+)]2 } 1/2； Di-=？ {? [wj(Zij-Zj-)]2} 1/2, where wj represents the weight coefficient of indicator J. If the weights of wj are equal, then wj= 1? . According to Di+? And Di-, and x 1? 、x2？ 、x3、x4？ 、x5？ , x6, weighted Euclidean distance Di+(0.0043 13, 0.003225, 0.00 1764, 0.00153) and di-(0.00153).
2.6 based on the above Di+ and Di- values, calculate the relative closeness Ci value, and sort the evaluation objects according to the Ci value. Ci value is the relative closeness of each evaluation index value to the true ideal solution and the negative ideal solution, and its calculation formula is: Ci=? Di-/(？ Di++Di-), its value range is [0? 1], the closer it is to 1, the closer it is to the positive ideal solution; The closer the value is to 0, the closer the evaluation object is to the negative ideal solution. According to the above analysis, the medical efficiency of this hospital from 2005 to 2008 was ranked, as shown in Table 6.
Table 6? The closeness and ranking of positive ideal solutions in 2005-2008
Year? Di+Di-？ Ci sequencing
20050.0043 130.00 12650.2268? four
20060.0032550.00 192 10.3733? three
20070.00 17640.0026660.60 18? 2?
20080.00 1 1530.00400.7762? 1
The ranking results in Table 6 show that the hospital's medical efficiency was the highest in 2008, and since 2005, the hospital's medical efficiency has been increasing year by year, as shown in Figure 1, which can intuitively show the change of Ci value.
Figure1Ci value change in 2005-2008
3. Result analysis
3. 1? According to the basic principle of TPOSIS method, the greater the Ci value, the closer the evaluation object is to the ideal value, and the higher the actual medical efficiency. It can be seen from the comprehensive evaluation results of medical efficiency in 4 years. 2008 is the year with the highest medical efficiency in four years. And 2005 was the lowest year. Results It accords with the reality of hospital development. The hospital began to implement full cost accounting at the end of 2004, and the hospital has done a lot of work to implement the concept of full cost accounting. Strengthen hospital cost control and improve medical efficiency. Expanding the scope of services has achieved great results in attracting patients to seek medical treatment. The work of the hospital has made great progress. Then the year of hospital management was launched in 2005. In the process of striving to meet the new standards, the hospital's self-construction and comprehensive service capacity have been further improved and improved. Work efficiency has leapt to a new level [4]. At the same time, the hospital implemented reform and innovation, improved the competitive incentive mechanism, effectively used various quantitative and efficiency quality indicators, and established a hospital comprehensive benefit evaluation system, which fully mobilized the enthusiasm and initiative of medical staff [5].
3.2? From the change range of broken line slope in Figure 1, it can be seen intuitively that the change range in 2005-2006 is not large, indicating that the measures taken by the hospital to improve medical efficiency are showing results; The biggest change was in 2006-2007, indicating that the effect of various measures was gradually enhanced and the market demand for medical services was strong; In 2007-2008, the range tends to be flat again, which shows that the medical services provided by hospitals and the medical service needs of patients are gradually balanced, which fully conforms to the health status of local people and the development law of medical service market.
4 discussion
Using TOPSIS method to evaluate hospital medical efficiency, this method has no strict restrictions on data distribution, sample size and selection of evaluation indexes, and has the characteristics of flexible application, simple operation and intuitive results, which can accurately reflect the differences of evaluation objects and has great application value in multi-index comprehensive evaluation of hospital work efficiency [6-7]? . TOPSIS method was used to comprehensively analyze and evaluate eight indexes reflecting medical efficiency in our hospital in the past four years. Thus, the relative closeness and ranking of ideal solutions in each year can be obtained. We can not only clearly see the advantages and disadvantages of medical efficiency in each year, but also find out the reasons for the advantages and disadvantages. So as to provide a reliable basis for medical and health work decision-making [8]. However, this method also has its own limitations and is greatly influenced by outliers. In order to meet the requirement of small dispersion of original data and reduce the influence of abnormal values of some evaluation indexes on the analysis results, TOPSIS method and RSR method can be combined to further improve the scientific evaluation results.
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