Abstract
Background
As an important content reflecting the quality of medical service, consultation satisfaction affects the final treatment effect in different degrees. The purpose of this paper is to analyze the influencing factors of dental emergency patients’ visit satisfaction and construct structural equation modeling, trying to find the key point to improve the visit satisfaction of dental emergency patients.
Methods
To develop a questionnaire on the satisfaction of emergency dentistry patients, to conduct a sample survey of emergency dentistry patients in different levels of public hospitals in the region, to measure the satisfaction of emergency dentistry patients, and to construct a structural equation model of the factors affecting them.
Results
This study included 1237 emergency dentistry patients in 12 hospitals. The overall satisfaction rate of emergency dental patients was 82.14%, and the satisfaction rate of patients in tertiary hospitals was significantly lower than that of tertiary B, secondary hospitals, and secondary B hospitals (P < 0.05). The structural equation model fit well, and satisfaction was mainly influenced by the five dimensions of “perceived value, service quality, service process, resource convenience, and facility comfort”, with perceived value having the highest intensity of influence on patient satisfaction, followed by service quality.
Conclusion
This study reveals the key factors that may affect the satisfaction of emergency dentistry patients’ visits, and management improvements by hospital and departmental administrators to address the relevant factors will help to improve the effectiveness of oral healthcare services and enhance patient satisfaction.
Keywords: Dentistry, Emergency patients, Visit satisfaction, Structural equation modeling, Construction
Introduction
As an important functional department in hospitals, one of the important duties of the dental department is to deal with toothache, an oral problem that is very likely to cause adverse emotions in patients. Emergency dental patient satisfaction is an important element reflecting the quality of dental health care services, often directly or indirectly affecting the final treatment outcome. Patient satisfaction assessment is of great significance in improving the quality of medical services, reducing doctor-patient disputes, and building a harmonious doctor-patient relationship [1–3]. Satisfaction is a variable that belongs to the category of variables that cannot be measured accurately and directly, i.e., potential variables, which can only be measured indirectly through some indicators. In terms of the form of patient satisfaction measurement, hospitals can adopt a combination of various forms, including on-site distribution of questionnaires, holding doctor-patient symposiums, setting up suggestion boxes, online surveys, etc., of which on-site questionnaire surveys are the measurement method adopted by most hospitals [4–6]. Among the various methods, satisfaction questionnaires are the most commonly used measurement tools, and the development of questionnaires is the basis of satisfaction surveys and a reliable guarantee of survey results.
At present, most of the content of patient satisfaction surveys in hospitals across China is designed according to the satisfaction evaluation standards for third-level hospitals developed by the Ministry of Health or the satisfaction questionnaire recommended by the Chinese Nursing Association [7–9]. Literature [10–13] explored the process of developing patient satisfaction questionnaires, elaborated on the key contents of the development of each step of the questionnaire, emphasized the scientific method and process of questionnaire index selection; at the same time, introduced several types of patient satisfaction questionnaires at home and abroad, and emphasized the scientific method and process of questionnaire indicator selection. Rn D K K et al. [14] proposed a hierarchical management system combining regular comprehensive assessment of patient satisfaction with daily focused assessment for the shortcomings of existing patient satisfaction studies in practical application, and constructed a regular comprehensive assessment index system and assessment data analysis method system. In recent years, scholars in various countries have paid increasing attention to the important research topic of patient satisfaction, but no research has been conducted on the satisfaction of emergency dental patients, an important and special group. In this study, 1237 emergency dentistry patients from 12 hospitals were surveyed on their visit satisfaction, and the influencing factors of emergency dentistry patients’ visit satisfaction were explored, and the structural equation model was constructed, and the intensity of the influence of each factor was found, with a view to providing several theoretical references for hospitals to improve patients’ visit satisfaction.
Materials and methods
Survey respondents and methodology
According to the distribution of the current healthcare service system in China, combined with the principle of stratified sampling, three tertiary hospitals, five tertiary hospitals, two secondary hospitals, and two secondary hospitals in the region were selected as survey subjects for this study, and all of the 12 selected were public hospitals. A self developed or administred inpatient satisfaction questionnaire was utilized to conduct a visit satisfaction survey from January 2016 to November 2021 for emergency dental patients in these 12 hospitals. To ensure that patients had fully experienced the consultation process, patients who had finished the consultation on the same day and were able to cooperate with the survey were selected for the survey, and the survey was conducted after the doctor had issued the discharge order. In order to ensure the quality of the survey, the questionnaire surveyors were systematically and professionally trained, and collaborated with the administrators of the hospital’s Department of Stomatology to distribute the questionnaires on site, which were retrieved by the patients on the spot after filling out the form, and answered on the spot in case of any questions. This study is a retrospective study. Informed consent was obtained from all participants in this study by signing an informed consent form.
Design of the questionnaire
A questionnaire was administered to all dental emergency patients with reference to relevant literature [15]. The questionnaire consisted of 40 questions, each of which was scored on a 7-point Likert scale and categorized into eight dimensions: service quality (SQ), resource convenience (RC), facility comfort (FC), service process (SP), perceived value (HV), “Overall Satisfaction” (OS), “Patient Complaints “ (PC) and “Patient Loyalty” (PL).
Statistical methods
SPSS version 23.0 (SPSS, Inc., Chicago, IL, USA) was used to process the reliability analysis, correlation analysis, logistic regression analysis, etc., and the structural equation model (SEM) constructed in this paper was validated using AMOS software. Count data are represented by n, and measurement data are represented by (± s). The F test is used to compare multiple groups of measurement data. The results were considered statistically significant when P < 0.05.
Results
General information on survey respondents
A total of 1,500 questionnaires were distributed and 1,320(88%) were recovered. After excluding questionnaires with obvious wrong answers, missing items, omissions, etc., the final valid questionnaires were 1,237, with an overall validity rate of 82.47%. The general information of the survey respondents is shown in Table 1.
Table 1.
General information about the respondents
| variant | number of people | component ratio(%) |
|---|---|---|
| genders | ||
| male | 610 | 49.3 |
| female | 627 | 50.7 |
| Age (years) | ||
| < 20 | 34 | 2.7 |
| 20 ཞ 29 | 169 | 13.7 |
| 30 ཞ 39 | 198 | 16.0 |
| 40 ཞ 49 | 252 | 20.4 |
| 50 ཞ 59 | 180 | 11.3 |
| ≥ 60 | 404 | 32.7 |
| Family residence | ||
| municipalities | 550 | 44.5 |
| townships | 315 | 25.4 |
| countryside | 372 | 30.1 |
| Monthly income (RMB) | ||
| < 2 000 | 402 | 32.5 |
| 2 000 ཞ 4 999 | 577 | 46.6 |
| 5 000 ཞ 9 999 | 205 | 16.6 |
| ≥ 10 000 | 53 | 4.3 |
| Medical Payment Methods | ||
| Basic medical insurance for urban workers | 416 | 33.6 |
| New rural cooperative medical care | 428 | 34.6 |
| Basic medical insurance for urban residents | 190 | 15.4 |
| commercial insurance | 30 | 2.4 |
| self-financed medical care | 99 | 8.0 |
| medical treatment at public expense | 33 | 2.7 |
| else | 41 | 3.3 |
| educational attainment | ||
| No formal schooling | 107 | 8.6 |
| secondary schools | 251 | 20.3 |
| junior high school | 340 | 27.5 |
| senior high school | 281 | 22.7 |
| University and above | 258 | 20.9 |
| careers | ||
| workers | 233 | 18.8 |
| peasants | 382 | 30.9 |
| freelancer | 172 | 13.9 |
| Commercial or self-employed | 121 | 9.8 |
| principals | 62 | 5.0 |
| medical personnel | 32 | 2.6 |
| worker in science and technology | 21 | 1.7 |
| office-bearer | 48 | 3.9 |
| Other (e.g. students, etc.) | 166 | 13.4 |
| First visit to the hospital | ||
| first time | 549 | 44.4 |
| second time | 350 | 28.3 |
| third time and above | 338 | 27.3 |
| Have you been to any other hospitals? | ||
| yes | 547 | 44.2 |
| no | 690 | 55.8 |
Comparison of the results of an empirical analysis of patient visit satisfaction in the dental emergency department
Statistical results of patient visit satisfaction scores for oral emergency room visits
According to the Likert scale 7 level scoring method, the option falling above 5 points was statistically considered satisfactory, and the statistical results are shown in Table 2. The overall satisfaction of the patients in the dental emergency clinic was high at 82.14%, with 86.86%, 82.79%, 85.13%, 81.65%, and 81.73% for the five influencing factor dimensions, respectively. The percentage of emergency patients who indicated that they were inclined to make complaints if they were dissatisfied was 74.54% for a score of 5 or higher for patient complaints, and 77.45% for a score of 5 or higher for patient loyalty, which indicated that the percentage of loyal patients who were likely to choose the hospital again or to praise or recommend the hospital to others was 77.45%.
Table 2.
Results of the evaluation of the dimensions of satisfaction of patients in the oral emergency department
| Satisfaction Dimension | satisfaction rating(X ± SD) | Percentage of patients with scores ≥ 5 (%) |
|---|---|---|
| Quality of Service(SQ) | 5.44 ± 1.29 | 86.86 |
| Resource convenience(RC) | 5.36 ± 1.33 | 82.79 |
| Comfortable facilities(FC) | 5.32 ± 1.36 | 85.13 |
| Service Process(SP) | 5.29 ± 1.30 | 81.65 |
| Hospital Values(HV) | 5.26 ± 1.28 | 81.73 |
| Overall satisfied(OS) | 5.31 ± 1.34 | 82.14 |
| Patient complaints(PC) | 5.01 ± 1.42 | 74.54 |
| Patient loyalty(PL) | 5.24 ± 1.30 | 77.45 |
Comparative analysis of patients’ satisfaction with dental emergency room visits in different levels of medical institutions
The satisfaction scores of oral emergency patients’ visits by level of medical institutions were counted separately, and the results are shown in Table 3.As seen in Table 3, the differences in the scores of all dimensions of satisfaction of oral emergency patients’ visits among hospitals of different levels were statistically significant (P < 0.05), and the patient satisfaction of tertiary hospitals was significantly lower than that of other hospitals.
Table 3.
Comparative analysis of patients’ satisfaction with dental emergency room visits at different levels of care(X ± SD)
| Hospital level | SQ | RC | FC | SP | HV | OS | PC | PL |
|---|---|---|---|---|---|---|---|---|
| Level 2 A hospital | 4.93 ± 1.55 | 4.90 ± 1.55 | 4.87 ± 1.63 | 4.76 ± 1.50 | 4.77 ± 1.51 | 4.78 ± 1.56 | 4.58 ± 1.55 | 4.76 ± 1.46 |
| Level 3B hospital | 5.85 ± 1.00 | 5.70 ± 1.16 | 5.68 ± 1.14 | 5.72 ± 1.07 | 5.62 ± 1.07 | 5.71 ± 1.08 | 5.30 ± 1.36 | 5.59 ± 1.14 |
| Level 2 A hospital | 5.99 ± 0.84 | 5.82 ± 0.92 | 5.74 ± 1.04 | 5.80 ± 0.98 | 5.77 ± 0.95 | 5.89 ± 1.03 | 5.31 ± 1.26 | 5.78 ± 1.05 |
| Level 2B hospital | 5.30 ± 0.76 | 5.33 ± 0.79 | 5.34 ± 0.72 | 5.26 ± 0.72 | 5.27 ± 0.75 | 5.27 ± 0.83 | 5.30 ± 0.87 | 5.23 ± 0.81 |
| F value | 57.932 | 38.500 | 35.542 | 58.991 | 47.928 | 55.134 | 27.337 | 46.577 |
| P value | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
Reliability analysis of sample data and modeling of influencing factors
Confidence analysis of sample data
CITC (item-total correlation coefficient) and Cronbach’s alpha concordance coefficient were used to analyze the reliability, and the results showed that the CITC values and alpha coefficients of the items corresponding to the five dimensions of “perceived hospital brand”, “perceived hospital quality”, “perceived hospital value”, “patient complaints”, and “patient loyalty” all showed good reliability, reaching 0.0. The results showed that the CITC values and alpha coefficients of the questions corresponding to the five dimensions of “perceived hospital brand”, “perceived hospital quality”, “perceived hospital value”, “patient complaints”, and “patient loyalty” showed good reliability ranging from 0.922 to 0.986.
Sample data validity test
Both exploratory factor analysis and validation factor analysis were used to test the validity of the questionnaire.
A validity test of the causative scale of patient visit satisfaction in emergency dental care
The KMO value for the Causal Scale of Patient Visit Satisfaction in Emergency Dental Care was 0.985 > 0.90, indicating that the relationship between the question variables was excellent and that the question variables were well suited for factor analysis. Factors with eigenvalues greater than 1 were extracted, and the analysis presented five principal components, component 1 representing perceived healthcare service quality, explaining 32.026% of the variance, component 2 representing service process, explaining 17.088% of the variance, component 3 representing perceived hospital value, explaining 16.289% of the variance, component 4 representing resource convenience, explaining 11.858% of the variance, and component 5 represents facility comfort, explaining 6.884% of the variance, and the five common factors explained 84.145% of the variance of the dental emergency patient visit satisfaction causation scale, which had quite good construct validity. Through multiple rotations and convergence after 9 iterations, the final factor loadings of the Oral Emergency Patient Visit Satisfaction Causation Scale all reached more than 0.5 and stabilized between 0.512 and 0.768, indicating that the construct validity of the scale was good. The results of the rotation were mostly consistent with the theoretical factor structure.
A validity test of the outcome scale for patient visit satisfaction in dental emergencies
The KMO value of the Oral Emergency Patient Visit Satisfaction Outcome Scale was 0.828 > 0.80, indicating that the relationship between the question variables was good and that the factor analysis was suitable between the question variables. By rotation, the factor loadings of all the question items reached the index and were significantly greater than 0.5, and the results of the rotation were fully consistent with the theoretical factor structure, with factor loadings of 0.838 to 0.907.
Modeling the factors influencing the satisfaction of dental emergency patients’ visit to the clinic
The validated factor analysis was used to construct a model (M1) of factors influencing the satisfaction of dental emergency patients’ visits, as shown in Fig. 1. The values of the goodness-of-fit indexes derived from the validated factor analysis of the Oral Emergency Patient Visit Satisfaction Causation Scale: χ2/df = 4.305, GFI = 0.919, AGFI = 0.901, NFI = 0.970, CFI = 0.977, and RMSEA = 0.052, which basically reached the standard values of reference, and at the same time, the factor of each question item in the dimension it corresponds to has a factor The score Weights of each question item under its corresponding dimension are significantly higher than those of other dimensions, so the scale items have good discriminant validity.The AVE values of the five latent variables are all significantly greater than 0.50, which indicates that the convergent validity of the model is ideal. The test results of other fit indexes were also all higher than the standard value, which shows that the model of factors influencing the satisfaction of dental emergency patients’ visit meets the statistical test standard and is acceptable.
Fig. 1.
Model of factors influencing the satisfaction of oral emergency patients’ visit to the clinic
Correlation analysis
Before conducting the structural equation modeling analysis, a two-by-two Pearson correlation analysis was done between the dimensions of the Dental Emergency Patient Visit Satisfaction Scale, and the results showed that OS was significantly correlated with SQ, RC, FC, SP, HV, PC, and PL (P < 0.05), with the correlation coefficients of Patient Loyalty and Overall Satisfaction being higher (r = 0.469, P < 0.05) and the model hypotheses were preliminarily verified in the correlation analysis. See Table 4.
Table 4.
Correlation analysis
| variant | OS | |
|---|---|---|
| r | P | |
| SQ | 0.251 | 0.026 |
| RC | 0.316 | 0.012 |
| FC | 0.189 | 0.017 |
| SP | 0.154 | 0.012 |
| HV | 0.327 | 0.004 |
| PC | 0.254 | 0.031 |
| PL | 0.469 | 0.021 |
Logistic regression analysis
Correlation analysis can judge the strength of the association between dimensions and variables, while logistic regression analysis can analyze the causal relationship between dimensions and variables, and can judge the degree of influence of causality according to the regression coefficient. The regression analysis of each dimension of the Oral Emergency Patient Visit Satisfaction Influence Factor Scale on OS is shown in Table 5.From the results of Table 5, it can be seen that four dimensions of the five dimensions of the Oral Emergency Patient Visit Satisfaction Factor Scale, namely, SQ, RC, SP, and HV, entered into the regression equation while FC did not enter into the regression equation, and the regression coefficient of HV was the largest of the four dimensions that entered into the regression equation, which indicated that it had the greatest influence on OS. The regression equation is: OS = 0.526 × HV + 0.411 × SQ + 0.431 × SP + 0.433 × RC (Eq. 1).OS has a significant negative effect on PC, and its regression equation is: PC = −0.705 × OS (Eq. 2).OS has a significant positive effect on PL, and its regression equation is: PL = 0.703 × OS (Eq. 3).
Table 5.
Logistic regression analysis of the dimensions of the dental emergency patient visit satisfaction influence factor scale on OS
| variant | β | SE | Wald value | Pvalue | OR | 95%CI |
|---|---|---|---|---|---|---|
| SQ | 0.411 | 0.188 | 4.779 | 0.029 | 1.508 | 1.043ཞ2.180 |
| RC | 0.433 | 0.208 | 4.334 | 0.038 | 1.542 | 1.026ཞ2.318 |
| SP | 0.431 | 0.206 | 4.377 | 0.037 | 1.539 | 1.028ཞ2.304 |
| HV | 0.526 | 0.227 | 5.369 | 0.021 | 1.692 | 1.084ཞ2.640 |
| PC | –0.705 | 0.308 | 5.239 | 0.023 | 2.024 | 1.107ཞ3.701 |
| PL | 0.703 | 0.306 | 5.278 | 0.022 | 2.020 | 1.109ཞ3.679 |
Structural equation modeling of the oral emergency patient visit satisfaction scale
Based on the results of the analysis of the Oral Emergency Patient Visit Satisfaction Causation Scale and the Outcome Scale, we constructed a structural equation model (M2) of the Oral Emergency Patient Visit Satisfaction Scale to further explore the effects of these influences on OS and on the expression of the satisfaction outcomes (see Fig. 2).The five influences can either directly affect the level of OS or can be expressed as PL or PC. The fit of the model M2 Indicator CMIN/df = 3.794, P value 0, GFI = 0.908, AGFI = 0.892, NFI = 0.965, TLI = 0.971, CFI = 0.974, RMSEA = 0.048, all of them meet the standard of the statistical test, and the model is well fitted. Then the AMOS software was used to test M2, and the results are shown in Table 6, which shows that the model hypotheses of RC and SP for OS cannot be supported. All other model assumptions adjusted according to the regression analysis were supported. The above results show that two factors, RC and SP, do not have a significant moderating effect on OS of oral emergency patients’ visit satisfaction, while both factors, SQ and HV, have a significant positive moderating effect on OS of oral emergency patients’ visit satisfaction. On the other hand, OS had a significant negative moderating effect on PC, i.e., the higher the OS, the lower the PC; and OS had a significant positive moderating effect on PL, i.e., the higher the OS, the higher the PL. These two findings happened to complement and harmonize with each other.
Fig. 2.
Structural equation modeling of patient visit satisfaction in oral emergency medicine
Table 6.
ESQ structural equation modeling test results
| trails | Standardized path factor | SE | CR | P |
|---|---|---|---|---|
| OS<---RC | 0.042 | 0.037 | 1.173 | 0.241 |
| OS<---SQ | 0.142 | 0.037 | 3.853 | < 0.001 |
| OS<---SP | 0.078 | 0.048 | 1.727 | 0.084 |
| PL<---HV | 0.730 | 0.056 | 14.010 | < 0.001 |
| PC<---OS | 0.807 | 0.025 | –34.875 | < 0.001 |
| PL<---OS | 0.883 | 0.020 | 44.982 | < 0.001 |
Discussion
In this study, a questionnaire was self-developed in a more scientific way to measure the satisfaction of dental emergency patients, and the results of the survey of dental emergency patients in 12 public hospitals showed that the questionnaire had good reliability and validity, and further explored the model of the factors influencing the satisfaction, and constructed a structural equation model of the satisfaction scale, and the assumptions of the model were also well empirically examined. Oral emergency patient visit satisfaction is mainly influenced by the following 5 factors, and in descending order of strength, they are HV, SQ, SP, RC, and PC, of which HV and SQ are the key factors. These 5 factors were in turn expressed as PC or PL through the results of OS, where PL showed a significant positive correlation with OS and PC showed a significant negative correlation with OS.
The results of this study show that the satisfaction score of tertiary hospitals is significantly lower than that of other levels of hospitals, and this result is worth pondering. Generally speaking, tertiary hospitals are hospitals with advantages in medical technology, equipment and human resources, so why do the results show that patient satisfaction is significantly lower? Possible reasons, from the objective status quo considerations, admitted patients with more complex conditions, coupled with a large number of patients, hospitalization cycle is short, so that the tertiary hospitals are in a state of overload; from the satisfaction of the factors affecting the consideration of the high cost of medical care, the quality of service is not as good as the patient’s expectations, there are problems in the service process, the lack of resources, not convenient enough, the facilities are not comfortable enough and so on, more prominent than in other hospitals, it is worth the hospital administrators to The results of Velverthi N et al. [16] have proved that demographic characteristics do not play a major role in patients’ choice of hospitals, and that the influencing factors are mainly the hospital’s own characteristics, such as the quality of the medical environment, attitude and services. A study by Bilenler Z K et al. [17] concluded that service attitude and medical technology are important aspects affecting patient satisfaction, and that the attitude and medical technology of medical staff have a strong positive correlation on satisfaction.A study by Zhu Y et al. [18] revealed that a doctor’s good technology and initiative in explaining health care, whether or not the doctor is trustworthy, and the waiting time are the key factors affecting patient satisfaction.Xu N et al. [19] developed a simple questionnaire covering seven entries of hospitalization procedures, medical technology, service attitude, pain management, patient participation, environment, and comprehensive evaluation to investigate and study patients’ satisfaction with their visit to the clinic.Although the questionnaire was streamlined and less time-consuming, it was not comprehensive enough to investigate the patient’s experiential aspects of the experience. Sana Y et al. [20] showed that non-medical factors have become the most important factors affecting the doctor-patient relationship (91.8%), and the problems of medical costs and doctor-patient communication are also very prominent, accounting for 21.5% and 11.51%, respectively.Wei H et al. [21] showed that the results of a survey of doctors and patients in Beijing’s public healthcare institutions showed that the perception of the factors affecting the doctor-patient relationship tensions was centered around the “cost problem”, with most of the doctors and patients believing that “the cost problem” was the main factor. The majority of the doctors and patients believed that the most vulnerable part of the doctor-patient conflict was the “charging process”.
In this study, we found that the most significant correlation factor for the satisfaction of emergency dental patients was “HV”, followed by “SQ”, which revealed that the key factor affecting the satisfaction of emergency dental patients may be the comprehensive evaluation of medical cost and service quality, this result is consistent with the conclusions of Huiling C’s research [22]. Therefore, the improvement of service quality of medical staff, optimization of service flow, and reasonable and transparent medical charges are the key links to improve patient satisfaction, which identifies the key factors and provides a reference path for effectively solving the conflicts between doctors and patients. For example, hospitals can try to improve SQ by establishing a 15-minute response mechanism for dental emergencies, developing an emergency pain grading intervention process, promoting painless local anesthesia techniques, and training staff in “emergency communication techniques.” They can also try to strengthen HV by introducing a fixed price for emergency services, which includes registration, treatment, and basic medication costs, thereby eliminating price uncertainty. With the increasing expectations of patients on the quality of medical services, the modern concept of patient-centered hospital management is popular, and the doctor-patient relationship model has a variety of dimensions of understanding, in which the analogy of patients as customers is widely accepted [23]. Medical and health services provided by medical institutions are also a kind of consumer product, to win customer satisfaction and repurchase willingness, the medical side should attach great importance to the patient’s medical experience and strive to improve patient satisfaction [24]– [25]. It is very necessary and urgent to incorporate patient satisfaction measurement into the standing indicators of hospital management, and third-party evaluation has many characteristics and advantages such as independence objectivity and professionalism, if it can be combined with the information management of modern hospitals, the evaluation scale of this study is combined with mobile electronic devices for regular evaluation, which can provide effective feedback data for the evaluation management of hospitals and the management of healthcare quality, and help targeting to improve management and enhance the satisfaction of emergency patients’ visits to the stomatology department [26–28]. Additionally, this study found that the two factors of RC and SP did not have a significant moderating effect on the OS of dental emergency patients. However, the lack of significance of RC and SP does not imply their unimportance; rather, their effects may have been absorbed by higher-order variables (SQ, HV). Exploring the potential reasons, the core concern of dental emergency patients is the rapid relief of severe pain or trauma, leading to reduced sensitivity to resource conditions such as geographical location and registration convenience. “Life-saving” may be more important than “proximity.” Emergency service processes in the medical field typically exhibit high standardization, and patients lack choice, with “service process experience” often yielding to “outcome effectiveness.”
Due to limited funding and time, this study has certain limitations, such as: the sample was selected only from some public hospitals in the region, lacking a large sample survey of hospitals across the country, therefore, the conclusions of this study may lack universality. In addition, research models and hypotheses lack longitudinal data in chronological order. When the conditions are ripe for follow-up research, the scope of the survey can be expanded horizontally, and the comparative study can be continued vertically, and the changes in patient satisfaction and doctor-patient relationship can be synthesized with the changes in medical policies and hospital management environment.
Conclusion
The satisfaction of dental emergency patients is primarily influenced by five dimensions: “SQ, RC, FC, SP, and HV.” Among these, the most significant factor affecting the satisfaction of emergency dental patients is “HV,” followed by “SQ.” This suggests that the key factors influencing the satisfaction of emergency dental patients may be a comprehensive assessment of medical costs and service quality. Hospital and department managers can enhance the effectiveness of oral healthcare services and improve patient satisfaction by implementing targeted improvement measures to address these issues.
Acknowledgements
We sincerely thank all participants for their excellent contributions to this paper.
Authors’ contributions
All authors made indispensable and important contributions to this study, including Li Shen and Xin Yang, who were mainly responsible for researching and writing this paper, Shuangshuang Zhang and Lingling Zhang, who were mainly responsible for reviewing and revising this paper.
Funding
None.
Data availability
Data are available upon request from the corresponding author of this article.
Declarations
Ethics approval and consent to participate
This study was approved by the vote of the Medical Ethics Committee of Nanjing Stomatological Hospital and informed consent was obtained from all participants. This study adheres to the the Helsinki Declaration.
Competing interests
The authors declare no competing interests.
Consent for publication
Inapplicable.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data are available upon request from the corresponding author of this article.