An innovative medical consultation model in mainland China: Acceptance and perceptions

Xiao Ping Xu (Department of Medical Service, Shenzhen Hospital, The University of Hong Kong, Shenzhen, China) (ISCTE-Instituto Universitario de Lisboa, Lisbon, Portugal)
Dong Ge Ke (Department of Medical Service, Shenzhen Hospital, The University of Hong Kong, Shenzhen, China)
Dong Ning Deng (The University of Hong Kong, Shenzhen, China)
Shannon H. Houser (Department of Health Services Administration, University of Alabama at Birmingham, Alabama, USA)
Xiao Ning Li (Shenzhen Hospital, The University of Hong Kong, Shenzhen, China)
Qing Wang (Shenzhen Hospital, The University of Hong Kong, Shenzhen, China)
Ng Chui Shan (Shenzhen Hospital, The University of Hong Kong, Shenzhen, China)

International Journal of Health Care Quality Assurance

ISSN: 0952-6862

Article publication date: 12 August 2019



The purposes of this paper are two-fold: first, to introduce a new concept of primary care consultation system at a mainland Chinese hospital in response to healthcare reform; and second, to explore the factors associated with change resistance and acceptance from both patients’ and medical staff’s perspectives.


A survey design study, with two questionnaires developed and distributed to patients and medical staff. Convenience and stratified random sampling methods were applied to patient and medical staff samples.


A 5-dimension, 21-item patient questionnaire and a 4-dimension, 16-item staff questionnaire were identified and confirmed, with 1020 patients (91.07 percent) and 202 staff (90.18 percent) as effective survey participants. The results revealed that patient resistance mainly stems from a lack of personal experiences with visiting general practice (GP) and being educated or having lived overseas; while staff resistance came from occupation, education, GP training certificate, and knowledge and experience with specialists. Living in overseas and knowledge of GP concepts, gender and education are associated with resistance of accepting the new practice model for both patients and staff.


There are few Chinese studies on process reengineering in the medical sector; this is the first study to adopt this medical consultation model and change in patients’ consultation culture in Mainland China. Applying organizational change and process reengineering theories to medical and healthcare services not only extends and expands hospital management theory but also allows investigation of modern hospital management practice. The experience from this study can serve as a reference to promote this new consultation model in Chinese healthcare reform.



Xu, X.P., Ke, D.G., Deng, D.N., Houser, S.H., Li, X.N., Wang, Q. and Shan, N.C. (2019), "An innovative medical consultation model in mainland China: Acceptance and perceptions", International Journal of Health Care Quality Assurance, Vol. 32 No. 7, pp. 1055-1071.



Emerald Publishing Limited

Copyright © 2019, Xiao Ping Xu, Dong Ge Ke, Dong Ning Deng, Shannon H. Houser, Xiao Ning Li, Qing Wang and Ng Chui Shan


Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at


Organizational change is a constant in today’s healthcare management, which involves a range of activities that are conducted to enhance a company’s efficiency and effectiveness, allowing it to change from its current situation to a future ideal. These activities mainly include reform, process reengineering and innovation (Hill and Jones, 1998). Organizational change is conducted to improve the overall performance of an organization and is based on process reengineering. Business Process Reengineering (BPR) is a specific organizational change model that includes redesign and a series of relevant reforms (Hammer and Champy, 2004). The “three-step-evolution” organizational change theory (Lewin, 1947) proposes unfreezing, changing and refreezing as the three main processes in organizational change. Given advances in relevant theories, BPR is appropriate not only for enterprises but also for hospital systems. For example, in the USA, process reengineering was applied by Eitel DR in their Emergency Department to divert patient crowds during peak hours; they succeeded in reducing the waiting time while maximizing patient satisfaction (Eitel et al., 2010).

Although healthcare is a business industry, some of healthcare’s special characteristics, such as trying to serve the entire population, BPR in healthcare might differ from that in other service industries. For example, as healthcare is closely connected to the population’s health and life quality, its main concern is service quality and cost effectiveness, even though it recognizes that profit is also necessary in order to exist. Conflicts may arise in organization management between these two goals. Moreover, healthcare organizations are typical organizations and include “professional bureaucracies” (Mintzberg, 1983). Hierarchical structures in healthcare, bounded by various hierarchical levels and different professions, might make agreement and cooperation difficult and change harder to implement (Rehder, 2012; Ham et al., 2003). People’s perceptions and acceptances of a new organization change vary and usually there is reluctance at the beginning. Adoption of a new concept in healthcare organizations requires a long period of time, especially when the change goes against a deeply embedded traditional practice.

Need for reform

There are very few studies in China focusing on BPR as applied to the medical sector. Thus, many issues remain to be further studied and modified. The development of primary care and general practice (GP) in Mainland China are lagging. The Chinese Government began to work on this area in the early 2000s (Hou, 2009). Major efforts have been directed to GP training and system development, yet it is still hard to build public trust and switch the culture from favoring specialist services to selecting and starting with GP (Li, 2016).

Traditional health seeking processes in Mainland Chinese hospitals allows patients to choose which hospital to visit, and which medical department to register within. For example, a patient with chronic chest pain may register for the cardiology department and to see a cardiologist at his/her initial hospital visit. Historic practice is that most patients seek medical care by walking in to self-selected hospital without an appointment, because patient appointment systems are a new concept, and only recently being adopted by a very few hospitals in China. Consequently, it produced a large volume of patients at the waiting room at the same time, not only results in unpredicted length of waiting time for patients, but also increased unpredicted volume of services for providers. Furthermore, because patients are visiting hospitals or select doctors at random, medical records created at Hospital-A may not be used at Hospital B, thus it is lacking in continuity and coordinated care since no patient information shared cross continuum of the treatments among hospitals. In addition, almost no patients in the public hospitals have a primary care physician to whom the patient can return for follow-up consistently over time. This traditional medical practice approach created isolated and episodic medical care, inconvenient to patients, involving large quantities of time and specialist resources. It also lacks the quality and continuity of care desired. From a hospital management and provider standpoint, perhaps the largest component of this system is the waste that occurs when the patient has selected the wrong department and specialist relevant to the patients medically determined diagnosis requiring a further referral to GP or another specialty department.

Conceptual framework and implementation of the new consultation model

GP is not new to healthcare systems in many developed countries, such as Scandinavian counties, Germany, Greece, Italy, the UK and the USA (van de Ven, 1996; Marshall, 1999). GP is said to focus more on health, psychological condition and humanity, instead of merely on disease, biology and technological aspects of health (Li, 2016). The new consultation model presented in this study, “Primary Care by General Practitioners and Secondary Care by Specialists,” aims to introduce GP services into the Chinese healthcare system. Similar to other GP models, it mandates GP service for the initial diagnosis, and the general practitioner has sole responsibility for deciding to transfer the patient for specialist service in the hospital.

The University of Hong Kong-Shenzhen Hospital (HKU-SZH), with a full capacity of 2,000 beds, 8,000–10,000 outpatient visits daily, officially established its operation in July 2012 in Shenzhen, China. The hospital is a public hospital which Shenzhen municipal government constructed and provided funding for the facility. It is intended to develop international medical standards and lead medical reform in mainland China. Medical consultation process reengineering is one of the reforms that the hospital initiated since the opening of the facility. The reengineering aims to shift from a disease-centered biomedical model dominated by specialist medical services to a bio-psycho-social medical model dominated by GP (or in Western terms, primary care,) medical services. To gain admission to the hospital and outpatient clinics, an appointment is required. Walk-ins must begin with GP and keep subsequent care by appointments. The implementation of the new consultation model in HKU-SZH could be seen as a first step in China’s healthcare system reform, as it was the first time in Mainland China that this medical consultation model and culture aspect was implemented in a hospital.

Another characteristic of this process is the need to pay a flat fee (or bundled payment) at time of admission for the GP services which is inclusive of payment for many ancillary services. Because the quid pro quo for these fees is not familiar or customary in most Chinese hospitals, it meets with resistance and requires much education and explanation.

The three main types of BPR are radical top-down BPR, participative BPR and BPR driven by enterprise resource planning (ERP) systems (Huq and Martin, 2006). It is said that radical top-down BPR negatively affects staff morale and is more likely to fail (Huq and Martin, 2006). To avoid drastic changes and ensure stability, HKU-SZH chose participative BPR (Huq and Martin, 2006) as a step-by-step organizational change that engages most stakeholders in the organization. Since at the time of the implementation of BPR, HKU-SZH was still a new hospital with fewer than three years in operation, its electronic information system was not yet well developed. Thus, HKU-SZH did not conduct ERP-driven BPR. The implementation of BPR requires the support of senior leaders as well as effort from all levels and all professions (Huq and Martin, 2006). Therefore, the process improvement team in charge of the change process should involve members from multiple levels and with varied professional backgrounds. The process improvement team at HKU-SZH included leaders (directors and vice directors in charge of medical affairs), project teams (heads of medical, nursing, public relations and other participating departments) and the head, professors and associate professors of the GP department. The implementation of the Reengineered Consultation Process followed Lewin’s (1947) “three-step-evolution” organizational change process of The Unfreezing Stage, The Changing Stage and The Refreezing Stage.

Step I. The unfreezing stage

This stage involved preparation for the consultation process. Several major activities included: establishing a GP department in the hospital as a “gate-keeper.” After hospital leaders and department heads reached consensus, the GP consultation model was introduced from Hong Kong to HKU-SZH. For the initial diagnosis, it became mandatory for patients to visit the GP department; if deemed necessary, the GP would arrange transfer to a specialist service; communicating the plan to all hospital departments. After the communication initiated by the hospital was transmitted with the Shenzhen government and the health authorities, the process transformation plan obtained support from all departments; and using public media to publicize the reform. This drastic change generated resistance and misperception by local residents (patients) and hospital employees. HKU-SZH tried to reduce resistance to the reform by promoting the model in all types of media, including television, newspapers and community posters.

Step II. The changing stage

This stage involved implementation of the proposed plan. Several steps are included in this stage: The director, professors and associate professors of the Department of Family Medicine and Primary Care of the Faculty of Medicine of the University of Hong Kong provided training sessions on GP to hospital employees and managers to help shift their attitudes and behaviors to accept the new consultation model; through mock demonstrations of the new consultation process, deficiencies in the process were summarized and corrected; training sessions on teamwork were provided to create a tolerant climate, enhance employees’ sense of security, reduce their psychological resistance to the reform and improve their confidence in it; and as an immediate task, general practitioners, nurses and other staff in the GP department were trained in their specialty related to the new consultation model at the GP training base in Hong Kong. The director, professors and associate professors of the Department of Family Medicine and Primary Care of the Faculty of Medicine from the University of Hong Kong conducted training.

Step III. The refreezing stage

This stage involves assessment of current status and issues related to the change model. After the consultation model was adopted for one and a half years, it was assessed to identify support and resistance to the reform and to propose suggestions and measures for further transformation. With the necessary reinforcement measures, the new process and related behaviors were resolved. The organization reform entered a stable stage and, hopefully, the new model is a part of the hospital culture.

Current issues

This study is focused on illustrating Step III, The Refreezing Stage – the assessment step of the BPR process. After the new medical consultation model had been implemented for a year and a half, an evaluation of the reengineering process revealed signs of resistance to the organizational change. The number of outpatient visits to GPs showed no remarkable increase, while the number of outpatient visits to specialists and total outpatient visits trended toward an increase (Figure 1). Therefore, the increase in the total number of outpatients mostly reflected an increase in the number of outpatient visits to specialists. This shows that the implementation of the new model did not attract more people to HKU-SZH GP service for an initial diagnosis. Instead, many chose to consult specialists for their initial diagnosis at other hospitals and then came to HKU-SZH for specialist services.

Resistance to organizational change manifests as a total or partial failure of the attempt to change the organization’s “technology, production, methods, management practices, or compensation systems” (Oreg, 2006). Szabla (2007) indicates that resistance is a combination of “cognitive, emotional and intentional reactions.”

The purpose of this case study was two-fold. First, as discussed above, to introduce a new concept of patient consultation system at a mainland Chinese hospital. Second, to examine the factors associated with resistance and acceptance of the newly established consultation model from both patients’ and medical staff’s perspectives.

The first significance of this study is that by assessing the current status of the BPR, top management at the hospital can know what areas need more attention. In addition, as a large public hospital, HKU-SZH can serve as a reference and help popularize the new consultation culture in China through this empirical case study. We hope that this study will promote further improvement of hospital services and that based on this experience, process reengineering can be expanded to similar medical service processes. Meanwhile, we also hope to perform further studies with relevant colleagues in this field as well as to conduct longitudinal studies to assess the implementation of our suggestions and their success.


Participants selection and procedures

Patients and medical staff were recruited from HKU-SZH to complete two separate self-designed questionnaires. Patient eligibility included: being 16 years of age or older; making outpatient visits for GP or specialty care (excludes emergencies); and being in stable health condition and willing to participate in the survey. Medical staff eligibility was determined by: doctors, nurses, medical technicians and other clinical staff (excludes administrative staff); and employed by the hospital for at least six months (Table I).

For the purpose of determining effective measurement items, a pilot survey was conducted. The sample size for the pilot survey was 120 patients and 55 medical staff. During the pilot surveys, feedback on the questionnaires was collected from participants as well as from experts in statistics, GP and management backgrounds in order to direct revision. The sample size for the final surveys included 1,200 patients and 240 medical staff.

The patient survey was distributed at outpatient departments during working hours, from Monday to Friday, for two weeks. Specially trained volunteers were assigned to assist patients with reading or comprehension issues. A convenience sampling method was applied to the patient sample selection. The pharmacy and ultrasound areas were the primary locations for patient sampling locations, since most of patients in these areas had often just completed consultation with different clinical departments and were willing to take the survey. In addition, to balance the sample size across departments, patients at waiting room areas from different outpatient services were also recruited.

The medical staff survey was distributed to the selected medical departments. The stratified random sampling method was conducted on the staff sample. The sample size within each occupation was arranged according to its proportion of staff within HKU-SZH. In particular, staff were primarily from Mainland China and Hong Kong, so the sampling considered the balance between these two areas to reduce perspective bias caused by culture differences. Both final surveys were conducted from April to May, 2014.

Survey development and measures

Two questionnaires were designed, one for patients and another for medical staff, to assess their knowledge and acceptance of the new consultation model. The perception of respondents was measured from 1 (strongly disagree) to 7 (strongly agree) on Likert scales (Likert, 1952). The questionnaires included demographic variables and items related to: knowledge of bundled-payments for visiting a GP, and for visiting a specialist; the concept of GP (or primary care) consultation model; appointment system and patient portal; patient satisfaction for service (for patient only); skill set for GP (for medical staff only).

Because the concept of GP (or primary care) came from western countries, we hypothesized that there was an association between people who have been educated or lived in foreign countries, who may have been exposed to or understand better the GP concept. We added variables of overseas experience or education into the questionnaires.

Statistical methods

The reliability of the questionnaire was assessed using Cronbach’s α coefficient. A coefficient >0.8 shows very good reliability (Cronbach, 1951). In terms of validity, an exploratory factor analysis with principle component analysis and varimax rotation was conducted. Only factors with common regression coefficients with an eigenvalue ⩾1 were chosen as primary factors. Factors were obtained by varimax rotation. The number of factors was determined by a scree plot and a factor loading matrix. Factors with a loading <0.4 were not considered.

In the process of analyzing results, the first component ratio was adopted to describe the general information for patients and medical staff, such as age, gender, degree and title. Second, one-way ANOVA, Kruskal–Wallis (to test homogeneity of variances), nonparametric and Bonferroni tests were used to analyze the relationship between the general information for the samples and factors in questionnaires. The general attitude for each factor was classified as “agree,” “neutral” and “disagree,” and these were determined by the total scoring of items within each factor.

To speculate as to the factors underlying resistance to the new consultation model, this study compares the means to identify individual characteristics that present lower acceptance scores in the consultation model factors.


Results for the questionnaires’ design and validation

The final analyses were based on 1,020 effective patient questionnaires (91.07 percent) and 202 effective staff questionnaires (90.18 percent). The KMO values (0.900 and 0.830, respectively) and Barlett’s test results (13,807.1 with probability 0.000 and 1,922.569 with probability 0.000 respectively) showed that the items in the two questionnaires had a significant level of correlation and were good for factor analysis. Through Scree Plot, a final version of the patient questionnaire (21 items) with five factors and of the medical staff questionnaire (16 items) with four factors were confirmed (Table II). Both questionnaires show good homogeneity reliability with total Cronbach’s α coefficients of 0.914 and 0.742, respectively (Tables III and IV).

The potential sources of patient acceptance of the new consultation model are mainly from having previous experiences with GP visits and having been overseas to live or to study.

Table V shows the patient participants’ demographics and average scores for each factor rated by the patients and classified by individual characteristics. In general, none of the patient participants showed a negative attitude (disagree) towards any of the five consultation model factors in the patient questionnaire. However, most of the patient participants showed an attitude between “Agree” and “Neutral” towards P-Factor1, P-Factor2 and P-Factor5.

Table VI shows a variance analysis for the influence of individual patient characteristics on each factor. There are eight individual characteristics that have at least one significant influence on the five consultation model factors in the patient questionnaire.

Table VII summarizes the individual patient characteristics that have a lower acceptance score in the consultation model factors. In detail, GP Visiting Experience has a significant impact on all five factors. Patients who have never experienced a GP visit have lower scores on all five factors. Overseas living experience significantly affects the P-Factor1, P-Factor2, P-Factor3 and P-Factor5. Patients without experience living oversees have lower acceptance scores. Overseas GP visiting experience significantly affects the P-Factor2, P-Factor3 and P-Factor5. Similarly, patients without such experience showed more negative attitudes. Moreover, Visiting GP or specialized clinic affects the P-Factor1 and P-Factor2, as patients visiting specialized clinics had lower acceptance scores. Last but not least, Female and Lower Education Level were associated with lower scores on P-Factor5 only; Patients without Overseas Study Experience have lower scores on P-Factor2 only; and Source of Medical Cost impacts P-Factor3, as those without Shenzhen medical insurance have lower acceptance scores.

To conclude, patients without experience of GP services (local or abroad) showed a lower acceptance of the consultation model factors. Patients who came for GP services showed a more positive attitude and were more willing to accept GP services. Other inherent or social characteristics, such as gender, educational level and medical payment method, might also be factors related to resistance in the patient’s acceptance of the new consultation model.

The potential sources of resistance to medical staff’s acceptance of the new consultation model mainly stem from occupation, education, GP training certificate and having specialist experience.

Table VIII shows the medical staff participants’ demographics and average scores for each factor rated by patients and classified by individual characteristics. Overall, no medical staff participant shows a negative attitude (Disagree) towards any of the four consultation model factors in the staff questionnaire.

Table IX presents a variance analysis of the influences of individual staff characteristics on each factor. In detail, except for the length of participation, all other individual characteristics of medical staff have at least one significant influence on the four consultation model factors in the medical staff questionnaire.

Table X summarizes the staff individual characteristics that have a lower acceptance score in the consultation model factors. First, of the above influential individual characteristics, Occupation shows a significant impact on all four factors. Staff other than doctors, nurses, pharmacists and lab technicians have lower scores for M-Factor1, M-Factor2 and M-Factor4. Lab technicians showed a less positive attitude towards M-Factor3. Moreover, Education Level, Specialist Working Experience and GP Training Certificate all show significant impacts on the M-Factor1, M-Factor2 and M-Factor3. Staff with education levels below college and without specialist work experience or a GP training certificate showed a more negative attitude on the above three factors.

Furthermore, other characteristics that show significant impacts on fewer factors are categorized into two main characteristics: inherent or acquired characteristics. First, Gender and Age are categorized as inherent characteristics, FEMALE staff and YOUNGER staff have a lower degree of acceptance of M-Factor2, M-Factor3 and M-Factor1, respectively. Second, postnatal characteristics can be divided into social position (department/job title) and experience (living/training/practicing/studying). For social position, those who scored lower are JUNIOR staff, with lower scores on M-Factor1, and staff from the GP department with lower scores on M-Factor1 and M-Factor3. For social experience, by and large, staff with NO overseas experience (living/training/practicing/studying) and NO relevant GP work experience showed a lower degree of acceptance. Such lack of overseas and practice experiences related to a low acceptance of GPR. In addition, M-Factor2 is graded lower by staff lacking GP work experience and an overseas bachelor’s degree, while M-Factor4 is graded lower by staff without overseas living experience.

In summary, different occupations show significantly different attitudes towards all four factors. Lab technicians and other occupations have lower acceptance than doctors, nurses and pharmacists. Staff with a lower educational level or without a general training certificate show less acceptance of the new model. Staff without specialist experience showed similarly lower acceptance of the new model. Gender, age and other different social positions and experiences have less impact but might also contribute to staff resistance to the new consultation model.

Overseas experiences, related consultation experiences, gender, and education are common potential sources of resistance in both patient’s and staff’s acceptance.

Last, the results from the patient and staff surveys reveal a common pattern in the factors affecting people’s acceptance of the new consultation model. In general, females or people with a lower educational level, no overseas experiences or no related consultation experiences showed lower acceptance.


Implications and suggestions

This study introduced a new consultation model of “Primary Care by General Practitioners and Secondary Care by Specialists” in China. Our study results indicated that participants’ acceptance level of the new consultation model was associated with their education level; gender; whether having overseas experience; whether having prior experience seeing a GP. In general, the study participants were more in favor of the traditional physician visit practice rather than adopting the new consultation model. Our findings suggested that process reengineering and innovation is a complicated, difficult, and multiple dimensional organizational change. Evaluating and managing resistance is part of an implementation strategy in change management (Trader-Leigh, 2002). According to Hultman (2003), people’s resistance behaviors are caused by mindset issues in which people’s personal facts (objective realities), beliefs (subjective assumptions, conclusions, and predictions) and values (conceptions about what is important in life) are the most important factors. When people process thoughts, they are more likely to consider their beliefs to be reality and overlook facts (Hultman, 2003). In terms of change management, when people’s beliefs in the benefits of old processes are stronger than those for new processes, and they take these beliefs as reality, they will consider the old ways of doing things to be more important and will resist change (Hultman, 2003). In this context, if managers want to make a change, they need to provide more facts to form a stronger evidence base for the benefit of the new processes.

Apart from people’s beliefs as being a deeper cause of resistance, our study also wonders if change management itself failed to reduce the resistance. As mentioned at the introduction, our study chose participative BPR to avoid the weaknesses of radical BPR. Nevertheless, participative BPR is said to have similar problems to radical BPR, such as negatively affecting staff’s levels of comfort, confidence, competence and control, particularly when leaders fail to provide enough retraining during the change management process (Davenport and Stoddard, 1994; Huq and Martin, 2006). Moreover, due to the limited organizational resources, HKU-SZH could not conduct an ERP-driven BPR, which the literature argues can overcome the weaknesses of the above two types (Davenport and Stoddard, 1994; Koch, 2001; Huq and Martin, 2006). Overall, apart from assessing resistance related to human factors, rethinking the BPR process is also important. However, since the latter is not the focus of this paper, future studies must explore this aspect.

We believe that to implement the new model effectively and efficiently, it is essential to have both patients and medical staff “buy in.” For patient population, several suggestions are drawn from the survey results. In general, we suggest that more attention should be given to promote GP knowledge and acceptance of the new model of “Referring patients to specialists only after consultation with general practitioners.” This is intended to be the new normal in Chinese health practice. Providing positive facts about the new model to influence beliefs and values, and generating more opportunities for people to experience GP service.

In detail, the following suggestions are proposed for the purpose of reducing patients’ resistance to the new model: improving appointment systems so that hospitals can better manage and plan their services, and also save waiting time for patients; Exploring innovative methods for medical charges and payments; and promoting the benefits of specialist team consultation through television, newspapers, magazines and other media. Establish “zero distance” to close the gaps between general practitioners and local residents by educating the public about GP and to expect it personally when entering the medical care setting. Some suggested approaches include: inviting foreign experts on GP from Canada, Australia, and USA, just to name a few to present and promote education materials on GP concepts and benefits to local communities in Shenzhen area; and to demonstrate case studies on how the GP works. The key purpose of these activities is to enhance the acceptance of GP concepts and understanding of the skill set of general practitioners. Strengthen information provision and the education of patients visiting specialists by showing promotional videos, distributing brochures and other forms of activities in specialist clinic waiting areas. Establish patient portal system, so the communication between patients and providers can be delivered through electronic or digital devices. Therefore, enable patients in different locations or remote areas to directly query clinical results from a networking platform.

In order to reduce medical staff resistance to the new consultation model, several suggestions were made: strengthening GP education for the medical staff – HKU-SZH is a new hospital and, according to the target, with full capacity, the total number of its medical staff will increase to 3,936 from the existing 1,200; these staff will come from all over China. Therefore, before the new medical staff begins to work, education about the GP model, the specialist team consultation pattern, innovative medical charges and other new measures should be conducted. In addition, consistent professional lectures on GP concepts and practice approach should also be held as continuous education materials at the hospital so that the medical staff can learn more and quickly about any new process reengineering ideas. Strengthening training for general practitioners. By using its collaboration platform with the University of Hong Kong, the hospital should send doctors from the general department to the Hong Kong GP Training Base for professional training to improve their technical skill level and self-confidence, thereafter to reduce the psychological barriers and resistance to the organizational change. Sending medical staff to visit the University of Hong Kong. The hospital should send medical technicians, pharmacists, nurses, and even administrative staff to the University of Hong Kong GP Training Base to gain real-world experience with the internationally well-known practice model with GP, and referral concepts. It is important to improve their knowledge and acceptance of the new practice model, and be the leading source of the medical reform for the general direction of development in the hospital, medical system and even the entire country.

Limitations of the study

The Hong Kong University-Shenzhen Hospital is a new hospital that has directly introduced the consultation model of “Transference to Specialized Departments after Consultation with General Practitioners” since it went into operation. Therefore, this study could not provide a comparative study between “before” and “after” outpatient workflow process reform. Second, the fact that the study is conducted in only one hospital hinders the possibility of generalizing the results. This may have also impacted the representativeness of the sample. In addition, we considered Lewin’s change management model to be the original and the most authoritative. However, since we adopted it in our study, we have noted that there are deficiencies and limitations in the model. We have subsequently identified a more complete model developed based on Lewin’s theory. Thus, the model we used in our study might affect the output of the BPR.

Future studies

Our findings suggested some areas that are worth future study. First, both the patient and medical staff participants are mostly female, which might show that females’ related experiences and opinions about the new consultation model are important for its further development. Thus, future relevant studies may focus more on this gender group to identify additional potential sources for acceptance to develop the new consultation model. Second, education factors might also be worthy of exploration. According to Schommer’s (1998) empirical study, people’s epistemological beliefs can be affected by education. In this context, educational experience might impact individuals’ attitude towards new social phenomenon. An example can be one of the results in this paper that less educated people showed lower acceptance of the new consultation model. Thus, one potential source of resistance to recognizing the new change lies in education. Third, our study also revealed that for a better GP experience, efforts should not only be made around the patient’s experience but should also include the medical staff’s experience with practicing the new concept. Further study can be conducted on how to improve patient visits and medical staff’s practice experiences with GP. In addition, an interesting finding in the paper is related to specialist consultations: those who have lower acceptance of the new model were medical staff with NO specialist work experience and patients WITH specialist visiting experience (Tables VII and X). More detailed surveys need to be conducted to explore how specialist experience may influence acceptance of the new consultation model. Last but not least, future studies may focus on assessing the process of implementing BPR in the hospital to uncover potential factors leading to the failure of BPR.


Actual Monthly Visits to HKU-SZH

Figure 1

Actual Monthly Visits to HKU-SZH

Participant inclusion criteria

Participants Category Criteria
Patients Age ⩾16
Consultation type Outpatients searching for general and special medical consultation (excludes emergencies)
Health condition In stable condition and willing to participate in this survey
Medical staff Occupation Doctors, nurses, medical technicians and other clinical staff (excludes administrative staff)
Employment length At least six months

Details of the consultation model factors in each questionnaire

Questionnaire Factor name Factor description Number of questions
Patient’s P-Factor1 General practice package consultation and treatment fee 5 questions
P-Factor2 Knowledge on general practice and primary care Model 6 questions
P-Factor3 Making appointment system and patient portal to receive clinical reports 3 questions
P-Factor4 Clinical service attitude 4 questions
P-Factor5 Consultation and treatment fee for specialist team 3 questions
Medical Staff’s M-Factor1 Consultation and treatment fee for specialist team 3 questions
M-Factor2 Package consultation and treatment fee for general practice and primary care model 6 questions
M-Factor3 Knowledge of general practice and skill sets 4 questions
M-Factor4 Making appointment system and using patient portal to receive clinical report 3 questions

Factor analysis of patients’ final questionnaire

Acceptance range
Factor Accumulated variance contribution rate Items included Cronbach’s α Agree Neutral Disagree
P-Factor1 16.314 13, 14, 11, 12, 15 0.867 25–35 20 5–15
P-Factor2 32.078 7, 6, 8, 5, 9, 10 0.876 30–42 24 6–18
P-Factor3 45.120 20, 19, 21 0.840 15–21 12 3–9
P-Factor4 58.146 1, 2, 4, 3 0.837 20–28 16 4–12
P-Factor5 69.731 17, 16, 18 0.912 15–21 12 3–9
Total 0.914

Factor analysis of medical staff final questionnaire

Factor Accumulated variance contribution rate Items included Cronbach’s α Agree Neutral Disagree
M-Factor1 36.274 9, 10, 8, 7, 6, 5 0.617 30–42 24 6–18
M-Factor2 18.629 12, 13, 14 0.663 15–21 12 3–9
M-Factor3 52.822 2, 3, 4, 1 0.656 20–28 16 4–12
M-Factor4 64.832 15, 16, 17 0.712 15–21 12 3–9
Total 0.742

Average scores for each factor by patient characteristics

Individual characteristics n Constituent ratio (%) P-Factor1 P-Factor2 P-Factor3 P-Factor4 P- Factor5
First 417 40.9 25.040 26.710 17.290 23.150 14.870
Established 603 59.1 24.610 26.730 17.340 23.520 14.930
General Clinic 251 24.6 25.770 29.000 17.600 23.380 15.350
Specialty Clinic 769 75.4 24.460 25.970 17.230 23.360 14.760
Female 613 60.1 24.470 26.430 17.330 23.240 14.570
Male 407 39.9 25.250 27.150 17.310 23.560 15.410
16–19 20 2.0 24.700 27.600 17.650 24.100 13.900
20–29 251 24.6 24.500 27.140 17.310 23.550 14.850
30–39 438 42.9 25.190 27.050 17.420 23.240 14.900
40–49 149 14.6 24.060 25.790 17.540 23.600 15.340
50–59 92 9.0 25.010 25.340 16.450 22.650 14.680
⩾60 70 6.9 24.510 26.660 17.310 23.730 14.790
Education level
Middle school or below 79 7.7 24.460 26.380 17.670 23.660 14.730
High school/technical secondary school degree 157 15.4 24.960 25.850 17.260 23.150 14.210
Junior college 227 22.4 24.720 26.900 17.400 23.330 14.520
Bachelor’s 421 41.2 24.890 26.970 17.260 23.330 15.120
Master’s 126 12.4 24.480 26.550 17.110 23.610 15.790
Doctoral 10 1.0 25.400 30.500 19.100 23.700 15.600
Overseas living experience
Yes 144 14.1 26.120 28.740 18.030 23.570 15.780
No 876 85.9 24.560 26.390 17.210 23.330 14.760
Overseas study experience
Yes 113 11.1 24.990 28.220 17.350 23.120 15.190
No 907 88.9 24.760 26.530 17.320 23.400 14.870
General clinic visit experience
Yes 423 41.5 26.380 28.760 17.950 23.670 15.590
No 597 58.5 23.650 25.270 16.880 23.160 14.420
Overseas general clinic visit experience
Yes 110 10.8 25.660 28.950 18.350 23.430 16.050
No 910 89.2 24.680 26.450 17.200 23.360 14.770
Source of patients
Shenzhen 804 78.8 24.920 26.800 17.360 23.450 14.930
Outside Shenzhen 67 6.6 25.070 27.580 17.370 23.160 14.520
Guangdong province except Shenzhen 126 12.4 23.830 25.830 16.940 23.260 14.820
Other province 23 2.3 24.430 26.350 18.000 21.780 15.520
Source of medical cost
Shenzhen medical insurance 682 66.9 25.000 26.740 17.260 23.430 14.940
Non-Shenzhen medical insurance 20 2.0 22.850 26.950 14.950 22.800 14.500
Commercial medical insurance 8 0.8 23.630 28.250 16.630 23.630 16.750
Private expense 310 30.4 24.450 26.620 17.630 23.250 14.810
Total questionnaire 1,020 100 24.780 26.720 17.320 23.370 14.900

Variance analysis of the factor influences of patient characteristics

Individual characteristics P-Factor1 P-Factor2 P-Factor3 P-Factor4 P-Factor5
First or return visit
F 1.108 0.002 0.051 2.665 0.06
Sig. 0.293 0.963 0.821 0.103 0.806
General or specialist clinic
F 1.887 0.006 3.621
Sig. 0.007* 0.000* 0.17 0.938 0.057
F 3.61 2.11 0.014 2.12 9.605
Sig. 0.058 0.147 0.907 0.146 0.002*
F 0.892 1.49 0.609
Sig. 0.486 0.544 0.443 0.19 0.693
F 0.17 0.759 0.388 2.643
Sig. 0.974 0.456 0.58 0.857 0.022*
Overseas living experience
F 7.398 11.617 6.303 0.561 7.146
Sig. 0.007* 0.001* 0.012* 0.454 0.008*
Overseas study experience
F 0.135 4.819 0.009 0.621 0.593
Sig. 0.713 0.028* 0.925 0.431 0.441
General clinic visit experience
F 5.336
Sig. 0.000* 0.000* 0.000* 0.021* 0.000*
Overseas general clinic visit experience
F 2.355 10.409 0.036 9.133
Sig. 0.125 0.001* 0.002* 0.85 0.003*
Source of patients
F 1.14 0.884 1.84 0.373
Sig. 0.332 0.449 0.749 0.138 0.773
Source of medical cost
F 1.246 0.13 3.751 0.377 0.631
Sig. 0.292 0.942 0.011* 0.769 0.595

Note: *Significant at p⩽0.05

Detailed influential individual patient characteristics associated with a lower acceptance score in consultation model factors

Influential individual characteristics P-Factor1 P-Factor2 P-Factor3 P-Factor4 P-Factor5
GP visiting experience None None None None None
Overseas living experience None None None / None
Overseas GP visiting experience / None None / None
Visiting GP or specialized clinic Specialist Specialist / / /
Gender / / / / Female
Education level / / / / Lower
Overseas study experience / None / / /
Source of medical cost / / Non-Shenzhen medical insurance / /

Note: /, means that the individual characteristic has no significant influence on the factor

Average scores for each factor rated by medical staff classified by individual characteristics

Individual characteristics n Constituent ratio (%) M-Factor1 M-Factor2 M-Factor3 M-Factor4
Female 150 74.3 15.780 31.220 18.780 16.000
Male 52 25.7 16.120 33.330 20.400 16.540
20–29 71 35.1 14.640 31.040 18.520 15.870
30–39 105 52.0 16.390 32.630 19.330 16.340
40–49 23 11.4 16.740 29.390 20.230 15.570
50–59 2 1.0 19.500 34.000 20.000 19.000
Over 60 1 0.5 21.000 42.000 28.000 21.000
Middle school or below 1 0.5 21.000 42.000 28.000 21.000
High school/technical secondary school 1 0.5 20.000 21.000 23.000 18.000
Junior college 31 15.3 13.720 29.700 18.120 15.630
Bachelor’s 108 53.5 16.020 31.580 18.710 15.830
Master’s 48 23.8 16.630 33.710 20.570 16.850
Doctoral 13 6.4 16.230 31.080 19.730 16.690
General 14 6.9 18.29 34.00 23.14 16.42
Specialist 122 60.4 16.52 31.93 18.86 16.40
Technician 42 20.8 13.27 29.77 18.57 14.90
Others 24 11.9 15.71 33.13 19.71 16.79
Doctors 68 33.7 17.340 33.310 20.680 16.980
Nurses 100 49.5 16.020 31.730 18.430 16.110
Pharmacists 8 4.0 15.130 29.500 19.380 15.630
Pathology 14 6.9 12.500 29.070 18.000 14.430
Others 12 5.9 10.690 28.000 18.420 13.920
Junior 98 48.5 14.990 31.440 18.600 16.110
Intermediate 69 34.2 16.630 32.450 19.640 16.260
Vice senior 22 10.9 17.730 32.480 19.760 15.230
Senior 8 4.0 15.380 27.380 19.800 17.500
Others 5 2.5 15.200 32.600 21.200 16.800
Half to a year 75 37.1 16.670 32.920 19.410 16.750
Over a year 127 62.9 15.370 31.220 19.100 15.830
GP experience
Y 12 5.9 17.750 35.450 23.420 17.070
N 190 94.1 15.750 31.530 18.930 16.080
Specialist experience
Y 75 37.1 16.960 33.000 20.560 16.570
N 127 62.9 15.220 31.040 18.390 15.880
Overseas training/learning experience
Y 30 14.9 17.230 32.630 20.790 17.270
N 172 85.1 15.630 31.610 18.920 15.940
Overseas living experience
Y 20 9.9 17.400 33.200 21.800 17.850
N 182 90.1 15.700 31.610 18.910 15.950
Overseas GP experience
Y 3 1.5 16.000 37.330 24.670 18.670
N 199 98.5 15.870 31.680 19.110 16.100
Bachelor’s degree
Domestic 133 96.7 15.860 31.610 19.050 16.070
Abroad 6 4.3 16.170 37.000 23.830 18.170
Master’s degree
Domestic 93 91.2 15.740 31.780 19.500 16.340
Abroad 9 8.8 16.330 33.560 23.440 17.330
GP training certificate
Y 13 6.4 18.770 35.330 22.450 17.140
N 189 93.6 15.670 31.520 18.970 16.070
Total questionnaire 202 100 15.870 31.770 19.200 16.140

Variance analysis of the medical staff influences of individual characteristics on each factor

Individual characteristics M-Factor1 M-Factor2 M-Factor3 M-Factor4
F 0.230 4.046 0.944
Sig. 0.632 0.046* 0.013* 0.332
F 2.836 2.836 2.304 1.180
Sig. 0.026* 0.026* 0.06 0.321
F 2.419 3.429 1.233
Sig. 0.037* 0.033* 0.005* 0.295
F 8.251 2.258 5.937 2.354
Sig. 0.000* 0.083 0.001* 0.073
F 10.006 2.874 4.051 3.271
Sig. 0.000* 0.024* 0.004* 0.013*
F 1.245 1.275 0.751
Sig. 0.03* 0.293 0.281 0.559
Length of employment in HKU-SZH
F 2.439 0.185
Sig. 0.083 0.120 0.668 0.189
GP experience
F 4.098 15.894 0.924
Sig. 0.121 0.044* 0.000* 0.338
Specialist experience
F 7.878 4.305 15.513
Sig. 0.005* 0.039* 0.000* 0.231
Overseas training/study experience
F 3.561 0.618 6.001 3.793
Sig. 0.061 0.433 0.015* 0.053
Overseas living experience
F 2.814 1.067 10.254 5.537
Sig. 0.095 0.303 0.002* 0.020*
Overseas practice experience
F 0.003 2.218 6.083 1.624
Sig. 0.957 0.138 0.014* 0.204
Bachelor’s degree
F 0.029 4.016 9.003 2.129
Sig. 0.864 0.046* 0.003* 0.146
Master’s degree
F 0.15 0.642 7.912 0.659
Sig. 0.699 0.425 0.006* 0.419
GP training certificate
F 9.982 1.167
Sig. 0.011* 0.039* 0.002* 0.281

Note: *Significant at p⩽0.05

Detailed influential individual medical staff characteristics that have lower acceptance score for consultation model factors

Influential individual characteristics M-Factor1 M-Factor2 M-Factor3 M-Factor4
Occupation Other Other Lab Technician Other
Education level College Technical secondary school or below College /
Specialist work experience None None None /
GP training certificate No No No /
Staff Dept. GP / GP /
Gender / Female Female /
Overseas living experience / / None None
GP working experience / None None /
Age Younger Younger / /
Bachelor’s degree (domestic/overseas) / Domestic Domestic /
Master’s degree (domestic/overseas) / / Domestic /
Overseas clinical practice experience / / None /
Overseas training/study experience / / None /
Title Junior / / /

Note: /, means that the individual characteristic has no significant influence on the factor


Cronbach, L.J. (1951), “Coefficient alpha and the internal structure of tests”, Psychometrika, Vol. 16 No. 3, pp. 297-334.

Davenport, T.H. and Stoddard, D.B. (1994), “Reengineering: business change of mythic proportions?”, Management Information Systems Quarterly, Vol. 18 No. 2, pp. 121-127.

Eitel, D.R., Rudkin, S.E., Malvehy, M.A., Killeen, J.P. and Pines, J.M. (2010), “Improving service quality by understanding emergency department flow: a White Paper and position statement prepared for the American Academy of Emergency Medicine”, Journal of Emergency Medicine, Vol. 38 No. 1, pp. 70-79.

Ham, C., Kipping, R. and McLeod, H. (2003), “Redesigning work processes in health care: lessons from the national health service”, The Milbank Quarterly, Vol. 81 No. 3, pp. 415-439.

Hammer, M. and Champy, J. (2004), Reengineering the Corporation: A Manifesto for Business Revolution, Harper Collins Publishers, New York, NY.

Hill, C.W.L. and Jones, G.R. (1998), Strategic Management: An Integrated Approach, 4th ed., Houghton Mifflin Company, Boston, MA.

Hou, T. (2009), “The Chinese primary care system: its evolution, challenges and legal aspects of reform”, CUREJ: College Undergraduate Research Electronic Journal, Vol. 96 No. 1, pp. 1-18.

Hultman, K.E. (2003), “Managing resistance to change”, in Bidgoli, H. (Ed.), Encyclopedia of Information Systems, Vol. 3, Academic Press, San Diego, CA, pp. 693-705.

Huq, Z. and Martin, T.N. (2006), “The recovery of BPR implementation through an ERP approach”, Business Process Management Journal, Vol. 12 No. 5, pp. 576-587.

Koch, C. (2001), “BPR and ERP: realizing a vision of process with IT”, Business Process Management Journal, Vol. 7 No. 3, pp. 258-265.

Lewin, K. (1947), “Frontiers in group dynamics: concept, method and reality in social equilibria and social change”, Human Relations, Vol. 1, pp. 5-41.

Li, D. (2016), “Training doctors for primary care in China: transformation of general practice education”, Journal of Family Medicine and Primary Care, Vol. 5 No. 1, pp. 1-2.

Likert, R.A. (1952), “A technique for the development of attitude scales”, Educational and Psychological Measurement, Vol. 12 No. 2, pp. 313-315.

Marshall, M.N. (1999), “How well do GPs and hospital consultants work together? A survey of the professional relationship”, Family Practice, Vol. 16 No. 1, pp. 33-38.

Mintzberg, H. (1983), Structure in Fives: Designing Effective Organizations, Prentice-Hall, Englewood Cliffs, NJ.

Oreg, S. (2006), “Personality, context, and resistance to organizational change”, European Journal of Work and Organizational Psychology, Vol. 15 No. 1, pp. 73-101.

Rehder, S. (2012), “Creating Sustainable Process Management in Healthcare”, Unpublished master’s thesis, Chalmers University of Technology, Goteborg.

Schommer, M. (1998), “The influence of age and education on epistemological beliefs”, British Journal of Educational Psychology, Vol. 68 No. 68, pp. 551-562.

Szabla, D.B. (2007), “A multidimensional view of resistance to organizational change: exploring cognitive, emotional, and intentional responses to planned change across perceived change leadership strategies”, Human Resource Development Quarterly, Vol. 18 No. 4, pp. 525-558.

Trader-Leigh, K.E. (2002), “Case study: identifying resistance in managing change”, Journal of Organizational Change Management, Vol. 15 No. 2, pp. 138-155.

van de Ven, W. (1996), “Market-oriented health care reforms: trends and future options”, Social Science and Medicine, Vol. 43 No. 5, pp. 655-666.

Corresponding author

Xiao Ping Xu can be contacted at: