Evaluating the Quality of Medical and Health Services by the Method

of Topsis and Linear Interpolation in China

Jiping Zhang

1,* a

, Yuqing Mi

and Haixia Zhang

Department of Hospital Infection-Control, Qingdao Jiaozhou Central Hospital, Qingdao, China

School of Public Health, Weifang Medical University, Weifang, China

Department of Scientific Research and Education, Qingdao Jiaozhou Central Hospital, Qingdao, China

Keywords: Medical Service, TOPSIS Method, Linear Interpolation Method.

Abstract: This study aims to use of TOPSIS method and linear interpolation method to evaluate the work of medical

services in towns and townships, to understand our country in various provinces, cities and towns and

townships, 2016 medical and health services status quo, analysis of regional differences. This study selected

reflected in towns and townships to medical service quality of six indicators, using TOPSIS method and

linear interpolation method in various provinces and cities in the country towns and townships is used to

evaluate medical service quality. Using the SPSS 17.0 software to the ranking results of two methods to do

Spearman correlation analysis and Kruskal Wallis H test.The Spearman correlation analysis and TOPSIS

method and the linear interpolation method, the correlation of evaluation results is higher (r = 0.915, P =

0.000).Two kinds of comprehensive evaluation results sorting, sichuan, henan, guangxi is located in the top

three, shanxi, Inner Mongolia, jilin, after three.Thus this research conclusions: regional differences in towns

and townships throughout the country medical service quality, two kinds of evaluation results is highly

correlation.

1 INTRODUCTION

In towns and townships as an important part of the

basic health service system construction, burdened

with a large number of medical and health services,

epidemic prevention, such as maternity care work, in

the protection of peasants health plays an important

role of (Gao 2018). Although grassroots health

workers are accelerating in China, has a certain

regional differences. In towns and townships of our

country is used to evaluate medical service quality is

of great significance to the evaluation result directly

reflect the grassroots medical service level. At

present, the TOPSIS method is limited in systems

engineering solution of multi-objective decision

analysis is a kind of commonly used method, often

used for quality evaluation work of medical

institutions, advantage is that can make full use of

original data information, sorting results intuitive

and reliable (Liu, Chai, Xu, Cai 2018); Linear

https://orcid.org/0000-0002-9712-7168

https://orcid.org/0000-0002-2923-5618

https://orcid.org/0000-0003-2903-2498

interpolation method, according to the average index

of minor sort method is simple, convenient

application, the differences due to different

evaluation method and evaluation results, in order to

ensure objectivity of evaluation results, this study

adopts the TOPSIS method, linear interpolation

method is used to evaluate the national basic

medical service quality, in order to understand our

country in various provinces, cities and towns and

townships, 2016 service present situation and

analyzes the regional differences.

2 DATA AND METHODS

2.1 Source

This research uses the data of national health and

family planning commission, "2017 China statistical

yearbook of health and family planning (National

health and family planning commission 2017).

Zhang, J., Mi, Y. and Zhang, H.

Evaluating the Quality of Medical and Health Services by the Method of Topsis and Linear Interpolation in China.

DOI: 10.5220/0012070500003624

In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis (PMBDA 2022), pages 91-96

ISBN: 978-989-758-658-3

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

2.2 Index Selection

Refer to the China statistical yearbook of health and

family planning of towns and townships health

service category, select six representative indicators

of 29 provinces in China in 2016 (the data does not

include Beijing, Shanghai) is used to evaluate the

towns and townships of medical service quality.

Selected indicators are: X1 - sickbed utilization rate

(%), X2 - average (day) of such confinement, X3 -

physicians daily for visits, X4 - physicians daily for

hospital bed, X5 - visits (ten thousand people), X6 -

admissions (ten thousand people).Among them, the

X2 - low average such confinement for optimal

index, the rest for the yields and indicators.

2.3 Comprehensive Evaluation Method

2.3.1 TOPSIS Method

TOPSIS method is based on the normalized after the

original data matrix, calculated to evaluate solutions

and the optimal scheme and the worst, according to

the size of the relative distance evaluation using a

method (Wang, Song, An 2015). list the decision

matrix, namely the original data set: 29 provinces,

six indicators, form a comprehensive evaluation of

the original data table, as shown in table 1.index

with chemokines normalization processing: 100 / (x)

by inverse method yields and index, low optimal

index can be converted to realize with chemokines,

further normalization processing eliminate the

influence of discrete tendency and normalized

matrix values(1):to determine the optimal worst

plan: Z+ = (0.31, 0.28, 0.38, 0.42, 0.52, 0.44), Z- =

(0.05, 0.01, 0.05, 0.01, 0.01, 0.01); D+i, D-i and

proximity Ci: each evaluation objects and the

distance Z+, Z- toD+i, D-i, proximity to Ci, Ci is

close to 1, medical services, the better the

results(2).sorting: according to the Ci value from big

to small order, get medical service level of provinces

and cities, sort the results, as shown in table 2.



(1)



−=

jiji

ZZD

)(



−−

−=

jiji

ZZD

)(

,,...,1 ni =

+−

−

,...,1,10 =≤≤

(2)

2.3.2 Linear Interpolation Method

Linear interpolation method is essentially actual

value evaluation of each index in the index is the

ratio of the location in the whole distance, finally

according to the evaluated object average minor sort,

(0,1), the bigger value shows that comprehensive

evaluation result more optimal (Li, Wang, Xia,

Zhang, Bai 2015).

Rank: the minimum and maximum parameter

values will be integers, the rest are basically as a

integer. The yields and indicators:(3). For low

optimal indicators: (4).

Calculated the comprehensive rank (5).

The sorting: by RSR values from big to small

order, comprehensive evaluation results by linear

interpolation method, shown in table 4.

minmax

min

)1(1

−

−+=

(3)

minmax

max

1n1

−

−+= ）（

(4)



RSR

(5)

2.4 Statistical Analysis Methods

SPSS 17.0 software was used to deal with the data

analysis.ɑ = 0.01.

3 RESULTS

3.1 Primary Care Services

Regional differences in towns and townships health

service indicators. Hubei province in towns and

townships sickbed utilization rate is as high as

76.70%, followed by chongqing, xinjiang, Tibet

autonomous region sickbed utilization rate, the

lowest is 28.30%; The highest average such

confinement was in towns and townships, zhejiang

province, is 9.1 days, followed by Shanxi Province

and jiangsu province. Physician burden of daily visits

are highest in Shanghai, followed by the zhejiang

province, tianjin, the lowest is Tibet; Physicians daily

for visits are highest in zhejiang province, the second

is in yunnan province and hainan province.

Physicians, xinjiang province, the highest average

daily take such confinement was followed by

chongqing municipality, sichuan province. In towns

and townships, 2016 visits the most were in henan

province, was hospitalized people most is sichuan

province, as shown in the table 1.

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Table 1: Provinces of original index in towns and townships medical services.

Area X1X2X3X4 X5 X6

Tian

in 44.00 7.50 11.70 0.80 645.94 7.22

Hebei 58.50 7.20 7.40 1.40 4777.19 168.67

Shanxi 35.10 8.50 6.70 1.10 1603.68 42.65

Inner Mongolia 42.20 6.50 5.50 0.90 1217.01 36.28

Liaoning 44.30 7.60 8.00 1.50 1718.16 55.25

Jilin 28.80 7.50 4.70 0.60 967.24 1.76

Heilon

ian

56.60 6.30 4.80 1.45 983.28 66.56

Jian

su 63.60 7.60 10.90 1.10 8288.55 163.38

Zhejiang 49.70 9.10 18.00 0.40 9351.85 30.69

Anhui 60.60 6.60 8.80 1.40 4576.62 157.95

ian 49.50 6.10 11.00 1.40 2702.97 82.14

Jian

xi 68.70 5.40 8.90 2.20 3228.70 201.88

Shandon

60.70 7.30 7.50 1.50 7331.87 273.53

Henan 62.20 7.20 12.50 1.70 11218.47 287.33

Hubei 76.70 7.00 8.10 1.80 5755.85 258.67

Hunan 70.50 6.00 4.60 1.80 4046.01 373.03

Guan

don

55.20 5.30 8.70 1.00 6690.25 194.48

Guan

xi 63.30 5.20 12.00 2.20 5132.05 252.32

Hainan 33.30 6.50 16.50 0.60 1149.72 7.72

Chongqing 74.10 6.70 7.60 2.80 2002.69 153.74

Sichuan 70.70 6.30 11.50 2.50 9372.06 443.28

Guizhou 44.90 4.90 8.70 1.40 2661.97 119.63

Yunnan 53.40 5.80 17.80 2.10 5087.92 140.96

Xizan

28.30 5.00 13.40 0.60 413.63 3.70

Shaanxi 46.60 7.30 9.00 1.60 2202.58 75.43

Gansu 60.00 6.40 8.90 1.50 2006.48 67.76

Qinghai 55.10 5.50 6.10 1.20 258.76 11.49

Nin

xia 49.10 6.60 13.70 0.60 670.59 4.88

Xin

ian

74.00 6.10 12.90 2.80 2170.96 101.67

3.2 TOPSIS Method to Comprehensive

Evaluation Results

We Used TOPSIS comprehensive evaluation method

of 29 provinces, cities and towns and townships of

six measures of service. The results are shown in

table 2, the medical service level in the top three,

guangxi, henan, sichuan, after three, respectively,

shanxi, jilin, Inner Mongolia.3.3. Status quo of

incentive satisfaction of urban community nurses in

Shandong Province. evaluation results.

Table 2: Based on TOPSIS method of job evaluation in towns and townships of medical services.

Area D+ D- Ci The sorting

Sichuan 0.151 0.666 0.8151 1

Henan 0.249 0.573 0.6970 2

Guan

xi 0.340 0.435 0.5618 3

Shandon

0.350 0.436 0.5549 4

Hunan 0.394 0.477 0.5480 5

Hubei 0.365 0.421 0.5357 6

Jiangsu 0.408 0.399 0.4940 7

Yunnan 0.418 0.403 0.4908 8

Guan

don

0.422 0.359 0.4598 9

Jian

xi 0.440 0.365 0.4530 10

Zhejiang 0.546 0.431 0.4410 11

Xinjiang 0.516 0.378 0.4232 12

Chongqing 0.511 0.370 0.4202 13

Hebei 0.469 0.298 0.3887 14

Evaluating the Quality of Medical and Health Services by the Method of Topsis and Linear Interpolation in China

Anhui 0.468 0.296 0.3876 15

Tianjin 0.686 0.381 0.3573 16

Guizhou 0.542 0.238 0.3053 17

ian 0.556 0.225 0.2878 18

Jian

su 0.586 0.212 0.2654 19

Shaanxi 0.581 0.204 0.2603 20

Hainan 0.678 0.219 0.2445 21

Liaoning 0.616 0.172 0.2183 22

Heilongjiang 0.637 0.178 0.2183 23

Nin

xia 0.686 0.181 0.2090 24

Xizan

0.703 0.185 0.2085 25

Qin

hai 0.691 0.152 0.1799 26

Shanxi 0.656 0.115 0.1489 27

Jilin 0.730 0.041 0.0527 28

Inner Mon

olia 0.673 0.037 0.0518 29

3.3 Linear Interpolation Method,

Comprehensive Evaluation Results

According to the mean value of each evaluation

index of provinces and cities, minor sort, the results

show that the sorting is located in the top three,

respectively is sichuan, guangxi, henan, and after the

three were in Inner Mongolia, shanxi, jilin, as shown

in the table 3.

Table 3: Based on the linear interpolation method, the average size of minor sort of job evaluation in towns and townships

medical services.

Area X1 X2 X3 X4 X5 X6 P

The

sorting

Sichuan 25.53 19.67 15.42 25.50 24.28 29.00 0.80 1

Guan

xi 21.25 27.00 16.46 22.00 13.45 16.89 0.67 2

Henan 20.61 13.67 17.51 16.17 29.00 19.11 0.67 3

Yunnan 15.52 23.00 28.58 20.83 13.34 9.83 0.64 4

Xinjiang 27.44 21.00 18.34 29.00 5.89 7.34 0.63 5

Jian

xi 24.37 25.67 9.99 22.00 8.59 13.69 0.60 6

Hubei 29.00 15.00 8.31 17.33 15.04 17.29 0.59 7

Hunan 25.41 21.67 1.00 17.33 10.68 24.54 0.58 8

Chongqing 27.50 17.00 7.27 29.00 5.46 10.64 0.56 9

Guangdong 16.56 26.33 9.57 8.00 17.43 13.22 0.52 10

Shandong 19.74 13.00 7.06 13.83 19.07 18.23 0.52 11

Jian

su 21.42 11.00 14.16 9.17 21.51 11.25 0.51 12

Anhui 19.69 17.67 9.78 12.67 12.03 10.90 0.48 13

Guizhou 10.60 29.00 9.57 12.67 7.14 8.47 0.45 14

Hebei 18.47 13.67 6.85 12.67 12.54 11.58 0.44 15

Fujian 13.26 21.00 14.37 12.67 7.24 6.10 0.43 16

Gansu 19.34 19.00 9.99 13.83 5.47 5.19 0.42 17

Jian

su 13.38 1.00 29.00 1.00 24.23 2.83 0.41 18

Shaanxi 11.59 13.00 10.19 15.00 5.97 5.67 0.35 19

Heilongjiang 17.37 19.67 1.42 13.25 2.85 5.11 0.34 20

Qinghai 16.50 25.00 4.13 10.33 1.00 1.62 0.34 21

Ningxia 13.03 17.67 20.01 3.33 2.05 1.20 0.33 22

Hainan 3.89 18.33 25.87 3.33 3.28 1.38 0.32 23

Xizan

1.00 28.33 19.39 3.33 1.40 1.12 0.31 24

Liaoning 10.26 11.00 8.10 13.83 4.73 4.39 0.30 25

Tianjin 10.08 11.67 15.84 5.67 1.99 1.35 0.27 26

Inner

Mon

olia

9.04 18.33 2.88 6.83 3.45 3.19 0.25 27

Shanxi 4.93 5.00 5.39 9.17 4.44 3.59 0.19 28

Jilin 1.29 11.67 1.21 3.33 2.81 1.00 0.12 29

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3.4 Correlation Analysis

The ranking results of two comprehensive

evaluation methods are the same, On the results of

regional sorting the raw data. Completely random

design of Kruskal Wallis H - inspection, the result

shows that the difference in the ranking results of

two kinds of evaluation methods has no statistical

significance. Further do Spearman correlation

analysis, the result of the evaluation shows that the

ranking results of two kinds of evaluation methods

have high correlation（r=0.915, P<0.01）,as shown

in the table 4.

Table 4: Two kinds of Spearman correlation analysis of

the evaluation results.

TOPSIS

method

linear

interpolation

method

TOPSIS method 1.000 0.915

linear interpolation method 0.915 1.000

3.5 Two Kinds of Evaluation Results of

Correlation Analysis

Two kinds of evaluation results is not the same, to

ensure the accuracy and objectivity of the evaluation

results, the results of the two evaluation methods

show comprehensive sequencing, the results showed

that the country towns and townships of medical

service quality of the top three provinces, guangxi,

henan, sichuan, those in the bottom three of shanxi,

Inner Mongolia, jilin, respectively. As shown in the

table 5.

Table 5: Based on two methods of evaluation of

comprehensive sorting table in towns and townships of

medical services.

Area

TOPS

metho

linear

interpol

ation

method

The

averag

e sort

The

compreh

ensive

sequenci

Sichuan 1 1 1.00 1

Henan 2 3 2.50 2

Guangxi 3 2 2.50 2

Yunnan 8 4 6.00 3

Henan 5 8 6.50 4

Hubei 6 7 6.50 4

Shandon

4 11 7.50 5

Jian

xi 10 6 8.00 6

Xinjiang 12 5 8.50 7

Jiangsu 7 12 9.50 8

Guan

don

9 10 9.50 8

Chon

13 9 11.00 9

Anhui 15 13 14.00 10

Zhejiang 11 18 14.50 11

Hebei 14 15 14.50 11

Guizhou 17 14 15.50 12

ian 18 16 17.00 13

Gansu 19 17 18.00 14

Shaanxi 20 19 19.50 15

Tianjin 16 26 21.00 16

Heilongjiang 23 20 21.50 17

Hainan 21 23 22.00 18

Nin

xia 24 22 23.00 19

Liaonin

22 25 23.50 20

Qinghai 26 21 23.50 20

Xizang 25 24 24.50 21

Shanxi 27 28 27.50 22

Inner

Mongolia

29 27 28.00 23

Jilin 28 29 28.50 24

4 CONCLUSIONS

4.1 Comprehensive Evaluation Results

At present, the urban grassroots medical and health

service system is steady and rapid development, but

there are still areas development speed and scale

imbalance problem. Comprehensive evaluation

results from the above, our country towns and

townships in the central region the low level medical

service quality, this is consistent with the result of

actor of (Liu 2013). Among them, the medical

service quality comprehensive ranking top three,

respectively is, guangxi, henan, sichuan, after three

shanxi, Inner Mongolia, jilin, respectively.

Sichuan, henan, guangxi region in towns and

townships of medical service quality is good, is

located in the top level. Sichuan towns and

townships comprehensive medical service quality is

best, high on the first bit admissions index; The

number of physician practice in henan and

admission number is located in the country first and

third respectively. In towns and townships of shanxi,

Inner Mongolia, jilin region after comprehensive

ranking in the national health service ability.

Hospital in jilin people located in all but 1, sickbed

utilization rate, average daily visits and

professionals, average daily for hospital beds per

second from bottom in the country. Grassroots

health work in recent years, the rapid development

in our country, but the regional conditions and

policy environment to a certain extent, affect the

operation of the medical and health work and

development. Some less developed areas of fiscal

investment is insufficient, compensation mechanism

Evaluating the Quality of Medical and Health Services by the Method of Topsis and Linear Interpolation in China

is imperfect, the government health work value

degree is low, lead to the low level of health

manpower, equipment and funds, weak grassroots

service capacity (Xue 2014). So, in order to improve

the basic health service ability, improve the

grassroots health development of the regional

imbalance, local governments should improve

attention to grassroots health work, increase policy

support and financial support. Central policy tilt in

less developed areas should be targeted to the

economy, to strengthen the construction of

infrastructure, the rational allocation of health

resources, perfect the incentive mechanism, to

provide economic underdeveloped regions in health

manpower and material resources, and promote the

equal basic health services.

4.2 The Application Value of the Two

Kinds of Evaluation Method

The combination of two kinds of evaluation

methods, can be more intuitive, accurately reflect the

regional grassroots medical service level (Ying, Liu,

Zhao, Wang, Sa, LI 2016). By Spearman correlation

analysis, according to two kinds of results

correlation is higher, the correlation coefficient were

statistically significant. Although the two kinds of

evaluation results, but the difference was not

significant, examined the Kruskal Wallis H - and

there was no statistically significant difference of the

two kinds of evaluation result, and the results have

good consistency. In this paper, research results are

accurate, can reflect the regional differences of the

basic medical service quality.

ACKNOWLEDGEMENTS

We thank all collaborators for their contribution in

collecting data for current study.

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