A discrete choice experiment (DCE) is a quantitative method that aims to elicit stated preferences. This method draws on Lancaster’s consumer theory, which assumes that health care interventions and policies are combinations of attributes and that individuals’ choice of these goods is based on various levels of these attributes[28]. The DCE model has been widely used to predict the probability of uptake of various contract service plans and to determine the preferences for goods services in lieu of observations of real-world market interactions.
DCE Questionnaire Design
To select representative attributes that can clearly depict and capture residents’ preferences for family doctor teams under FDCSs, we developed a DCE questionnaire through qualitative methods, including a literature review and interviews with key informants. We first reviewed the international and domestic literature on primary health care providers and patients' choices of doctors to identify which attributes were highly relevant to our study. A pilot study recruited 3 rural residents who signed an FDCS contract, 2 village doctors and 2 township hospital managers from Zhangqiu County, located in central Shandong Province, to encourage them to share their views on 1) how the family doctor service mechanism has been implemented; 2) the influencing factors considered by residents to sign family doctor contract service contracts; 3) the hindering factors that deter awareness and acceptance of this service scheme; and 4) policy recommendations to increase the family doctor signing rate. Using semi-structured interviews, we collected data about what factors influence rural residents the most when they sign family doctor contracts. A DCE workshop with 2 DCE experts was also conducted on March 23-25, 2018. The DCE experts provided valuable suggestions on describing the attributes, determining the levels for each attribute, and designing the experiment. Combined with the literature review results and the common suggestions raised by FGD participants, five determinants that impact rural residents’ decision making the most were selected.
The five attributes of FDCS contracts described below were determined to be the most relevant to uptake in our setting. A full description of the attribute selection and questionnaire implementation process is available in the Appendix.
(1) Contract price: This attribute refers to the annual signing expenses incurred by an individual resident. After we reviewed public policies and guidelines on FDCSs enacted by central and local governments, three levels were specified for this attribute: 0 CNY, 100 CNY and 200 CNY per year[29, 30].
(2) Availability of medicines: Medicine availability refers to the ability to obtain affordable medicines that are necessary for a person to maintain his or her health[31]. We selected this attribute to indicate the accessibility of health services provided by the contracted family doctor. We divided this attribute into two levels in our questionnaire: shortage and sufficient.
(3) Insurance reimbursement rate: While health insurance was recently universalized in China, insurance reimbursement rates vary by plan and scheme. Previous studies have shown a close relationship between medical insurance and patients’ choice of medical treatment[32]. Referring to the reimbursement guidelines issued by the Shandong Health Commission, we divided this attribute into three levels in our questionnaire: standard reimbursement, 5% more than the standard reimbursement rate, and 10% more than the standard reimbursement rate.
(4) Family doctor competence. The competence and skill of physicians are considered of great importance to patients[25, 33, 34]. This attribute refers to a resident’s attention to physician credentials and perceived competence when selecting a family doctor. We divided this attribute into three levels in our questionnaire: low, medium and high.
(5) Family doctor attitude. Many studies have shown a correlation between doctors' attitudes and patients' medical behaviours[35-37]. Thus, we sought to investigate the relative importance of perceived attitude in the decision to sign a family doctor team. In this research, this attribute was divided into three levels: poor, normal and good.
A consistency test was performed to ensure that each respondent made realistic trade-offs and to check validity of this research. In this study, one repeated choice set question was added to each version of the questionnaire to check the preference consistency of each respondent. We excluded the information of respondents who failed the consistency test.
Data Collection
This study was conducted in Shandong Province, the second largest province in China. Within Shandong, 3 cities—Binzhou, Zibo, and Liaocheng, located in the northeast, central, and west regions of the province, respectively—were selected as study sites. Multi-stage random sampling was used to choose a sample of respondents representative of the rural residents in each selected city. To do so, 2 counties in each city were first chosen at random. Within each county, 5 townships (the administrative level below the county) and 24 households in each township were randomly chosen. In this study, the questionnaire was administered to 720 residents 18 years of age and above, which is more than the 600 observations recommended as sufficient for preference heterogeneity analysis[38]. Among the 720 questionnaires, 20 of them were incomplete, and these ineligible surveys were dropped. A total of 91 surveys failed to pass the consistency test in the questionnaire and were excluded. Finally, 609 questionnaires were included in the statistical analysis.
Data were collected in this study through a DCE questionnaire administered by teams of trained enumerators at study households. Since most respondents had low levels of educational attainment, a face-to-face interview method was applied to ensure that each respondent clearly understood the entire survey. At the beginning of each interview, the enumerators described the purpose of the study and sought participant consent. Following consent, a brief introduction to FDCSs, the recent public health policies implemented by the government, and the attributes in each choice set were explained. This explanation was then followed by a one-page introduction to the task with a warm-up choice question to check whether the respondent could fully understand the questionnaire and make trade-offs in each pair-wise choice set. Each participant was asked to imagine different hypothetical scenarios in which different family doctor contract service plans are enrolled in to enhance their health status. They were then asked to make discrete choices between 10 pair-wise combinations of scenarios. On average, it took approximately 50 minutes to complete the whole questionnaire, and the survey was returned to the interviewer immediately. A sample questionnaire choice is shown in Table 1.
Table 1 An example of a DCE question.
Attributes
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Contract plan 1
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Contract plan 2
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Cost of the contract
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200 CNY/year
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100 CNY/year
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Availability of medicine
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Easy
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Difficult
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Reimbursement rate
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Standard
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10% more
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Family doctor competence
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Medium
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Low
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Family doctor attitude
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Good
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Normal
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Which contract plan would you choose?
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□
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□
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Pleases consider that you are going to enrol in a family doctor contract service for yourself. Of the two contract plans above, which contract plan would you choose?
Statistical Analysis
The data were first double-entered and coded using EpiData version 3.1, and the final data were then transferred to STATA 14.2 for all statistical analyses.
Random utility theory provided the theoretical foundation for the analysis of the DCE data[39]. Mixed logit models were used to estimate the utility of enrolling in one contract plan[39]. We assumed that the respondents were relatively homogenous in terms of the demographic measures; hence, their preferences would be associated with choice variables. The utility function is specified as follows:

All attributes were dummy coded except for the cost of the contract, which was specified as a continuous variable to facilitate the calculation of willingness to pay (WTP). WTP was calculated to measure the trade-offs among various contract attributes. WTP was estimated as the ratio of the coefficient to the negative coefficient on the contract cost attribute. The coefficients indicated the relative importance of the worst values for the categorical variables.