A cross-sectional survey on influencing factors of contracted services of Chinese family doctors : A quantitative and qualitative study

Background: The family doctor system has gained rapid ground worldwide. In recent years, China has been actively exploring family doctor-type contracted services. The purpose of this study was to explore the influencing factors of Contracted Family Doctors Services (CFDS) from the perspectives of community health service providers, administrators and medical staff, and it provides a strong basis for the development and promotion of CFDS. Methods: A combination of quantitative and qualitative methods was adopted in this study. A cross-sectional survey was conducted among community health service providers and administrators in 12 community health service centers across four provinces (Zhejiang, Anhui, Beijing, and Shanghai) of China. A total of 389 people took the survey. Ultimately, 320 questionnaires were valid. The effective response rate was 82.3%. A total of 36 consumers were interviewed through in-depth interviews. The total effective rate 100.0%. Exploratory factor analysis, confirmatory factor analysis, and expert consultation were used to analyze the influencing factors of CFDS. Results: The factors influencing CFDS from the perspectives of medical staff were divided into four dimensions, with the following weighting coefficients: national government (31.87%), community health service agency factors (24.73%), consumers-related factors (22.58%), and contracted doctor-related factors (20.82%). The factors influencing CFDS from the perspectives of patients/consumers were national policy factors, contracted team factor, and consumers-related factors. Conclusions: National governments, community health agencies, community health workers, and consumers play an important role in the advancement of CFDS. Therefore, the development of CFDS needs to consider the rights and interests of all stakeholders involved.


Background
The family doctor system, as an important policy measure to realize the Alma-Ata Declaration's grand goal of primary health care for all, has gained rapid ground worldwide [1]. According to a World Health Organization report, the proportion of all patients with diseases requiring specialized medical treatment was only about 5%, and more than 90% of health problems could be effectively solved by professionally trained general practitioners [2].The role of general practitioners/family doctors, according to the World Organization of Family Doctors, is to provide comprehensive health care services to every person seeking them, and arrange for other health professionals to provide related services when necessary [3]. So far, this concept of family doctors has been accepted by many countries. The family doctor system has been implemented in more than 50 countries and regions in the world and has achieved gratifying results in various aspects, which has attracted the attention of governments and medical circles [4]. There exist obvious differences in the specific service modes and operating mechanisms in various countries. Moreover, there is no doubt that the family doctor system plays an important role in medical and health service systems across countries. The family doctor system originated in the United States in the 1960s [5], when the government integrated health management into the community general practitioner service model [6]. At the same time, active follow-up observations were performed on patients with chronic diseases and during the rehabilitation period [6].
In the UK, the National Health Service was established in 1948and adopted the national management model, which requires citizens to register their family doctors and sign contracts with them [7]. The Cuba established the family doctor program, in which a family physician and at least one nurse were each responsible for providing primary disease prevention and medical treatment services to 120-150 families [8]. The family doctor system in Denmark is a form of health care developed from the private doctor system, and each family doctor is responsible for a maximum of 1,780 health care-registered patients/consumers [9].
However, in China, the idea of "family doctors" was introduced in the 1980s, when "family doctortype contracted services" were proposed. In recent years, China has been actively exploring family doctor-type contracted services. Relevant scholars have proposed some suggestions and directions for the development of contracted family doctor services (CFDS) and have also analyzed some influencing factors of CFDS.
Although there are existing studies on the influencing factors of CFDS in China [10][11], there are several differences in this study. First, this paper studied the influencing factors of CFDS as a whole, rather than just from a single point of view such as that of patients/consumers or medical staff. Secondly, the investigation area of this study is from typical areas of CFDS, rather than a single city from a certain area. Thirdly, the most important difference is that the study is set against the backdrop of China's latest policies.
Based on the new policy environment, this study explored the influencing factors of CFDS from the perspectives of community health service providers, administrators and medical staff, which can help to improve the contracting rate of family doctors, to promote the health of consumers, and to provide a basis for the government and the health administration to formulate policies for CFDS.

Study design and population
A cross-sectional survey was used to select 12 community health service centers in four regions of Zhejiang, Anhui, Beijing, and Shanghai provinces in a typical area survey. The cluster sampling method was used to conduct a questionnaire survey on the directors of the community health service centers, the CFDS team from community health service agencies, and the administrative staff.
Moreover, convenient sampling method was used to conduct in-depth interviews with patients/consumers in the same regions.

Data collection
Data were collected from July through September 2017. Respondents filled out an anonymous questionnaire after providing informed consent. A total of 389 questionnaires were distributed. While all of them were returned, 320 questionnaires were valid (total effective rate 82.3%).The reasons for elimination included incomplete questionnaires, multiple omissions, or multiple choices. We interviewed 3 patients/consumers in each community health service center. A total of 36 patients/ consumers were interviewed. The total effective rate 100.0%.

Questionnaire
The Questionnaire on the Influencing Factors of CFDS was designed based on five steps. First, we tried to select as many items as possible by searching for relevant literature [12][13]. Then, these items were summarized and collated through four times panel discussions, and items with similar or repeated meanings are deleted. Next, five experts (including health service management experts, public health experts, and contracted services researchers) were consulted to revise and improve the questionnaire. Finally, pre-study was conducted at four community health service centers in Harbin City. The 120 questionnaires were distributed and returned (pre-study data were not included in the final data analysis). Based on this, the questionnaire was further refined and finalized (Cronbach's α for the questionnaire was 0.865). Data were collected using the final questionnaire, which comprised the following sections: 1.
Sociodemographic information (including gender, age, education level, professional title, etc.). were excluded according to the following criteria: a factor load of <0.40; a higher load on multiple factors; and a factor with less than three items included. The orthogonal rotation was used to explain the factor structure reasonably. The model was considered to have a good fit when all path coefficients were significant at the level of 0.05; χ2/df was below 5; the root mean square error of approximation (RMSEA) was below 0.08; the root mean square residual(RMR) was below 0.10; and the goodness of fit index(GFI), the normed fit index(NFI), Tucker-Lewis incremental (TLI) fit and comparative fit index(CFI) were ≥0.90. A p-value of <0.05 was considered statistically significant.

Results of in-depth interviews
Through in-depth interviews with patients/consumers, the reasons why they were more willing to accept CFDS are summarized. For example, patients/consumers' understanding level of CFDS; benefits of CFDS; concern about one's own health; the degree of family doctors' protection of patients/consumers' privacy; cost and process of signing a contract; satisfaction with the community; and advocacy of contracting services, etc. The keywords extracted from the interviews were counted and found that the factors affecting CFDS were as follows: national policy factors, contracted team factor, and consumers-related factors.

Demographic characteristics of community medical staff
The demographic characteristics of the medical personnel are shown in Table 1.

Analysis of the influencing factors of CFDS Exploratory factor analysis
The KMO value calculated was 0.836, which is within the scope of factor analysis (if the KMO value is close to 1, the variable group is suitable for factor analysis). Results showed that data could be used for factor analysis.
After finishing the orthogonal rotation of the factor load matrix, the remaining 25 items made the characteristic root >1, the maximum variance was orthogonal rotation, seven factors were extracted from the system, and the cumulative variance contribution rate of 67.613% is shown in Table 2. From Table 2, it can be clearly seen that 25 observational variables were clearly classified into seven common factors. Based on the results of the group discussion among project team members, seven factors were named according to the characteristics of the variables observed. F1 was "national policy factor", the combination of F2 and F3 was "resident factors", the combination of F4 and F5 was "contract doctor factors", and the combination of F6 and F7 was "community factors".

Confirmatory factor analysis
The results of the CFA were as follows: the RMSEA was 0.059, and thus was less than the 0.08 cutoff that indicates a good fit; the RMR was 0.05; The TLI, NFI, GFI, and CFI were 0.913, 0.902, 0.905, and 0.917, respectively.

Results of expert consultations
The health and family planning commission, contracted services researchers, and administrators were selected to carry out an expert consultation. The above results were modified according to their inputs, and the final versions of the predisposing factors are listed below.
In the first round of consultation, the name of each dimension in the model was modified: "national policy factors" was revised to "national government factors", "resident factors" was revised to " consumers-related factors", "contracted doctor factors" was revised to "contracted doctor-related factors", and "community factors" was revised to "community health service agency factors".
The second round of consultation integrated the dimensions of the model. The experts deemed that, "situation of the first diagnosis of the patients/consumers" should be incorporated into the residentrelated factors dimension rather than contracted doctor-related factors.

The final determinants of the factors of CFDS
The final determinants of the factors of CFDS are shown in Table 3.
Based on the above results, we merged similar factors into four dimensions. Finally, the weight coefficients of the common factors were 0.319, 0.247, 0.226, and 0.208, respectively (see Table 4 for specific details).

Discussion
Compared the factors affecting CFDS from the perspective of patients and medical staff, we found that the factors of national policy and community health service agency are two important common factors affecting CFDS.
The results showed that the national government factor is the main trigger that affects CFDS. The

Limitations
This study has two limitations. First, the sample size of the study is small; a typical survey needs to select a sample representative of a typical unit, so there is a higher requirements for judgement ability of the researchers, otherwise it may cause investigation conclusion has the certain bias tendency, and the results of typical survey in general is not easy to calculate the overall situation.

Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethical approval
This research project was approved by the Medical Ethics Committee of Harbin Medical University.
Before the survey, we received approval from the community health centre.

Consent for publication
Not applicable.