Currently, there are many studies on family doctor contracting services from the perspective of residents, but few scholars have conducted studies on the current situation of family doctor team contracting based on the perspective of general practitioners (GPs) .

To understand the current situation of family doctor contracting services in primary health care institutions in Guangdong Province, and explore the factors affecting the contracted number from the perspective of the supplier.

From July 5—31, 2021, GPs in primary health care institutions in Guangdong Province were selected as the study subjects by using a multi-stage stratified cluster sampling method to conduct the survey with a self-designed questionnaire. The contracted number was compared by different GPs and their family doctor team characteristics. A two-level Logistic regression developed by R 4.2.2 software was used to identify influencing factors of contracted number above 2 000.

A valid sample of 3 252 cases in family doctor team with contracted number more than 100 was screened, and the median contracted number was 1 400 (2 499) in 2020. The differences were statistically significant when comparing the contracted number by gender, age, education level, position, employment form, working years, working unit, working area, training acceptance, and annual income, number of team members, population size under jurisdiction, willingness of specialists from medical community to join the team, inpatient bed resources and guidance from superior departments (P<0.05). Zero model fitting showed that contracted number was clustered at the regional level (P<0.05). Two-level Logistic regression model showed that, with master's degree or above as the reference, the contracted number of the team including GPs with college〔OR (95%CI) =2.79 (1.84, 3.74) 〕and secondary/high school〔OR (95%CI) =2.83 (1.80, 3.86) 〕degrees were more likely to be above 2 000; taking no position as reference, the contracted number of the team including unit leaders〔OR (95%CI) =0.66 (0.33, 0.99) 〕was more likely to be above 2 000; taking temporary staff as reference, the contracted number of the team including formal staff〔OR (95%CI) =2.02 (1.53, 2.51) 〕was more likely to be above 2 000; taking the team with size of 3 or less people as reference, the contracted numbers of the teams with size of 4 to 6 people〔OR (95%CI) =1.31 (1.05, 1.57) 〕, 7-10 people〔OR (95%CI) =2.06 (1.75, 2.37) 〕, 11-19 people〔OR (95%CI) =3.67 (3.31, 4.03) 〕and≥20 people〔OR (95%CI) =3.46 (2.74, 4.18) 〕were more likely to be above 2 000; taking population size under jurisdiction at 2 000 or less as reference, the contracted numbers of the team with population size under jurisdiction at 2 001 to 9 999〔OR (95%CI) =2.37 (2.12, 2.62) 〕, 10 000 to 29 999〔OR (95%CI) =2.92 (2.65, 3.19) 〕and more than 30 000〔OR (95%CI) =2.86 (2.55, 3.17) 〕were more likely to be above 2 000; taking condition of having inpatient bed resources as reference, the contracted number of the teams without such resources〔OR (95%CI) =1.38 (1.14, 1.62) 〕was more likely to be above 2 000 (P<0.05) .

The population under jurisdiction and the large number of team members create favorable conditions for contracting; family doctor teams with GPs with positions, inpatient bed resources and high education level have a good understanding of family doctor contracting service policies and control the number of contracted patients better; comparing with temporary staff, GPs team with formal staff may undertake more contracting tasks.

目前，从居民角度针对家庭医生签约服务开展的研究较多，但少有学者基于全科医生视角开展家庭医生团队签约现状相关研究。

了解广东省基层医疗卫生机构家庭医生签约服务现状，从供方视角，探寻影响家庭医生团队签约人数的因素。

于2021年7月5—31日，采用多阶段分层整群抽样法，选取广东省基层医疗卫生机构全科医生为研究对象，使用自行设计的调查表对其进行调查。比较不同全科医生及其所在家庭医生团队特征下家庭医生团队签约人数，采用R 4.2.2软件建立两水平Logistic回归模型，识别全科医生所在家庭医生团队签约人数是否>2 000人的影响因素。

筛选出所在家庭医生团队签约人数在100人以上的有效样本3 252个。2020年全科医生所在家庭医生团队中位签约人数为1 400（2 499）人。不同性别、年龄、文化程度、职务、用工形式、工作年限、工作单位、执业地区、接受培训情况、年收入的全科医生所在家庭医生团队签约人数比较，差异有统计学意义（P<0.05）；人员数量、管辖人口数、希望医共体内医院专科医生加入团队情况、住院床位资源情况、上级部门指导情况不同的家庭医生团队签约人数比较，差异有统计学意义（P<0.05）。零模型拟合结果显示，家庭医生团队签约人数在全科医生执业地区水平上具有聚集性（P<0.05）。两水平Logistic回归全模型结果显示，以硕士研究生及以上学历者为参照，大专〔OR（95%CI）=2.79（1.84，3.74）〕和中专/高中〔OR（95%CI）=2.83（1.80，3.86）〕学历的全科医生所在家庭医生团队签约人数在2 000人以上的可能性更大；以无职务者为参照，职务为单位负责人的全科医生所在家庭医生团队签约人数在2 000人以上的可能性更小〔OR（95%CI）=0.66（0.33，0.99）〕；以临聘人员为参照，用工形式为正式在编的全科医生所在家庭医生团队签约人数在2 000人以上的可能性更大〔OR（95%CI）=2.02（1.53，2.51）〕；以人员数量为≤3人的家庭医生团队为参照，人员数量为4~6人〔OR（95%CI）=1.31（1.05，1.57）〕、7~10人〔OR（95%CI）=2.06（1.75，2.37）〕、11~19人〔OR（95%CI）=3.67（3.31，4.03）〕和≥20人〔OR（95%CI）=3.46（2.74，4.18）〕的家庭医生团队签约人数在2 000人以上的可能性更大；以管辖人口数为≤2 000人的家庭医生团队为参照，管辖人口数为2 001~9 999人〔OR（95%CI）=2.37（2.12，2.62）〕、10 000~29 999人〔OR（95%CI）=2.92（2.65，3.19）〕和≥30 000人〔OR（95%CI）=2.86（2.55，3.17）〕的家庭医生团队签约人数在2 000人以上的可能性更大；以有住院床位资源的家庭医生团队为参照，无住院床位资源的家庭医生团队签约人数在2 000人以上的可能性更大〔OR（95%CI）=1.38（1.14，1.62）〕（P<0.05）。

管辖人口、团队人员数量多为签约创造了有利条件；有职务、有住院床位资源、学历高的全科医生所在家庭医生团队对家庭医生签约服务政策了解度高，对签约人数控制得较好；与临聘人员相比，正式在编的全科医生所在家庭医生团队可能承担了更多的签约任务。