Dental Patients’ Loyalty and Experiences with Staff/Systems in a Tertiary Hospital

Abstract

Objectives

This study examines relationships between outpatients' experience with medical staff, hospital system construction, and patient loyalty, exploring how enhancing experience boosts loyalty. 

Methods

A cross-sectional study via in person interviews with 288 outpatients at a Xi'an tertiary dental hospital by simple random sampling. Questionnaires included experience (staff, system), loyalty, demographics, and satisfaction. Structural equation modeling analyzed latent/observed variable relationships, adjusting for demographics. 

Results

61.5% were female, 50.7% were aged 30-60 years old, 92.4% participants satisfied with the oral health services. System construction strongly affected staff experience (β = 0.93). Both system (β = 0.72) and staff experience (β = 0.78) influenced loyalty. Loyalty and satisfaction had reciprocal links (β = 0.56/β = 0.55). 

Conclusions

This study provides a framework for understanding dental patient loyalty through structural equation modelling to guide similar institutions and broader healthcare settings. Future research, should include larger cohort and explore mediating/moderating factors.

Clinical Significance.

Structural equation modelling helps quantify key pathways, overcoming prior limitations. Identifies system construction as a primary driver, offering actionable strategies for resource allocation and service quality in tertiary dental settings.

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Introduction

Within the Chinese healthcare system, patients are permitted a high degree of autonomy in selecting their healthcare provider, a privilege that is particularly evident in the field of dentistry, which is isolated and separated from the mainstream health-care system.1, 2, 3 As dental problems are for the most part not life-threatening, there is not much information of healthcare reforms focusing on dentistry.⁴ While with the rapid economic growth⁵ and aging of China, providing sufficient dental care is an emerging challenge.⁶

In the field of medicine, healthcare providers and patients are the key stakeholders.⁷ As providers begin to realize the potential of uploading their capabilities to increase the rate of successful treatment, patients are becoming an important stakeholder in the choice of hospital, especially those who have priority oral healthcare needs.⁸ There is widespread recognition of the importance of evaluating services from consumer perspectives.⁹ It is impossible for all dental care to be carried out at the first visit, and loyalty is considered to involve maintaining the patient's loyalty for as long as possible.¹⁰

People and dental professionals hold varying views on oral health status. Using tooth wear as an illustration, dentists are unable to accurately capture patient-reported outcomes (PROs) and patient-reported outcome measures.¹¹ In dental clinics, dentists have a crucial role to play in boosting patient loyalty.¹² Hamasaki and Hagihara¹³ got the conclusion that improve the quantity and quality of the dentists' explanations of treatment may promote regular dental visits, which is consistent with Goetz et al¹⁴ study that patient loyalty was strongly associated with hospitals having more physician's assistants in the practice. Szabó et al¹⁵ noted that a personal patient-dentist relationship serves as a key factor in enhancing loyalty and suggested that local factors such as local context generally not reported might be at play. For private hospitals,¹⁶ nursing care experience played a mediating role between patient loyalty and surgical medical science. In public hospitals, the ethical and professional behavior of radiographers plays a vital role in the overall patient experience.¹⁷ Tarakji et al¹⁸ findings are interesting that dentists with relatively high knowledge and less experience performed better among patients.

The development of stomatology is refined, and there are many outpatient specialties in the tertiary stomatological hospital, which affects the patient's experience. Cancer and its treatments can significantly affect oral health.¹⁹ From cancer patients perspective, the complicated procedures increase the administrative, psychological, and financial challenges associated with cancer treatment.²⁰ For disabilities, processes like extended appointment durations enhance dental care.²¹ An artificial intelligence-based solution for automated dental inspections and charting, which serves as a method of documenting findings, has the potential to decrease clinical time and expenses while enhancing patient experiences and outcomes.²² In orthodontic treatment for adults, various treatment techniques can influence the medical experience of the patient. In contrast to traditional orthodontic methods, implant-supported mini-screw perforation serves as an innovative and efficient auxiliary technique that can significantly enhance the patient’s experience during clinical practice.²³ A better dental resin composite will improve the standard of care and the experience for patients.²⁴

The objectives of this study aim to examine the relationship between patients' interactions with medical personnel, the structure of the healthcare system, and patient loyalty.

Methods

Study process

This analysis offers a quantitative examination of a face-to-face interviewer survey conducted at a tertiary dental hospital in Xi’an, located in Shaanxi Province, northwest China. Patients are required to access medical services through the registration system. Possible participants were evaluated using the registration system to verify they were at least 18 years old, and the recruitment was facilitated by the chief physician of the department, with informed consent forms completed simultaneously. Participants were recruited using simple random sampling between July and October 2024. The recruitment process was executed by trained nurses, facilitated by the chief physician of the relevant department, and participants were prescreened via the hospital’s registration system to confirm basic eligibility. Eligibility Requirement: individuals must be patients of this hospital who have utilized the registration system to access medical services and be at least 18 years of age (confirmed through the hospital's registration system). Exclusion Criteria: inability to participate effectively in the interview due to cognitive impairment, refusal to provide a signed informed consent form, or failure to meet the inclusion criteria in full. Responses that are incomplete in the questionnaires will be excluded from the final analysis. The qualitative results adhere to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

The sample size is calculated using the formula n = $\frac{2\times \left(\mathrm{Z}\alpha /2+\mathrm{Z}\beta \right)2\times \sigma 2}{\delta 2}$. The initial sample size is estimated to be approximately 251; considering a 10% incomplete-response rate which is common in dental face-to-face surveys, the adjusted final sample size is about 277. Data utilized for this analysis was sourced from valid responses collected for all questions. The questionnaire comprised 3 dimensions, which included patients' experiences with medical personnel, system infrastructure, loyalty, and demographic details (such as sex, age, medical personnel, medical insurance, and educational level) alongside their satisfaction regarding the dental visit.

The measurement of patient loyalty was based on 3 items adapted from validated scales in existing healthcare service research,^25,26 focusing on patients’ intention to revisit and recommend the service; these items employed a 5-point Likert scale with anchors from 1 (“Very unlikely”) to 5 (“Very likely”). For patient experience, a total of 9 scenario-specific items were developed based on the healthcare service quality model, covering two core dimensions: interpersonal experiences with medical staff27, 28, 29 and functional experiences with hospital system development^30,31; these items used a 5-point Likert scale ranging from 1 (“Strongly disagree”) to 5 (“Strongly agree”). With full wording provided in Table 1. Patient satisfaction was assessed using the questionnaire item: “Please select your satisfaction level based on your actual experience during the medical visit.” Responses were measured on a 5-point Likert scale, with anchors ranging from 1 (“Strongly dissatisfied”) to 5 (“Strongly satisfied”), we reclassified it into 3 categories: “Not satisfied”, “Normal” and “Satisfied”. To ensure the quality of the question design, a pretest was conducted with 30 dental patients to assess item clarity and relevance, followed by minor revisions to ambiguous wording based on feedback, thereby guaranteeing the questions were easily understandable and capable of effectively capturing the intended constructs.

Table 1.

Patients experience with medical staff and discipline construction.

Latent variables	Observed variables
Patients experience with medical staff	1 The health care providers here are able to accurately grasp my needs.
	2 The health care workers here have advanced treatment concepts and high aesthetic standards
	3 The medical staff here have an outstanding professionalism
	4 Healthcare workers here have good diagnostic and treatment effects.
	5 The medical and nursing staff here strictly follow the standardized procedures to carry out diagnosis and treatment.
	6 The medical and nursing staff here have in-depth detailed and oral research problems, and have many special treatment specialties.
	7 The medical staff here can communicate my condition and treatment plan in a language that l can understand.
	8 The staff here will pay attention to my emotions and attitude when communicating with me, and try to reduce my pain and fear, and provide me with humanistic care.
	9 The staff here remember my personal situation and think about things from my point of view.
Patients experience with system construction	10 The process design of the treatment process is reasonable, the effective treatment time is sufficient, and the treatment efficiency is high.
	11 Patient health information records have been effectively applied. In any diagnosis and treatment link or hospital area, I can obtain a consistent personalized service experience.
	12 The setting of the diagnosis and treatment process is reasonable, which can not only guarantee the service, not over-marketing, but also will not miss the key needs.
	13 Information system construction is complete, I can easily obtain medical services without special study.
	14 My needs and feedback can be timely response and effective solution.
	15 The hospital's information system can help me learn medical knowledge and carry out customized health management.
	16 The hospital continues to introduce new technologies and high-end equipment, with a comfortable and clean treatment environment.
	17 The hospital can solve the whole cycle and whole oral health problems in one stop.
	18 The hospital continuously adjusts and optimizes the reception capacity and waiting environment, and can still maintain an orderly treatment environment during the peak period.
Loyalty	20 I will strictly follow the doctor's advice.
	21 If there is a need in the future, I will still come here.
	22 When relatives and friends have oral health problems, I will recommend them to come here.

Data analysis

The structural equation modeling (SEM) is a statistical analytical approach enabling the simultaneous estimation of parameters across multiple equations. In the present study, 3 latent variables were defined: patients' experience with medical staff (encompassing items 1-9) and hospital system construction (encompassing items 10-18), each comprising 9 underlying factors, and loyalty (encompassing items 20-22), which consisted of 3 factors. Following the adjustment for confounding demographic factors, we employed AMOS 24 to examine the relationships among these latent and observed variables. The connections between them are indicated by the numbers situated between the lines.

Results

A total of 307 questionnaires were collected, with 288 being completed and valid. The sample has a higher number of females, with 177 participants (61.5%) compared to 111 males (38.5%). The age distribution indicates that the largest group of participants (50.7%) was between 30 and 60 years old, followed by those aged 30 or younger (44.1%), while only 5.2% were aged 60 or older. In terms of professional background, a significant majority (85.4%) were not employed in healthcare, with only 14.6% being medical professionals. The educational levels reflect the age distribution, 50.7% had a bachelor’s degree, 44.1% completed high school, and merely 5.2% achieved a master’s degree or higher. Medical insurance coverage was almost evenly split, as 50.7% did not have insurance and 44.1% were insured. Lastly, satisfaction levels were predominantly positive, with 92.4% expressing satisfaction, 6.9% feeling neutral, and only 0.7% indicating dissatisfaction (Table 2).

Table 2.

Demographic characteristics of participants.

Characteristics	Variables	N	%
Sex	Male	111	38.5
	Female	177	61.5
Age	30 y old and below	127	44.1
	30-60 y old	146	50.7
	60 y old and above	15	5.2
Medical staff	Yes	42	14.6
	No	246	85.4
Educational attainment	High school and below	127	44.1
	Bachelor	146	50.7
	Master and above	15	5.2
Medical insurance	Yes	133	46.2
	No	155	53.8
Satisfaction	Not satisfied	2	0.7
	Normal	20	6.9
	Satisfied	266	92.4
	Total	288	100

Figure illustrates a comprehensive framework that elucidates the intricate relationships among the key dimensions of our questionnaires. A total of twenty-two observed variables (numbered 1-22) effectively evaluates these latent constructs, exhibiting factor loadings that span from 0.45 to 0.91, with particularly robust reliability (loadings 0.77) for indicators related to the patient's experience with system construction and medical personnel. The patient's experience with system construction shows an exceptionally strong direct effect (path coefficient = 0.93) on medical staff while also exerting a significant impact (path coefficient = 0.72) on loyalty. The patient’s experience with medical personnel has a considerable influence on loyalty (path coefficient = 0.78). The relationship between loyalty and satisfaction demonstrates reciprocal path coefficients of 0.56 and 0.55 respectively, establishing a positive cycle of service improvement. Additionally, the model confirms significant synergistic effects through covariances of 0.64 and 0.78 among patients experience with system construction, medical staff, and loyalty.

Fig. 1.

The connection between the loyalty of outpatients, their satisfaction, and their interactions with medical personnel and the structure of the healthcare system.

Discussion

High agreement between patients' views on system construction and medical personnel experience

One of our findings showcase an exceptionally strong direct effect (path coefficient = 0.93) between patients' assessments of system construction and their views on the performance of medical personnel,³² which means 1-unit increase in patients experience with system construction leads to a 0.93-unit increase in medical staff performance. This nearly perfect correlation indicates that patients perceive the quality of the institution and the competency of the staff as inherently intertwined. The significant factor loadings (0.77-0.93) for the observed variables of both constructs further support this consistency, suggesting that patients' encounters with system efficiency directly influence their evaluation of staff effectiveness. Our study aligns with Moore et al³² structure-process-outcome model, which posits that institutional infrastructure (structure) directly enables staff performance (process). This implies that healthcare administrators cannot enhance staff perceptions in isolation—improvements to the system are necessary prerequisites for better patient-staff interactions. The high correlation between them is supported by other studies in healthcare.^33,34

Patient experiences have a strong impact on loyalty, with system construction being more influential

Although both system development (0.72) and medical personnel performance (0.78) notably affect patient loyalty, the model highlights a crucial hierarchy: experiences related to the system have a more primary influence. The direct path of 0.72 from system development to loyalty indicates that patients' loyalty is primarily based on the reliability of the institution, with staff competence serving to enhance this groundwork. This is further supported by the significant covariance (0.78) between system development and loyalty, indicating a shared variance in the factors that influence these assessments. The practical takeaway is that healthcare providers should prioritize improvements to the system (digital tools, process optimization), as these lay the groundwork for loyalty, which is then enhanced by staff excellence.

Reciprocal relationship between patient loyalty and satisfaction

The two-way connection between loyalty and satisfaction (0.56/0.55) illustrates a self-reinforcing cycle that is crucial for retaining services. Patients who cultivate loyalty through positive system and staff experiences report greater satisfaction (0.56), while those who are satisfied reciprocally bolster their loyalty (0.55). This balance indicates that loyalty indicators (reuse intention, recommendations) are effective at predicting satisfaction. Satisfaction assessments alone may overlook the true drivers of loyalty. Early interventions aimed at fostering loyalty (through system and staff enhancements) can lead to sustained increases in satisfaction. The moderate yet equitable coefficients suggest that neither construct fully encapsulates the other - both need tailored management approaches despite their interdependence. This relationship underscores the need for ongoing monitoring of both metrics in patient experience initiatives.

Conclusion

In summary, this study provides a comprehensive theoretical framework for understanding the mechanisms of patient loyalty in dental care settings, with its insights guiding resource allocation and service quality improvement in similar dental institutions and offering a reference for advancing patient-centered care in broader healthcare contexts. Future research could expand the sample across multiple regions and hospital types to enhance result generalizability and further explore potential mediating or moderating factors influencing the identified variable relationships.

Author contributions

Concept and design: Xiao, Wei, Hong.

Acquisition, analysis, or interpretation of data: Xiao, Jingwen, Hui, Wei, Hong.

Drafting of the manuscript: Xiao.

Critical revision of the manuscript for important intellectual content: Xiao, Hui, Wei, Hong.

Ethics statement

The Ethics Committee of the Stomatological Hospital of Xi’an Jiaotong University approved this study (No. KY-QT-20250053).

Funding

The authors received financial support from the China Oral Health Foundation, grant number FX202428.

Conflicts of interest

The authors state that they have no recognized financial conflicts of interest or personal connections that might have seemed to affect the work presented in this article.