A comparative study of total quality management in healthcare from provider and patient perspectives at Al-Mouwasat University Hospital

Abstract

The Total Quality Management (TQM) is a strategic approach that aims to improve healthcare services by enhancing operational efficiency and ensuring patient satisfaction. Despite its widespread application in developed countries, TQM’s implementation in developing nations, particularly in the healthcare sector, has been limited. This study aims to evaluate TQM awareness, its application, and the effectiveness of scientific methods in improving healthcare services at Al-Mouwasat University Hospital, Syria. A cross-sectional, descriptive-analytical design was used, surveying 390 participants, including doctors, nurses, and patients. The study assessed TQM awareness, perceptions of hospital performance, and the use of scientific and statistical methods to enhance healthcare delivery. Statistical analyses, including the Mann–Whitney test, Kruskal–Wallis test, Dunn’s test, and Tukey test, were applied to identify significant differences in opinions across groups. The study found that doctors and nurses demonstrated neutral attitudes toward TQM principles, while patients showed higher satisfaction with healthcare services. Nurses were more supportive of scientific and statistical methods for improving hospital performance compared to doctors (P < 0.001). Significant differences were observed between doctors and nurses regarding patient interaction (P < 0.001), while no significant differences were observed regarding medical errors. Longer hospital stays correlated with higher patient satisfaction (P < 0.001), while no significant differences were found based on gender or age. These findings underscore the necessity of targeted training programs and organizational support to foster TQM adoption. By addressing systemic barriers, the hospital can enhance service delivery, ultimately contributing to better patient outcomes and sustained healthcare quality improvement.

Introduction

TQM has become a globally recognized strategic management philosophy, focusing on customer satisfaction and fostering a cohesive strategy to enhance organizational performance. It is integral to the competitive strategy of organizations across various industries, including healthcare^1,2. TQM centres on continuous improvement, engaging all members of an organization in refining processes, products, services, and the organizational culture itself³. For example, Salah et al.³ emphasize that integrating TQM principles with continuous improvement methodologies fosters organizational resilience and adaptability. This customer-focused approach ensures that quality is embedded in every aspect of operations, driven by data, strategic planning, and effective communication^3,4. Ultimately, customer satisfaction determines the success of these efforts, highlighting the importance of aligning quality improvement initiatives with customer expectations^4,5. This study highlights that patient satisfaction is a core determinant of healthcare success and directly reflects the effectiveness of quality improvement measures.

In recent decades, the healthcare sector has increasingly embraced TQM as a means to boost efficiency, reduce costs, and elevate the standard of care provided to patients^5,6. Ahmed⁶ demonstrates that implementing TQM in hospitals leads to measurable improvements in service performance and patient outcomes, particularly in resource-constrained settings. This widespread adoption reflects a broader global trend in which healthcare organizations integrate TQM principles to meet the growing demands for higher quality care and operational efficiency⁶. As healthcare organizations continue to evolve, quality has become paramount, particularly in ensuring patient satisfaction and addressing patient needs promptly^4,5. In healthcare, quality is not merely a competitive advantage but a critical factor for survival and success. Providers must navigate professional standards while avoiding legal and ethical challenges^4,5. The sector’s commitment to TQM underscores a dedication to improving healthcare services, managing risks, and meeting the evolving needs of patients in a dynamic and complex environment⁷. Healthcare in Syria is characterized by significant challenges, including resource scarcity, infrastructural damage due to ongoing conflict, and limited access to advanced medical technologies. These constraints shape the readiness and feasibility of implementing TQM principles. Additionally, cultural factors such as hierarchical organizational structures and traditional attitudes toward patient care may influence healthcare providers’ perceptions of TQM initiatives. Al-Mouwasat University Hospital is one of Syria’s leading healthcare institutions, serving as a tertiary care center and a critical provider of specialized medical services in a resource-limited environment⁸. Its prominence makes it a valuable case study for evaluating TQM implementation in the Syrian healthcare system. Addressing these contextual barriers is critical for designing effective interventions tailored to the Syrian setting.

This significance of the current paper emerges from exploring critical issues that are crucial to healthcare administrators who are seeking effective sustainable mechanisms which lead to continuous and accurate improvements in overall service quality. As a result, valuable time and money resources are preserved while ensuring the satisfaction of hospital staff and patients. To be more precise, this study contributes to the existing body of literatures related to applying statistical methods in TQM, which in turn provides valuable insights not only for the decision makers in the studied hospital, but also for broader healthcare sectors, domestic and worldwide. Despite the growing adoption of TQM worldwide, there is still a need to explore its statistical underpinnings, particularly in healthcare institutions of developing nations, like Syria. We hope that this study would bridge that gap by evaluating the feasibility of TQM implementation through adopting rigorous statistical analysis, and would contribute to deeper understandings of the practical applications of TQM in developing countries context. By focusing on Al-Mouwasat University Hospital, the study offers actionable recommendations for improving healthcare quality and operational efficiency, which may serve as a model for similar institutions navigating comparable challenges.

The findings reflect the existence of growing needs for enhancing quality services as rapid technological advancements and intense competition do exist. These findings support the well-known fact that conducting statistical studies is crucial for quality control improvement and evaluate the efficiency of healthcare institutions. Besides the international sanctions imposed on Syria, years of conflict have devastated the country’s infrastructure, economy, and social systems, so we are trying to address and answer the following questions: How feasible is it to implement TQM at Al-Mouwasat University Hospital under current conditions to improve the quality of healthcare services provided to patients, if possible? What is the level of awareness among doctors and nurses at Al-Mouwasat University Hospital regarding principles of TQM? What is the perceived quality of healthcare services provided at Al-Mouwasat University Hospital from the patients’ perspective?

TQM’s global success as a strategic philosophy underscores its potential for improving both operational efficiency and customer satisfaction across sectors. Its integration into healthcare is a natural progression, given the sector’s growing emphasis on quality-driven care models, so, this study contextualizes these principles within the unique challenges of the Syrian healthcare system.

Results

Awareness of TQM principles

Likert scale values, expressed as weighted averages, were calculated for each dimension of medical staff Table 1. The findings revealed that doctors and nurses exhibited a neutral stance towards TQM principles, with average scores of 1.90 and 2.29, respectively. The overall weighted average (aveALL) for both doctors and nurses is close to 2, indicating neutral responses to the survey. This suggests that the awareness of TQM principles is neither strongly positive nor negative among healthcare providers.

Table 1.

Descriptive statistics for doctors and nurses.

Measure	Doctors (N = 92)	Mean (SD)	Nurses (N = 96)	Mean (SD)
aveA	92 (48.9%)	2.375 (0.424)	96 (51.1%)	2.624 (0.463)
aveB		1.624 (0.443)		2.116 (0.592)
aveC		1.800 (0.485)		2.205 (0.528)
aveD		1.811 (0.397)		2.213 (0.475)
aveE		1.908 (0.383)		2.289 (0.316)
aveALL		1.904 (0.340)		2.289 (0.370)

A represents the first dimension, B the second dimension, and so on. Thus, aveA is the weighted average for the first dimension, aveB for the second, and so forth. The overall weighted average, aveALL, is close to 2 for both groups, indicating neutral responses to the survey.

Similarly, Table 2 illustrates Likert scale values for patient dimensions. Patients demonstrated higher satisfaction with the quality of health services, reflected in an average score of 2.63 (Table 2). The weighted average for all patient dimensions (aveAll) exceeds 2.33, indicating that patients have a more favorable perception of health services than healthcare providers.

Table 2.

Descriptive statistics for N = 105 patients.

Measure	Mean (SD)
aveA	2.891 (0.186)
aveB	2.678 (0.369)
aveC	2.627 (0.319)
aveD	2.751 (0.360)
aveE	2.841 (0.286)
aveF	2.279 (0.343)
aveG	2.364 (0.352)
aveAll	2.633 (0.158)

The results in Table 2 demonstrate that all patients agree with all dimensions, as their weighted averages exceed the threshold of 2.33. The overall weighted average, aveAll, is also larger than 2.33, supporting this conclusion.

The higher patient satisfaction scores (aveAll = 2.63) compared to providers’ neutral responses suggest a misalignment between frontline staff priorities and patient experiences, potentially reflecting unmet TQM training needs among clinicians. This indicates a notable discrepancy between the perceptions of healthcare providers and patients regarding TQM implementation.

Application of scientific and statistical methods

The study also explored the application of scientific and statistical methods to enhance hospital performance. The variable C6, representing this aspect, showed contrasting opinions among doctors and nurses (Table 3).

Table 3.

Frequencies and percentages of the C6 variant for doctors and nurses.

Response	Frequency for DOCTORS (N = 92)	% (Doctors)	Frequency for nurses (N = 96)	% (Nurses)
Not Accept	51	55.4%	19	19.8%
Neutral	31	33.7%	32	33.3%
Accept	10	10.9%	45	46.9%

Presents the frequencies and percentages (in parentheses) for the C6 variant, illustrating notable differences in acceptance levels between doctors and nurses.

The notable disparity in the acceptance of scientific methods (where 55.4% of doctors versus 19.8% of nurses rejected C6) highlights role-specific challenges. Nurses, with their frequent engagement in data-driven tasks such as patient monitoring, may exhibit greater openness to such methods. In contrast, the resistance observed among doctors may be attributed to concerns over perceived threats to clinical autonomy or a lack of sufficient statistical training.

The Mann–Whitney test revealed significant differences between the opinions of doctors and nurses (U = 2303.5, P < 0.001). This difference was attributed to the differences in professional experience, with doctors being relatively new to the hospital compared to the more experienced nurses.

Patient interaction

The ANOVA test showed that a significant difference exists between the three studied groups concerning patient interaction. Post hoc Tukey tests detected a significant differences between doctors and nurses (P < 0.05) and doctors and patients (P < 0.05). However, there were no significant differences between the opinions of nurses and patients (P = 0.955 ), indicating a consensus between these two groups. The alignment between nurses and patients (P = 0.955) may reflect nurses’ direct patient care roles, enabling them to internalize patient-centric TQM values more effectively than doctors, who often prioritize clinical decision-making over service delivery metrics.

Perception of medical errors

The Kruskal–Wallis test showed that significant differences do exist, )P < 0.05 (. Therefore, we applied Dunn’s test with Bonferroni’s correction which revealed significant differences between the opinions of patients and doctors about medical errors (P = 0.021) (Table 4).

Table 4.

Dunn’s test results with Bonferroni’s correction.

Comparison	Adjusted Sig	Sig	Std. test statistic	SE	Test statistic	Sample 1–Sample 2
3 vs. 1	0.021	0.007	2.705	9.905	26.791	3–1
3 vs. 2	0.000	0.000	4.323	9.794	42.343	3–2
1 vs. 2	0.373	0.124	− 1.537	10.120	− 15.552	1–2

The labels are defined as follows:

1 represents doctors,

2 represents nurses,

3 represents patients.

The table summarizes the statistical significance of differences between these groups using Dunn’s test with Bonferroni adjustment.

Patients were more likely than doctors to agree that there were no medical errors in the hospital. Similarly, patients’ opinions were significantly higher than those of nurses (P < 0.05), indicating greater patient confidence in the absence of medical errors.

Impact of hospital stay duration

The Tukey test showed significant differences in patient opinions based on hospital stay duration. Patients who stayed for one day had lower opinions about the quality of health services compared to those who stayed for 2–9 days (P = 0.032 ) and more than 30 days (P = 0.022 ) (Table 5).

Table 5.

Tukey’s test for hospital stay duration.

Stay duration comparison	Mean difference	Sig	95% confidence interval
One day vs. 2–9 days	− 0.099	0.032	− 0.194 to − 0.005
One day vs. 10–17 days	− 0.111	0.226	− 0.257 to 0.035
One day vs. 18–30 days	− 0.139	0.289	− 0.335 to 0.057
One day vs. > 30 days	− 0.150	0.022	− 0.286 to − 0.015
2–9 days vs. 10–17 days	− 0.011	1.000	− 0.159 to 0.137
2–9 days vs. 18–30 days	− 0.039	0.981	− 0.237 to 0.159
2–9 days vs. > 30 days	− 0.051	0.848	− 0.189 to 0.088
10–17 days vs. 18–30 days	− 0.028	0.997	− 0.256 to 0.199
10–17 days vs. > 30 days	− 0.040	0.972	− 0.217 to 0.138
18–30 days vs. > 30 days	− 0.011	1.000	− 0.232 to 0.210

This suggests that longer stays may lead to higher satisfaction, possibly due to better adaptation to the hospital environment.

Addressing potential problems

The study aimed to identify solutions to potential problems that could negatively affect patient services. The independent one-way ANOVA revealed significant differences between the opinions of doctors, nurses, and patients on various aspects of hospital performance (P < 0.05). The results indicated that doctors’ opinions were generally lower than those of nurses and patients, highlighting areas for improvement in TQM awareness and application.

Overall patient satisfaction

The analysis of patient satisfaction with the quality of health services, considering personal variables such as gender, age group, and length of hospital stay, showed no significant differences based on gender (P = 0.657 ) or age group (P = 0.280 ). We may refer to the fact that our study included 56 male and 49 female patients. However, significant differences were found based on the length of hospital stay (P = 0.005 ), with longer stays correlating with higher satisfaction.

These results underscore the importance of enhancing TQM awareness and training among healthcare providers to bridge the gap between provider perceptions and patient satisfaction. Implementing scientific and statistical methods can further improve hospital performance, as supported by the nursing staff.

Discussion

TQM is a vital approach to improving effectiveness within the healthcare sector^9,10. Numerous studies have demonstrated a positive and significant relationship between the implementation of TQM factors and hospital performance^11–13. Although TQM has been widely adopted in various regions, its application has been more prevalent in developed countries, where the primary motivation is to increase efficiency^14,15.

This study investigated the role of mathematical and applied statistics within TQM to enhance healthcare quality at Al-Mouwasat University Hospital. By analyzing the perspectives of doctors, nurses, and patients, the research aimed to evaluate TQM implementation, explore patient satisfaction drivers, and examine the effectiveness of scientific methods in improving hospital performance. These insights contribute valuable knowledge to hospital managers and healthcare professionals striving for optimized operations and enhanced patient care⁹.

The Syrian context presents unique challenges to TQM implementation. Cultural norms, such as deference to authority and traditional hierarchical structures, may hinder the participatory decision-making crucial for TQM. Furthermore, limited healthcare financing can restrict access to necessary resources and training for quality improvement. Government policies often prioritizing crisis management over long-term development may further complicate TQM integration. Successfully embedding TQM necessitates addressing these systemic and cultural barriers to foster sustainable healthcare quality improvements.Our findings regarding the core components of TQM (leadership, continuous improvement, patient focus, staff involvement, and data-driven decision-making) suggest significant leadership gaps, particularly in fostering staff involvement and ongoing improvement initiatives. The limited infrastructure observed also appeared to constrain data-driven decision-making, impeding the systematic application of TQM principles. These observations highlight that targeted investments and strategic focus in these areas are critical for effective TQM implementation within this setting.A key finding was the neutral attitude of healthcare providers towards TQM principles (average scores: doctors 1.90, nurses 2.29). This overall neutrality, while showing slight variations between doctors and nurses, indicates a potential system-wide challenge in TQM adoption. These differences might reflect varying levels of readiness, possibly influenced by factors such as specific training received, daily workload, and distinct organizational roles, as suggested by literature in other contexts¹⁶. For instance, while doctors’ perceptions might offer areas for enhancement through targeted interventions like improved statistical literacy and workload management, nurses’ slightly more positive yet still neutral scores could indicate a need for greater empowerment and specialized TQM training.

Critically, this provider neutrality contrasts sharply with the higher patient satisfaction scores (average 2.63). This discrepancy is a central point for reflection. While patients report satisfaction, the ambivalence of providers towards TQM principles raises questions about the sustainability and depth of quality care. It is possible that patient satisfaction is driven by aspects of care not directly captured by TQM metrics as perceived by staff, or that provider neutrality has not yet translated into a discernible negative impact on the patient experience. However, as several studies show that well-implemented TQM positively impacts patient satisfaction¹⁷, this mismatch suggests a missed opportunity. If providers are not fully engaged with TQM, the hospital may not be realizing the full potential of quality improvement. Further research should explore which elements of TQM resonate most with patients and how provider engagement can be enhanced to bridge this perceptual gap. The implication is that relying solely on patient satisfaction metrics might mask underlying weaknesses in TQM adoption by staff, potentially hindering long-term quality enhancement.

Regarding the application of scientific and statistical methods, the divergence between nurses (more supportive) and doctors (less supportive), as indicated by the Mann–Whitney test, presents another area for strategic intervention. The original text suggested this might be attributed to nurses being more experienced than the relatively newer doctors¹⁸. While professional experience can influence perspectives, this study did not directly measure tenure or specific experience levels to definitively link them to these attitudes. Therefore, this remains a plausible hypothesis rather than a confirmed reason. It is also possible, as literature suggests, that nurses’ roles, often involving direct data handling for patient monitoring, make them more receptive to such methods. Conversely, doctors’ resistance could stem from concerns about clinical autonomy or insufficient training in these methods. This disparity, also noted elsewhere¹⁹, underscores the need for tailored approaches. For instance, demonstrating the clinical benefits of statistical methods and ensuring training is relevant to doctors’ decision-making processes might improve acceptance.

The finding that nurses’ and patients’ opinions on TQM principles showed no significant differences, suggesting closer alignment, is noteworthy. This convergence, as supported by recent studies^20,21, likely reflects nurses’ continuous and direct patient interaction, which may afford them a deeper understanding of patient needs and satisfaction drivers. This reinforces the pivotal role of nurses in championing patient-centric TQM values.

The analysis of perceptions regarding medical errors, where patients were more likely than doctors (and also nurses) to believe no errors occurred, offers another layer of complexity. While this might reflect genuine quality from the patient’s viewpoint, it could also be influenced by factors such as perceived provider empathy, as suggested by prior research²². If patients perceive care as empathetic, they may be less likely to report or perceive errors. This highlights the importance of fostering strong communication and empathetic interactions, but also cautions against interpreting patient confidence as the sole indicator of error-free care, especially when provider perspectives differ.

The observation from the Tukey test that patients with longer hospital stays (2–9 days and > 30 days) reported higher satisfaction than those with a one-day stay is an interesting finding. While plausible explanations include better adaptation to the hospital environment, improved staff relationships, or increased familiarity, as originally posited, these remain interpretations. Alternative or complementary factors, such as the cumulative effect of consistent care or trust-building over sustained interactions, could also contribute and warrant further investigation to refine strategies for enhancing satisfaction across all patient stay durations.

Conclusion

This study reveals a critical paradox within Al-Mouwasat University Hospital: while patients express high satisfaction, the healthcare providers central to delivering that care remain largely neutral towards the formal principles of Total Quality Management (TQM). This disconnect suggests that current patient satisfaction may be fragile, relying on the positive interpersonal dynamics of care rather than on a deeply embedded, systematic culture of quality. The divergence in attitudes towards scientific methods between doctors and nurses further underscores an inconsistent engagement with the core tools of TQM. Therefore, the essential challenge is not simply to maintain satisfaction, but to transform TQM from an abstract concept into a shared, operational value among all clinical staff. Moving beyond provider neutrality is the critical next step to ensure that high-quality patient outcomes are both sustainable and systematically achieved, rather than incidental.

Implications

Our findings suggest several actionable recommendations to facilitate TQM implementation. At the organizational level, this includes: (1) targeted training programs for doctors and nurses focused on leadership, statistical tools, and collaborative practices; and (2) systematic integration of statistical methods in daily hospital operations to support data-driven decision-making.

However, for TQM to become truly institutionalized across the Syrian healthcare system, these organizational efforts must be supported by robust, top-down policy architecture. Therefore, we propose (3) the development of concrete policy-level mechanisms, such as:

• Establishing National Quality Standards: The Ministry of Health could develop and mandate a clear set of evidence-based quality and patient safety standards based on TQM principles. These standards would create a unified benchmark for performance that all healthcare facilities must strive to meet.

• Implementing a National Accreditation Strategy: A formal accreditation body could be created or empowered to assess hospitals against these national quality standards. Making accreditation status public and linking it to funding, reimbursement rates, or other incentives would shift TQM from a voluntary activity to a strategic necessity for survival and growth.

These steps, in combination with the aforementioned training and data integration, can address identified barriers and create a powerful enabling environment for TQM adoption. This study further supports evidence suggesting that such comprehensive quality initiatives enhance perceived care quality through improved environments, patient empowerment, and strengthened patient-provider relationships¹⁷.

Limitations

This study has several limitations. The sample size may not be representative of the entire hospital staff and patient population. Also, the small sample size has a direct impact on the consistency of opinions related to the years of experience of doctors, where almost all doctors were trainees. Additionally, the study’s reliance on self-reported data may introduce bias. Future research should include larger, more diverse samples and consider objective performance metrics.

Future research

Future research should explore the reasons behind the neutral stance of healthcare providers toward TQM through qualitative approaches such as interviews or focus groups. A multi-phase mixed-methods design could combine in-depth qualitative insights with quantitative validation to provide a comprehensive understanding of these attitudes. Additionally, comparative studies across regions with similar resource constraints could identify shared challenges and successful strategies, further informing TQM implementation efforts in low-resource settings.

Materials and methods

Participants and study design

A cross-sectional, analytical descriptive design was employed to collect and analyse data using appropriate statistical techniques. The study population consisted of doctors, nurses, and patients at Al-Mouwasat University Hospital, and a stratified random sampling method was used to select 390 participants for analysis. For healthcare providers, participants were selected proportionally across departments to ensure representation of various specialties. Patients were approached directly in collaboration with hospital staff to capture a comprehensive sample of hospital service recipients.. The inclusion of these three groups enables triangulation of perspectives, which enhances the comprehensiveness and reliability of the analysis. All methods were performed in accordance with the principles of the Helsinki Declaration. Informed consent was obtained from all participants, with healthcare providers providing written consent and patients providing verbal or written consent as appropriate. Confidentiality was ensured through anonymized data collection and secure storage. Ethical approval for the study was obtained from the Ethical Committee of Damascus University, Damascus, Syria with serial number (4886) on 26 Sep 2023.

Study scope

The study was conducted across hospitals comparable to Al-Mouwasat University Hospital, and were adopted as experimental hospitals. These experimental hospitals are Ibn Al-Nafis, Damascus Al-Mujtahid, and National University Hospitals. These hospitals were selected for their similar demographic, service profiles, and organizational structures to Al-Mouwasat, ensuring comparability of results. The final study was applied to Al-Mouwasat University Hospital. This means that while data from experimental hospitals contributed to the pilot phase, the primary focus and full implementation occurred at Al-Mouwasat University Hospital.

Measures

Data collection and sample design

The questionnaires were manually distributed to study participants (physicians, nurses, and patients) in three pilot hospitals with characteristics similar to Al-Mouwasat University Hospital in Damascus. These hospitals were Ibn Al-Nafis Hospital, Al-Mujtahid Hospital, and National University Hospital, chosen for their educational and general profiles and coverage of the specialties targeted in the study. A total of 1,200 questionnaires were distributed, and 897 valid responses were retrieved after excluding 303 incomplete or defective forms. This cross-sectional, analytical descriptive study employed a stratified sampling approach to recruit participants, ensuring representation across key stakeholder groups (doctors, nurses, and patients). Inclusion criteria for healthcare providers included active employment in public hospitals for at least one year, while patients were required to have received hospital care within the last six months. Exclusion criteria included incomplete surveys or lack of informed consent. Confidentiality was upheld by anonymizing all participant data and storing information securely, in compliance with ethical guidelines approved by the institutional review board. Responses were collected across various hospital departments, including ENT surgery, neurosurgery, orthopedic surgery, plastic surgery, and emergency services, over six months in 2023.

Questionnaire development and validation

The study employed a questionnaire designed in two sections:

1. The first section assessed the implementation of TQM principles from the perspective of hospital staff (physicians and nurses).

2. The second section evaluated patient satisfaction with the quality of healthcare services provided.

The questionnaire was developed following a comprehensive review of relevant literature and validated international instruments^9,23–25. It initially included 90 items for each group (hospital staff and patients), tailored to the study population and aligned with the research objectives. Face validity was ensured through expert review by statisticians and medical professionals at the University of Damascus. These experts evaluated the clarity, accuracy, and relevance of the questions, as well as their comprehensiveness in addressing research dimensions. Based on their feedback, filler questions were excluded, and certain items were rephrased for clarity.

Exploratory factor analysis (EFA)

The questionnaire we distributed in the three experimental hospitals consisted of 51 questions for healthcare workers (doctors and nurses). However, after exploratory factor analysis (EFA), the questionnaire was reduced to 42 questions, which were then distributed in the target hospital, Al-Mouwasat. The EFA was conducted to ensure the measurement tool was statistically consistent and effectively captured the study objectives. This analysis, performed on data collected from the pilot hospitals, identified five factors for healthcare providers and six factors for patients, reflecting distinct domains of TQM and patient satisfaction, respectively. Factor loadings exceeded 0.5 for all included items, and no items were removed due to low loading or redundancy, ensuring robust construct validity. For the patients’ questionnaire, it initially consisted of 48 questions distributed across the three experimental hospitals. After factor analysis, it was reduced to 41 questions and distributed in Al-Mouwasat. The dimensions of the healthcare workers’ questionnaire (for doctors and nurses) originally consisted of four dimensions before factor analysis but increased to five dimensions after the analysis, with changes in the number and distribution of questions. For the patients’ questionnaire, the number of dimensions remained the same before and after factor analysis, although the distribution and total count of questions across the dimensions changed.

Final questionnaire design

• For healthcare workers, the final questionnaire included 42 items across five domains:

  1. Patient interaction (8 items)
  2. Quality improvement (8 items)
  3. Training and data automation (10 items)
  4. Incentives and supervisor relations (7 items)
  5. Workflow (9 items)
• For patients, the final questionnaire consisted of 41 items grouped into six domains:

  1. Reception experience (5 items)
  2. Radiological and laboratory examinations (12 items)
  3. Physician interaction (5 items)
  4. Nurse interaction (4 items)
  5. Health condition follow-up (6 items)
  6. Hospital stay (9 items)

Implementation at Al-Mouwasat University Hospital

Following the pilot study, the finalized questionnaires were distributed at Al-Mouwasat University Hospital over three months in 2023. A total of 400 questionnaires were distributed manually among physicians, nurses, and patients. Of these, 293 valid responses were retrieved (92 from physicians, 96 from nurses, and 105 from patients), achieving a response rate of 73%. The feedback encompassed various hospital departments, such as ENT surgery, neurosurgery, orthopedic surgery, plastic surgery, and emergency services. The first questionnaire evaluated TQM application from healthcare workers’ perspectives, while the second assessed patient satisfaction with healthcare quality and services.

Statistical analysis

The data were exported from Questionnaire to Excel, and analyses were performed using Statistical Package for Social Sciences software package (SPSS Inc., Chicago, IL, USA) version 23. Independent One-way analysis of variance (ANOVA) and independent t-student test was performed to consider the overall differences in mean opinions across groups. The Mann–Whitney test, Kruskal–Wallis test, Dunn’s test, and Tukey test, were applied to identify significant differences in opinions across groups. and P < 0.05 was taken as a statistically significant association. Using GPower version 3.1.9.7 with a 95% confidence level, groups number equals 3 and effect size of 0.2, the required sample size is 390.

Sample size

The sample size was determined using the GPower software, which identified the optimal number of participants to be selected from each category (physicians, nurses, and patients). The software calculated a total sample size of n = 390, based on the study’s objective of detecting differences among the groups within the study population. Of these, 92 participants were physicians, 96 were nurses, and 105 were patients, reflecting proportional representation based on their respective populations within the hospital. The opinions of the study participants were collected regarding the research questions and objectives using a three-point Likert scale, categorized into the following ranks: "Disagree," "Neutral," and "Agree."

This calculation was performed under the assumption of a small effect size (d = 0.2) as defined by Cohen’s statistical criteria, indicating that the study aims to capture differences of 0.2 or greater within the population. The significance level (α\alpha) was set at 0.05, and the test power was set at 95%. The following settings were applied.

Author contributions

AE, JA, AH, JS, have participated in writing the manuscript. AE, JA, AH, JS reviewed the literature. AE, YAZ, FAT did the statistics and the relevant table. AE, EK, YAZ, JA, AH, JS, FAT critically and linguistically revised the manuscript. AE, JA, AH, JS contributed to revision of the manuscript. AE, JA prepared and revised the final manuscript. FAT, YAZ, EK supervised the conduct of the study. All authors read and approved the final manuscript.

Funding

The authors received no specific funding for this work.

Data availability

All data generated or analysed during this study are included in this published article.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval

Ethical approval for the study was obtained from the Ethical Committee of Damascus University, Faculty of Science, Syria with serial number (4886) on 26 Sep 2023.

Informed consent

Written informed consent was obtained from all patients for the publication of this study and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal on request.