Analysis of Risk Management Ability of Chronic Disease on General
Practice Team in Shandong Province, China
Yuqing Mi
1,† a
, Jiping Zhang
2,‡ b
, Kexuan Chen
1,§ c
, Jingwen Huang
1,** d
, Ruxin Kou
1,‡‡ e
and Wei Li
1,* f
1
School of Public Health, Weifang Medical University, Weifang, China
2
Department of Hospital Infection-Control, Qingdao Jiaozhou Central Hospital, Qingdao, China
*
Keywords: General Practice Team, Chronic Disease, Risk Management, Ability.
Abstract: This study aimed to understand and analyse the ability of general practice team in chronic disease risk
management, and to explore the risk factors that affect the ability of general practice team in chronic disease
risk management. So as to provide theoretical and empirical basis for improving the risk management level
of chronic diseases on general practice team. We used the mean and standard deviation (𝑥̅ ± SD) and
frequency (%) to describe the distribution of quantitative and qualitative data respectively. The t test and
ANOVA test were used to compare the difference of risk management ability of chronic between different
groups.
The multiple linear regression analysis was used to analyse the influencing factors of risk
management ability of chronic on general practice team. The scores of risk management ability of the
general practice team in chronic disease prevention, chronic disease diagnosis and treatment, chronic
disease rehabilitation and nursing dimensions were as follows (55.88±13.00), (84.52±18.85) and
(36.26±15.39). The risk management ability of the general practice team at the level of chronic disease
prevention and chronic disease diagnosis and treatment was at a medium to high level, and the risk
management ability of the general practice team at the level of chronic disease rehabilitation and nursing
was at a low level in Shandong Province. There were many factors that affect the chronic disease risk
management ability of general practice team, the core factors included higher refresher course, degree of
promotion, awareness of chronic disease risk management, working pressure and welfare benefits. It is
necessary to implement improvement measures from system level, management level and individual level to
optimize the community chronic disease risk management ability of general practice team.
1 INTRODUCTION
1
According to the World Health Organization's
(WHO) global report on chronic diseases in 2014,
the number of deaths from chronic diseases had
reached 38 million in 2012 and was expected to
reach 52 million in 2030, of which 20% were caused
by cardiovascular diseases, chronic respiratory
diseases, cancer and diabetes (Mendis, 2014).
a
https://orcid.org/0000-0002-2923-5618
b
https://orcid.org/0000-0002-9712-7168
c
https://orcid.org/0000-0002-8535-3096
d
https://orcid.org/0000-0003-0059-2563
e
https://orcid.org/0000-0003-3600-1147
f
https://orcid.org/0000-0003-2740-2782
*
Corresponding author
"Healthy China Action (2019-2030)" showed that
nearly 180 million elderly people suffer from
chronic diseases, and one person suffered from a
variety of chronic diseases. The incidence and
mortality of chronic diseases were high, which
brings great risks to people and also becomes a
major public health problem affecting the country's
economic and social development (Jiang, 2020).
With the increasing severity of chronic diseases,
it is very important to implement scientific and
effective risk management of chronic diseases. The
World Health Organization suggested that
community-based comprehensive prevention and
control is one of the effective strategies to prevent
and control the risk of chronic diseases (Lee, 2022).
To prevent and reduce the occurrence of chronic
diseases and reduce the burden of chronic diseases
190
Mi, Y., Zhang, J., Chen, K., Huang, J., Kou, R. and Li, W.
Analysis of Risk Management Ability of Chronic Disease on General Practice Team in Shandong Province, China.
DOI: 10.5220/0012071900003624
In Proceedings of the 2nd International Conference on Public Management and Big Data Analysis (PMBDA 2022), pages 190-195
ISBN: 978-989-758-658-3
Copyright
c
 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

has become the focus of community chronic disease
management (Zhou, 2013). However, at present, the
risk management of chronic diseases in the
community is affected by the fragmented
management mode and the traditional medical mode,
and there are some problems, such as imperfect
management information system, poor effect of
prevention and health care, serious mental health
problems, insufficient medical resources, incomplete
service items, and poor self-health management
awareness of residents (Wang, 2017; Tey, 2016). In
order to improve the comprehensive service quality
and service efficiency of community health, the
General Practice Team (GPT) management mode
with general practitioners as the core and community
nurses and public health doctors as the auxiliary has
become one of the basic chronic disease risk
management modes (Harris, 2011).
This study integrated health management and
risk management, and analysed the ability of GPT in
chronic disease risk management, and explored the
risk factors that affect the ability of general practice
team in chronic disease risk management. This study
might provide theoretical and empirical basis for
improving the risk management level of chronic
diseases in GPT, so as to strengthen the prevention
and control effect of chronic diseases, reduce the
burden of chronic diseases and improve the quality
of life of residents.
2 METHODS
2.1 Study Design and Participants
Chinese and English literature, laws and regulations,
and policy documents related to chronic disease risk
management in general practice teams were
searched. A total of 4656 literatures were searched,
and irrelevant literatures were excluded. Finally, 279
literatures were included. Two researchers extracted
the related projects of chronic disease risk
management of general practice team. Based on
consulting experts in related fields and community
workers, the study constructed a project collection to
evaluate the chronic disease risk management ability
of general practice team.
Data of the current study (N=278) were collected
from a survey on risk management ability of general
practice team in Shandong province, China. The
random stratified cluster sampling method was
applied to select the survey subjects.
Three cities of
Shandong province and 18 community health
service centers were chosen by equal ratio randomly
according to the development of economy and the
geographical location. Then, all members of the
general practice team were chosen as the survey
respondents.
In order to control the information bias and loss,
the collaboration institutes research meeting had
been held several times to discuss the quality
control. Pilot investigation was carried out to test the
reliability and validity of the questionnaires. The
interviewers were trained in order to increase the
skill of interviewer.
2.2 Ethics Approval and Consent for
Participate Statement
This study was approved by the Ethics Committee of
Weifang Medical University, and written informed
consent was obtained from all participants.
2.3 Statistical Analysis
The EpiData 3.1 was used to build a database. SPSS
20.0 and AMOS 24.0 software were used to analyse
the data. The mean and standard deviation (𝑥̅ ± SD)
and frequency (%) were used to describe the
distribution of quantitative and qualitative data
respectively. The t test and ANOVA test were used
to compare the difference of risk management ability
of chronic between different groups. The multiple
linear regression analysis was used to analyse the
influencing factors of risk management ability of
chronic on general practice team. All analyses were
two tailed and statistical significant probability was
determined by P ≤ 0.05. The Multiple Linear
Regression Model describes how the dependent
variable changes with the changes of multiple
independent variables. Partial regression coefficient
β indicates the average change of the dependent
variable when the independent variable changes by
one unit while the other independent variables
remain the same. The methods of independent
variables entering the equation include forward
method, backward method and stepwise regression
method. This study used stepwise regression
method.
3 RESULTS
3.1 Basic Situation of the Sample
There were 278 eligible residents recruited in the
current study and 278 residents actually participated
Analysis of Risk Management Ability of Chronic Disease on General Practice Team in Shandong Province, China
191

in. The participation rate was 100%. Basic situation
was shown in Table 1.
3.2 The Score of Risk Management
Ability of Chronic Disease on GPT
The study integrated health management and risk
management. According to the theory of tertiary
prevention of chronic diseases, the general practice
team's chronic disease risk management ability was
divided into three dimensions: chronic disease
prevention, chronic disease diagnosis and treatment,
chronic disease rehabilitation and nursing. After two
rounds of Delphi expert consultation, 24 projects to
assess risk management capabilities had been
formed. The abilities ranged from 1 to 10 points
from low to high, and the scores ranged from 24 to
240 points (Table 2).
3.3 Influencing Factors of Risk
Management Ability of Chronic
Disease on GPT
3.3.1 Single Factor Analysis
The dependent variable of the study was the risk
management ability of chronic disease on general
practice team. Independent variables were as
follows, gender, age, education level, professional
title, training time / 1 month(h), higher refresher
course, training effect, working pressure, degree of
promotion, Awareness of chronic disease risk
management, project service proficiency,
satisfaction with one's ability, incentive mechanism
and welfare benefits. The factors with statistical
differences included training time, higher refresher
course, training effect, working pressure, degree of
promotion, Awareness of chronic disease risk
management, project service proficiency,
satisfaction with one's ability, incentive mechanism
and welfare benefits (Table 1).
Table 1: Basic situation of general practice team.
Variables
Frequency
(%)
Ability score
(𝒙

± SD)
t/F
Gender
Male 132(47.48) 174.35±41.45 0.752
Female 146
(
52.52
)
178.74±42.80
Age (year)
<25 8(2.88) 169.63±58.89 1.636
25~ 76
(
27.34
)
185.68±40.34
35~ 117(42.09) 173.15±39.74
45~ 77
(
27.34
)
173.79±44.99
Education level
Variables
Frequency
(%)
Ability score
(𝒙

± SD)
t/F
Technical 36(12.95) 180.06±42.44 0.436
College degree
112
(
40.29
)
178.42±42.85
>Bachelor 130(46.76) 174.19±41.64
Professional title
None 44
(
15.83
)
178.32±43.41 1.809
Primar
y
123(44.24) 180.58±42.67
Intermedia
te
95(34.17) 174.34±41.42
Senio
r
16
(
5.76
)
155.59±34.61
Training time / 1 month(h)
0 66(28.57) 159.94±39.34 4.985**
<10 110
(
47.62
)
183.82±43.62
10~ 42(17.18) 182.43±41.72
50~ 13
(
5.63
)
179.92±28.24
Higher Refresher course
Yes 103(37.05) 187.57±41.49 13.263**
No 175
(
62.95
)
167.63±41.26
Training effect
Ver
y
g
oo
d
89
(
38.53
)
186.40±37.66 2.724*
Bette
r
92(39.83) 170.32±42.92
Common 48
(
20.77
)
170.83±47.86
None 2(0.87) 159.00±0.00
Working pressure
None 7(2.52) 198.86±55.77 4.062**
Low 7
(
2.52
)
206.86±28.02
Common 87(31.29) 180.63±47.71
Greate
r
150
(
53.96
)
176.34±40.41
Stressful 27
(
9.71
)
176.65±43.02
Degree of promotion
Difficult
y
249
(
89.57
)
157.26±40.03 12.141**
Easy 29(10.43) 180.50±41.57
Awareness of chronic disease risk management
None 4
(
1.44
)
146.00±28.87 7.317**
Common 60(21.58)
160.55±45.89
Yes 214(76.98) 181.74±39.98
Project service proficiency
Dissatisfie
d
2(0.72)
171.00±0.00
6.455**
Common 55
(
19.78
)
158.80±41.09
Satisfie
d
221(79.50) 181.15±41.49
Satisfaction with one's ability
Dissatisfie
d
10(3.60) 182.40±32.55 4.797**
Common 67
(
24.10
)
162.92±43.97
Satisfie
d
201(72.30) 180.94±41.13
Incentive mechanism
Dissatisfie
d
45
(
16.19
)
164.49±40.43 5.487**
Common 137(49.28) 173.27±43.24
Satisfie
d
96
(
34.53
)
187.19±39.33
Welfare benefits
Dissatisfie
d
63
(
22.66
)
168.10±45.16 4.402*
Common 130(46.76) 173.85±42.71
Satisfied 85(30.58)
187.29±37.00
*P < 0.05, **P < 0.01
PMBDA 2022 - International Conference on Public Management and Big Data Analysis
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Table 2: The score of risk management ability.
Dimension/Project
Ability
score
(𝒙

± SD)
Chronic disease prevention 55.88±13.00
Dynamic management of health
records
8.19±2.24
Collect patient information
8.17±2.35
Health education
8.04±2.15
Health monitoring
8.54±2.10
Health care guidance
6.96±2.87
Concept guidance for medical
treatment
7.77±2.24
Health consultation
8.20±2.20
Chronic diagnosis and treatment 84.52±18.85
Physical examination
8.45±2.13
Disease screening
7.73±2.35
Follow-up
7.48±2.85
Exercise guidance
7.90±2.29
Sleep and rest instruction
7.71±2.49
Behavior guidance
8.47±1.90
Dietary guidance
8.68±1.94
Environmental hygiene guidance
7.57±2.50
Mental health guidance
7.35±2.75
Appointment registration
5.13±2.98
Medication guidance
8.16±2.53
Chronic disease rehabilitation and
care
36.26±15.39
Therapeutic evaluation
7.01±2.98
Rehabilitation treatment plan
6.68±3.10
Traditional Chinese medicine rehabilitation
7.38±2.70
Rehabilitation training
6.82±3.09
Hospital bed at a patient's home
4.25±3.83
Remote health monitoring
4.11±2.62
3.3.2 Multivariate Analysis
We used multiple stepwise linear regression analysis
for multivariate analysis. The dependent variable of
the study was the risk management ability of chronic
disease on general practice team. Independent
variables were 10 factors with statistical differences
by single factor analysis. The inclusion criteria for
entering the equation was 0.05, and the exclusion
criteria for removing the equation was 0.10.
The F statistic value of multiple regression model
was 11.091(P<0.001), which indicated that the
model had statistical significance. The collinearity
diagnosis resulted that TOL>0.8 and VIF<1.3. It
showed that there was no collinearity problem in this
regression equation. The main factors affecting the
risk management ability of chronic disease on
general practice team included higher refresher
course, degree of promotion, awareness of chronic
disease risk management, working pressure and
welfare benefits. The estimated values of parameters
were shown in Table 3.
Table 3: Multiple stepwise linear regression analysis.
Factors β SC t
TOL VIF
Constant
98.264 3.971**
A
18.791 0.221 3.634**
0.903 1.107
B
-29.232 -0.253 -4.182**
0.908 1.101
C
18.854 0.181 3.013**
0.926 1.080
D
-8.758 -0.169 -2.807**
0.920 1.087
E
11.193 0.133 2.130*
0.856 1.168
*P < 0.05, **P < 0.01. SC: Standardization Coefficients
A- Higher refresher course;
B- Degree of promotion;
C- Awareness of chronic disease risk management;
D-
Working pressure;
E- Welfare benefits.
4 DISCUSSION
In recent years, a series of policy documents on
chronic diseases have been published by China, and
good policy effects have been achieved. The
Medium-and Long-term Plan for Prevention and
Treatment of Chronic Diseases in China (2017-
2025) was released, and it was proposed that the
comprehensive prevention and treatment mechanism
of chronic diseases should be improved, which was
led by the government, coordinated by departments,
mobilized by society and participated by the whole
people in January, 2017(The State Council，2017).
"Healthy China Action (2019-2030)" included the
prevention and treatment actions of four chronic
diseases (cardiovascular and cerebrovascular
diseases, cancer, chronic respiratory diseases and
diabetes) into the major actions of Healthy China in
July 2019(The State Council，2019). Although the
prevention and treatment of chronic diseases in
China has made some achievements, the overall
mortality rate and death toll of chronic diseases are
still at a high level, and the prevention and treatment
of chronic diseases still faces important challenges.
In particular, the comprehensive prevention and
control mechanism of chronic diseases in primary
medical and health institutions was not perfect, and
chronic disease prevention and control personnel
lack information exchange and chronic disease risk
management experience. Chronic diseases still bring
huge risks to residents. This study combined the
concept of health management and risk management
Analysis of Risk Management Ability of Chronic Disease on General Practice Team in Shandong Province, China
193

theory, and relied on the theory of tertiary
prevention of chronic diseases. It investigated the
chronic disease risk management ability of general
practice team, and analysed the risk factors that
affect it from three dimensions: chronic disease
prevention, chronic disease diagnosis and treatment,
and chronic disease care and rehabilitation.
The results showed that the GPT's risk
management ability of chronic disease prevention
level was above the middle level (55.88±13.00,
Score range:7-70). Among them, the ability of health
education, health care guidance and concept
guidance for medical treatment were low. The
possible reasons included the lack of perfect
TCM(traditional Chinese medicine) health care
policies and regulations for chronic diseases(Wang,
2017), lack of TCM and nursing professionals(Jia,
2020). Besides, Nationally, the rural population
occupies only a few health resources, and the
graduates of medical colleges and universities who
choose township hospitals were rare, and health
education and publicity were weak. Some primary
medical institutions lack systematic planning for
chronic disease risk management, and the publicity
and education work was scattered (Nagourney,
2020). The GPT's risk management ability of
chronic disease diagnosis and treatment level was
above the middle level (84.52±18.85, Score
range:11-110). Among them, the score of disease
screening, follow-up, sleep and rest instruction,
environmental hygiene guidance, mental health
guidance and appointment registration were low.
Although the primary medical institutions organized
residents' health check-ups every year, follow-up
visits every quarter, measure their blood pressure
and blood sugar, guide their lifestyle, observe their
illness and give medication guidance, the general
practice team feedback that their chronic disease
diagnosis and treatment ability had not reached a
high level. The reason might be that grass-roots job
training was not in place, limited to theoretical
knowledge training, ignoring the combination of
theoretical knowledge and practical skills training,
which could not meet the development requirements
of chronic disease risk management (Bunschoten,
2019). The GPT's risk management ability of
chronic disease rehabilitation and care was the
medium low level (36.26±15.39, Score range:6-60).
Among them, the score of therapeutic evaluation,
rehabilitation treatment plan and rehabilitation
training were low. And the score of hospital bed at a
patient's home and Remote health monitoring were
very low. At present, the rehabilitation was only
limited to exercise, but the rehabilitation of chronic
diseases covering five prescriptions was not really
carried out, and muscle exercise and balance training
were neglected (Reynolds, 2018). The rehabilitation
and home-based rehabilitation led by primary
medical institutions have not really landed.
Single factor analysis results showed that the risk
factors that affect the chronic disease risk
management ability of general practice team
included training time, higher refresher course,
training effect, working pressure, degree of
promotion, Awareness of chronic disease risk
management, project service proficiency,
satisfaction with one's ability, incentive mechanism
and welfare benefits. This was only a preliminary
assumption. We further verified these risk factors
with multiple stepwise linear regression model. The
results showed that the risk factors of entering the
regression equation included higher refresher course,
degree of promotion, awareness of chronic disease
risk management, working pressure and welfare
benefits. They were the core factors that affect the
general practice team's chronic disease risk
management ability. Among them, the degree of
promotion and working pressure were negatively
correlated with the chronic disease risk management
ability of general practice team, that was, the more
difficult the promotion of professional title was, the
greater the job stress was, the lower the risk
management ability was (Rachmawati, 2019). In
addition, the awareness of chronic disease risk
management, welfare benefits, higher-level study
and general practice team's chronic disease risk
management ability were positively correlated, that
was, the stronger the awareness of chronic disease
risk management, the better the welfare benefits, the
higher education, the higher the risk management
ability (Hadi, 2020).
5 CONCLUSIONS
The risk management ability of the general practice
team at the level of chronic disease prevention and
chronic disease diagnosis and treatment was at a
medium to high level, and the risk management
ability of the general practice team at the level of
chronic disease rehabilitation and nursing was at a
low level in Shandong Province. There were many
factors that affect the chronic disease risk
management ability of general practice team, the
core factors included higher refresher course, degree
of promotion, awareness of chronic disease risk
management, working pressure and welfare benefits.
It is necessary to implement improvement measures
PMBDA 2022 - International Conference on Public Management and Big Data Analysis
194

from system level, management level and individual
level to optimize the community chronic disease risk
management ability of general practice team.
ACKNOWLEDGEMENTS
We thank all collaborators for their contribution in
collecting data for the study.
FUNDED
This study has been funded by National Nature
Science Foundation of China (grant 71774119) and
Soft Science Project in Shandong Province (grant
2022RKY07011).
CONFLICTS OF INTEREST
All authors declare that they do not have any conflict
of interest on this research.
REFERENCES
Bunschoten, C., Jacobs, B. C., Van den Bergh, P. Y. K.,
Cornblath, D. R., & van Doorn, P. A. (2019). Progress
in diagnosis and treatment of chronic inflammatory
demyelinating polyradiculoneuropathy. The Lancet.
Neurology, 18(8), 784–794.
Hadi, M. D., Lin, Y. P., & Chan, E. Y. (2020). My health,
myself: a qualitative study on motivations for effective
chronic disease self-management among community
dwelling adults. Family practice, 37(6), 839–844.
Harris, M. F., Jayasinghe, U. W., Taggart, J. R., Christl,
B., Proudfoot, J. G., Crookes, P. A., Beilby, J. J., &
Davies, G. P. (2011). Multidisciplinary Team Care
Arrangements in the management of patients with
chronic disease in Australian general practice. The
Medical journal of Australia, 194(5), 236–239.
Jia, Q., Wang, L., Zhang, X., Ding, Y., & Li, H. (2020).
Prevention and treatment of chronic heart failure
through traditional Chinese medicine: Role of the gut
microbiota. Pharmacological research, 151, 104552.
Lee, A. Y. L., Wong, A. K. C., Hung, T. T. M., Yan, J., &
Yang, S. (2022). Nurse-led Telehealth Intervention for
Rehabilitation (Telerehabilitation) Among
Community-Dwelling Patients With Chronic Diseases:
Systematic Review and Meta-analysis. Journal of
medical Internet research, 24(11), e40364.
Jiang, C. H., Zhu, F., & Qin, T. T. (2020). Relationships
between Chronic Diseases and Depression among
Middle-aged and Elderly People in China: A
Prospective Study from CHARLS. Current medical
science, 40(5), 858–870.
Mendis, S. (2014). Global status report on
noncommunicable diseases 2010. World Health
Organization 2014.
Nagourney, E. M., Robertson, N. M., Rykiel, N.,
Siddharthan, T., & Alupo, P. Study Investigators
(2020). Illness representations of chronic obstructive
pulmonary disease (COPD) to inform health education
strategies and research design-learning from rural
Uganda. Health education research, 35(4), 258–269.
Rachmawati, S., Prihhastuti-Puspitasari, H., & Zairina, E.
(2019). The implementation of a chronic disease
management program (Prolanis) in Indonesia: a
literature review. Journal of basic and clinical
physiology and pharmacology, 30(6),
/j/jbcpp.2019.30.issue-6/jbcpp-2019-0350/jbcpp-2019-
0350.xml.
Reynolds, R., Dennis, S., Hasan, I., Slewa, J., & Chen, W.
(2018). A systematic review of chronic disease
management interventions in primary care. BMC
family practice, 19(1), 11.
Tey, N. P., Lai, S. L., & Teh, J. K. (2016). The debilitating
effects of chronic diseases among the oldest old in
China. Maturitas, 94, 39–45.
The State Council. (2017).
http://www.gov.cn/zhengce/content/2017/02/14/
The State Council. (2019).
http://www.gov.cn/xinwen/2019/07/15/content.
Wang, S., Ungvari, G. S., Forester, B. P., Chiu, H. F. K.,
Wu, Y., Kou, C., Fu, Y., Qi, Y., Liu, Y., Tao, Y., Yu,
Y., Li, B., & Xiang, Y. T. (2017). Gender differences
in general mental health, smoking, drinking and
chronic diseases in older adults in Jilin province,
China. Psychiatry research, 251, 58–62.
Wang, T., Xu, C., Pan, K., & Xiong, H. (2017).
Acupuncture and moxibustion for chronic fatigue
syndrome in traditional Chinese medicine: a
systematic review and meta-analysis. BMC
complementary and alternative medicine, 17(1), 163.
Zhou, W., Dong, Y., Lin, X., Lu, W., Tian, X., Yang, L.,
& Zhang, X. (2013). Community health service
capacity in China: a survey in three municipalities.
Journal of evaluation in clinical practice, 19(1), 167–
172.
Analysis of Risk Management Ability of Chronic Disease on General Practice Team in Shandong Province, China
195