Willingness rate of the first visit to primary healthcare services and the associated factors in China: a meta-analysis

Keywords: associated factor, China, first visit, health-seeking behaviour, hierarchical medical system, meta-analysis, primary health care, willingness rate.

China maintains a three-tiered healthcare system consisting of primary healthcare (PHC) facilities, secondary hospitals, and tertiary hospitals (Wang et al. 2014). The PHC facilities include community health centres, community health stations, township health centres, and village clinics, all of which serve an important role in the management of acute and chronic conditions, reducing disease burdens, and constitute a cornerstone of the healthcare system (Wu et al. 2017; Zhang et al. 2020). Nevertheless, it has been observed that most patients in China increasingly bypass primary care in favour of higher levels of hospitals when requiring medical treatment (Liu et al. 2018), despite the fact that PHC facilities provide care that is usually more accessible, resulting in an inequitable distribution of medical resources. It is known that many developed countries, like the United Kingdom, Spain, and Germany, have adopted the gatekeeper policy, which requires that patients first consult their primary healthcare providers, then seek their primary care providers’ referrals before visiting a hospital or specialist. This policy has proven to be effective and is critical to optimising the allocation of health resources and meeting the public’s health needs (Grumbach et al. 1999; Lember 2002).

As part of efforts to address imbalances in the distribution of medical resources and divert patients to PHC facilities, the State Council published Guidelines on Promoting Hierarchical Medical System (HMS) in September 2015, emphasising that different levels of hospitals have a clear division of labour and are responsible for providing distinct medical services. Multiple measures are used to determine how the HMS applies to residents’ health-seeking behaviour. Increasing supply side strategies will enhance the infrastructure and human resources in PHC, which can result in an improvement in the quality of primary care provided and increase patients’ trust in such facilities (Wu et al. 2017). In terms of demand-side strategies, significant efforts have been made to direct patients to primary healthcare facilities through the implementation of gradient reimbursement schemes and referral reform (Meng et al. 2015). The first visit to PHC facilities will improve the order of treatment, ultimately leading to the optimal use of medical resources (Wang and Jin 2015).

According to HMS policy, the first visit rate to PHC facilities should be increased to 70% among all medical institutions by 2017 (Li et al. 2021). In some areas, statistics (Zeng et al. 2020) showed that patients were 1.8-fold more likely to visit tertiary hospitals than PHC facilities, suggesting that PHC services are not as effective as originally anticipated. There is a strong correlation between health-seeking preference and health service utilisation (Yao and Agadjanian 2018); therefore, it is very necessary to understand residents’ willingness to first visit PHC facilities and identify the associated factors. A previous study (Zhang et al. 2021) explored the willingness to engage in the first visit to PHC services across the country; however, the study explored a broad range of years and did not discuss the influencing factors related to willingness. There is, therefore, a need to conduct a meta-analysis to collect and analyse existing data on the willingness of Chinese residents after the year 2015 to make their first visit to PHC services and identify its determinants and offer some suggestions to facilitate the smooth implementation of the first visit to PHC services, as well as the improvement of the hierarchical system of diagnosis and treatment.

This review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standards (Moher et al. 2009). Two researchers (CL, LQ) independently carried out each step, and a third researcher was consulted when a consensus could not be reached.

We reviewed studies that investigated the willingness rate for the first visit to PHC facilities and its determinants in China. To assess the eligibility of the articles, the COCOPOP framework (Condition, Context, and Population) was applied (Zhu et al. 2017). Specifically, POP (Population) concerned residents, CO (Condition) concerned the willingness for the first visit to a PHC, and CO (Context) concerned only studies conducted in China. Articles were eligible to be included if they met the following criteria: (1) the type of study should be an observational study (case-control, cohort, or cross-sectional); (2) data collection should have taken place after 2015; (3) studies reporting a willingness or utilisation of first visits to PHC services (or raw data that permitted the calculation of an estimate); (4) only articles in English and Chinese were eligible; and (5) articles had to have been published in a peer-reviewed journal. Preprints, study protocols, and conference abstracts were excluded.

Six electronic databases, including the Cochrane Library, PubMed, Web of Science, CNKI, WanFang, and China Science and Technology Journal Database (VIP), were scientifically explored for articles. To obtain additional articles, we also checked the reference lists of included studies. Different medical subject headings (MeSH) terms and search engines were searched using the following terms, including (‘community health service’ OR ‘township hospital’ OR ‘village clinic’ OR ‘General Practitioner’) AND (preference × OR willingness OR uptake OR utilisation OR attitude) AND (People’s Republic of China OR China OR Chinese). Supplementary material S1 contains a detailed description of the search strategy. The retrieval period spanned from January 2015 to October 2021.

The quality of each study was evaluated using a 14-project quality assessment tool developed by the National Institutes of Health (NIH) (NIH 2013). Each study was determined to be suitable for cohort and cross-sectional studies using five options: Yes, No, Cannot Determine, Not Applicable, or Not Reported. All answers except ‘Yes’ suggest a potential bias. The evaluation criteria include consideration of potential selection bias, information bias, measurement bias, or confounding (indistinguishable exposure mix) risks (NIH 2013). The scoring criteria 6, 7, and 10 were not applicable in cross-sectional studies. A score of less than seven was considered low quality with a high risk of bias; a score of seven to eight was considered medium quality with a certain risk of bias, and a score of greater than or equal to nine was considered high quality with a low risk of bias (NIH 2013).

Data extraction was performed using a standardised data collection form that collected information about study characteristics, including author, publication year, data collection years, region of study setting, study design, sample size, and willingness rate. Possible sources of heterogeneity such as age, sex, study area, and associated factors related to the results were extracted.

For further analysis, we imported the data into Stata software (StataCorp, College Station, TX, USA) and Cochrane Review Manager version 5.3 (The Nordic Cochrane Centre, Copenhagen, Denmark). Pooled estimates are reported using 95% confidence intervals (CIs) with the results, and Cochrane’s Q statistics (Chi-squared), inverse variance (I²), and P-values were used to identify the heterogeneity (Higgins et al. 2003). Given the possible high levels of statistical heterogeneity between studies, random effects enables us to effectively address heterogeneity that cannot readily be explained by other factors (Migliavaca et al. 2022). Therefore, we reported the pooled estimates based on random effects models, and we also conducted subgroup analyses to explain the sources of heterogeneity and reported prediction intervals, which would give an indication of the extent of between-study variation. Sensitivity analysis was also conducted. The odds ratio was calculated to measure the association between the outcome variable and the determinants. For each meta-analysis, publication bias was assessed graphically using a funnel plot and statistically by using Egger’s and Beggar’s tests (Egger et al. 1997).

In total, 9537 studies were retrieved from PubMed, Web of Science, CNKI, WanFang, and the VIP Database. Duplicates were removed and 8232 studies remained. After reviewing their titles and abstracts, 8111 publications were excluded. A total of 121 articles was read in full, of which 98 were excluded. Seventy studies were excluded due to content mismatches, 10 studies were excluded due to incorrect data and 18 studies were excluded due to time spent before the required year, 2015. Last, a meta-analysis was conducted on 23 studies that met the inclusion criteria (Fig. 1).

Fig. 1.  PRISMA flow diagram of the study selection process.

Table 1 summarises the study characteristics. Studies were conducted primarily in Eastern China (n = 14), followed by the Middle (n = 3) and the West (n = 4), with two studies based on national data. All included studies were cross-sectional surveys, except for one cohort study. The majority of these studies (n = 16) used random sampling, including multistage stratified random sampling, stratified random sampling, and multistage random sampling, whereas the remaining studies used convenience sampling (n = 7). The study participants were mostly community residents (n = 17), the remaining were patients seeking healthcare services (n = 4) and recurrent populations (n = 2). In terms of sample size, there were 302 to 24 116 participants with a total of 59 855. The willingness rate of the first visit to primary healthcare services ranged from 8.33 to 95.50%. In terms of research quality, the scores ranged from 4 to 10; nine studies were rated low, 11 studies were rated medium and three studies were rated high. The Supplementary material S2 contains a detailed breakdown of each study’s quality assessment.

Table 1.  Study characteristics included in the meta-analysis.

Of the 23 studies included in this systematic review, as indicated in the forest plot (Fig. 2), the pooled estimate of the first visit to PHC services in China was 56% (95% CI: 47–65). We identified a high and significant heterogeneity between studies (I² = 99.8%), indicating great variability in willingness across studies. Publication bias was assessed using visual inspection of funnel plots (Fig. 3) followed by the Begg’s and Egger’s tests indicating no significant bias (P = 0.224).

Fig. 2.  Forest plot of the pooled willingness rate of the first visit to PHC services.

Fig. 3.  Funnel plot of publication bias.

To identify the sources of heterogeneity, we conducted a subgroup analysis based on region, age, gender, medical coverage, educational level, per capita monthly income, and chronic disease history (Table 2). Because the confidence intervals overlap considerably, we cannot conclude that a statistical difference exists between most of the subgroup analyses. For chronic diseases, there is only a small overlap in confidence intervals between those with chronic diseases and those without chronic diseases; the willingness rate of the first visit to PHC services was 60% (95% CI: 50–70) among residents with chronic diseases and 47% (95% CI: 34–61) among residents without chronic diseases. Therefore, chronic diseases may be one source of heterogeneity. Supplementary material S3 presents the sensitivity analysis. According to the analysis, no influential studies were found, so all of the studies were included in the final analysis.

Table 2.  Subgroup analysis of the willingness rate of the first visit to PHC services.

The analysis of associated factors of first visit rates to PHC services included a total of 13 studies. Several significant factors were identified with a pooled odds ratio that ranged from 1.39 to 10.28, including fair self-reported health status, high understanding of service content, good service attitude, solid expertise and advanced diagnostic methods, and a good medical environment. In detail, residents who felt well about their health were 1.39-fold more likely to first utilise PHC services in comparison to those who felt poorly about their health (OR: 1.39, 95% CI: 1.13–1.70) (Fig. 4a). The understanding of service content was statistically associated with the use of PHC first, when compared to those without knowledge of services (OR: 3.33, 95% CI: 1.13, 9.83) (Fig. 4b). In addition, the first utilisation of PHC services was statistically associated with faculty members who had a good service attitude (OR: 10.28, 95% CI: 3.57–29.62) (Fig. 4c). The extent of solid expertise and advanced diagnostic methods was associated with the occurrence of the first use of PHC services (OR: 2.36, 95%CI: 1.64–3.88) (Fig. 4d). Facilities with a good medical environment were 2.53-fold more likely to attract customers as compared with those with a poor visiting environment (OR: 2.53, 95% CI: 2.20–2.91) (Fig. 4e).

Fig. 4.  Forest plot showing the pooled odds ratio of the associations between first visit rates to PHC service willingness and its determinants: (a) self-reported health status, (b) understanding of service content, (c) service attitude, (d) medical technology, and (e) medical environment.

In this meta-analysis, we extensively reviewed studies analysing the willingness rate of the first visit to PHC services by Chinese residents and the associated factors. The combined estimate from 23 studies was 56% (95% CI: 47–65). This finding was still far behind the 70% recommended by the Chinese government and also much lower when compared with Brazil, where 76% of the population was dependent on PHC services (Bastos et al. 2017), indicating the goal of ‘minor illnesses treated in the community and serious illness treated in hospital’ is not being fully realised (Yang et al. 2014). Residents with chronic disease histories were more likely to request PHC services on their first visit. It may be due to the fact that they require long-term medication, medicaid reimbursements are high for PHC facilities, and those facilities are close to their residences, making it more convenient for them to receive care (Zhang et al. 2015; Song et al. 2019). This trend is consistent with previous reports from China (Zhang et al. 2021) and Albania (Gabrani et al. 2020).

Among the associated factors, we found that residents with good self-reported health status are more likely to seek out PHC services first, whereas residents with poor health status are more likely to bypass them. This might be due to a popular belief that higher-tier hospitals are of higher quality, and those with poor physical condition are concerned that they will not be able to obtain high-quality services (Babiarz et al. 2012), which is consistent with the findings of a qualitative study conducted in Zhejiang, China (Wu et al. 2017). A promotion campaign targeting residents of poorer health, for example, promising timely referral to secondary or tertiary hospitals, may be effective in encouraging the first use of PHC services (Liu et al. 2018). Furthermore, we found that residents who had a high understanding of service content were more likely to use PHC services for the first time, indicating that insufficient publicising and inadequate services may prevent residents from using PHC services on their first visit (Onyeneho et al. 2016). The government should evaluate the content and scope of the service and increase publicity in accordance with the specific needs of different populations (Huang et al. 2019).

A good medical environment appears to positively influence the first utilisation of PHC services, which accords with the findings of a study carried out in Europe (Gabrani et al. 2020), which revealed that inadequate resources, defective infrastructure, and insufficient supporting measures restrict the first use of PHC services. It is necessary to increase the government’s financial support in order to improve people’s perception of the PHC system (Onyeneho et al. 2016). In the study, patients who experience good service are more likely to go to the PHC facilities for the first time. The most recent evidence (Hu et al. 2022) suggests that better patient experiences are associated with a lower burden of treatment, so it is necessary to create a more welcoming space in health facilities, with culturally sensitive and friendly health workers to improve perceptions of the primary healthcare system. Considering that general practitioners earn less than one-third of the wages of clinicians in large hospitals, an increase in their income will likely increase their enthusiasm for their work (Zhou et al. 2014). Further, solid expertise and advanced diagnostic methods were considered important factors in determining willingness to accept PHC services first. The training standards for general practitioners are low in China and their skills and abilities are limited, resulting in mistrust among residents (Wang et al. 2018). A study conducted in Tanzania (Saronga et al. 2014) emphasised the importance of improving medical quality. The provision of education and training interventions in PHC settings, as well as ongoing medical technology innovation, should be considered priorities for meeting residents’ health needs (Grill et al. 2016).

There are some limitations to this study. Due to time constraints, we did not conduct a research protocol. Additionally, the cross-sectional design of this study can only explain correlations, limiting its ability to identify causal relationships between influencing factors and outcome variables. The third problem with our study is that it addressed demand-side factors only. Supply side factors, which might influence residents’ choices, were not taken into account. Furthermore, the existing analysis does not adequately explain what caused the heterogeneity; therefore, a more comprehensive analysis should be undertaken in the future. Or a large sample multicenter study should be conducted to explore the willingness rate and influencing factors.

In this study, the pooled willingness rate of the first visit to PHC services was 56% in China. Positive self-reported health status, knowledge of the content of services, good medical environment, good service attitude, solid expertise and advanced diagnostic methods all contributed to a higher willingness rate of the first visit to PHC services. Therefore, the government should formulate strategies to facilitate the implementation of the policy, including expanding service packages, publicising the policy completely, increasing government financial subsidies, providing education and training interventions, and creating a more responsive environment to promote the sustainability of PHC services and accelerate progress towards universal health care.

Supplementary material is available online.

Data sharing is not applicable as no new data were generated or analysed during this study.

The authors declare that they have no conflicts of interest.

This research was supported by the International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 51861125101).