Faculty of Nursing, University of Kufa, Najaf Governorate, Kufa, Najaf, 540011, Iraq
*Corresponding Author’s Email: Mohammeda.aljanabi@uokufa.edu.iq
ABSTRACT
Keywords: Emergency; Challenge; Knowledge of Nurses; Triage Systems
INTRODUCTION
Triage is an important phase in emergency care that involves the listing of patients based on the urgency of their health conditions to facilitate an effective treatment. The method is important in dealing with the rising demand for emergency health care services, which are often challenged by issues of patient congestion and a shortage of resources (Adhikari et al., 2024). Triage systems have evolved to reduce mortality, improve patient flow, and optimise resource allocation, making them a staple in modern emergency departments (EDs) (Wolf et al., 2025). The effective use of triage systems depends on an integrated approach comprising the knowledge, skills, and decision-making capacities of emergency nurses (Al Dhefeeri et al., 2024). The roles of emergency nurses in triage are dynamic and challenging, requiring fast and accurate clinical assessments in stressful environments.
Research has shown that the ability of nurses to perform triage is significantly associated with patient outcomes and also with the overall functioning of emergency departments (Oh & Jung, 2024). However, the actual implementation of triage always faces various challenges (Khaleghi et al., 2022). Among such challenges are inadequate training, limited resources, and heterogeneity in nursing staff experience levels. These barriers must be addressed to ensure patients receive appropriate care in the timely manner required by their medical condition (Fekonja et al., 2023). At a global level, the introduction of triage systems has been accompanied by efforts to standardise practice and to enhance education for nurses (Gorick, McGee & Smith, 2025; Van Hecke et al., 2025). While high-income countries have made significant advances in the introduction of complex triage frameworks, many low- and middle- income countries face continued challenges in implementing such systems (Wolf et al., 2025). These challenges are often compounded by factors such as high patient-to-nurse ratios, insufficient infrastructure, and a lack of continuing education opportunities for health professionals (Chen et al., 2022). The present study explores the relationship between nursing knowledge and challenges faced in implementing triage systems within emergency departments.
Previous studies have focused primarily on individual aspects of triage, such as training and system architecture, with less attention paid to the interconnection between knowledge gaps and barriers to implementation. This gap in the current literature calls for a comprehensive analysis that treats both aspects as interrelated variables influencing the performance of triage systems (Seo, Lee & Jang, 2024). Nurse knowledge in triage includes principles, categories, and clinical applications. The ability to triage a patient requires knowledge of assessment tools, the ability to prioritise care based on severity, and the ability to communicate effectively with multidisciplinary teams. The main principles involve quick assessment and categorising patients into levels such as red (immediate care), yellow (delayed care), green (minor injuries), and black (deceased). These categories help healthcare teams allocate resources efficiently in emergencies or mass casualty events. Tools such as the Simple Triage and Rapid Treatment (START) system and the Emergency Severity Index (ESI) assist nurses in classifying patients based on the severity of their conditions, ensuring timely interventions. In clinical settings, triage is crucial for nurses to make rapid decisions regarding patient care, especially in emergency departments or during disasters. Nurses utilise various assessment tools, such as vital sign measurements and severity scales, to determine a patient’s priority level (Bazyar et al., 2020). Effective communication with multidisciplinary teams is key to ensuring coordinated care. Nurses must relay critical information quickly to other healthcare providers to ensure that patients receive the appropriate care based on their triage classification. This collaboration improves patient outcomes and reduces delays in treatment. Evidence has shown that structured training programs can enhance nurses' competencies; however, the sustainability of these improvements often depends on the availability of ongoing support and resources (Bahlibi et al., 2022).
On the other hand, the challenges in implementation expose systemic and organizational issues that impede the consistent execution of triage protocols (Yi, Baik & Baek, 2025). Contributory factors to this problem are inadequate staffing, lack of access to current guidelines, and weak monitoring and evaluation systems (Bijani & Khaleghi, 2019). All these challenges require a concerted effort by a group of policymakers, healthcare managers, and frontline personnel.
Significance of the Study
The importance of this study is marked by its potential for informing practice in order to improve triage methods within EDs. By identifying the relationship between nurse knowledge and challenges in implementation, the findings can guide the development of tailored training programmes, resource allocation strategies, and policy frameworks. This study has also contributed to the broader discourse in healthcare quality improvement by emphasizing the role of evidence-based approaches in addressing systemic inefficiencies (Anaraki et al., 2024). A key objective of this study is to determine how demographic factors such as age, education level, and years of experience relate to nurse knowledge and to the facilitation or hindrance of overcoming implementation barriers. Understanding these relationships can help in the design of interventions that are both context-specific and scalable. For example, novice nurses would benefit by being included in mentorship programmes, while the veteran staff would have to undertake refresher courses to be updated on the new triage guidelines that keep evolving (Elgazzar, 2021).
Through an exploration of the relationship between knowledge and the challenges associated with implementation, this study provides important perspectives on how healthcare systems can adapt their operations in response to changing demands and constraints. Such perspectives are particularly important in the face of global health crises, where the capacity of emergency departments to act effectively is often tested. Moreover, the inclusion of evidence from diverse contexts increases the credibility and applicability of this research. Comparative studies of triage methods in different health care systems can highlight best practices and enable the spread of knowledge to settings with similar challenges. It follows principles of global health equity—that all patients receive appropriate and timely emergency care regardless of their geopolitical situation (Çelik, Mollaoğlu & Hastaoğlu, 2025; Seda, 2020).
The aim of this research is to connect the theoretical framework with practical applications in the implementation of triage. By offering concrete recommendations based on empirical data, this study aims to give nurses and healthcare institutions the opportunity to overcome obstacles in a quest to improve the quality of care offered at the emergency departments. The findings are expected to be of considerable interest to a wide audience, including clinicians, educators, researchers, and policymakers, and will encourage a collective commitment to improving outcomes in emergency care. In summary, this study addresses a gap in the current literature by examining the twofold nature of nursing knowledge and the challenges associated with implementation within triage systems. Its findings have the potential to drive meaningful change in emergency care practices, contributing to the broader goal of achieving excellence in healthcare delivery.
A descriptive correlational study design was chosen as it aligns with the objectives of evaluating the relationship between nurses' knowledge and implementation challenges regarding triage systems.
A non-probability representative sample of 230 nurses working in governmental hospitals was selected. The sample size was determined based on a power analysis to ensure adequate representation of the population. Participants were recruited from emergency departments across Al-Najaf Al-Ashraf, Iraq (governmental hospitals). The unique cultural and social dynamics within Iraqi healthcare settings, such as high patient-to-nurse ratios and resource limitations, play a critical role in shaping nurses' experiences and challenges in implementing triage systems."
The structured questionnaire employed in this research was developed from literature and expert panel comments to ensure content validity. The content validity of the study instruments is determined by the panel of six) experts, who had more than five years’ experience in their field to investigate the content of the nursing intervention. The panel of experts was composed of four faculty members from the College of Nursing, University of Kufa; one faculty member from the College of Medicine, University of Kufa; and one representative from the Ministry of Health. Moreover, the mean of experience years for the expert panel is 18.2 years. Those experts were asked to review the instrument for content, clarity, relevancy, and adequacy; some items were excluded, and others were added after a face-to-face discussion with each expert, and after the instrument was considered valid after taking all the comments and recommendations into consideration. 100% of experts agreed upon the final draft. The knowledge domain was based on Bloom's Taxonomy as a model for cognitive understanding of triage systems. Similar questionnaire-based studies have also been employed in recent nursing research evaluating triage competencies and system issues (Bahre et al., 2024; Zagalioti et al., 2025).
The questionnaire was pre-tested on a pilot sample of 20 nurses to ensure clarity and relevance. Feedback from the pilot study informed revisions to enhance question comprehensibility and alignment with the study objectives. The study employed a structured questionnaire consisting of three sections:
The questionnaire was reviewed by a panel of experts in nursing and emergency care to ensure content validity. Reliability was tested using Cronbach's Alpha, achieving a score of 0.85, indicating high internal consistency.
Data were collected between October 30, 2023, and May 2, 2024, using face-to-face structured interviews. Participants provided informed consent, and interviews were conducted in a private setting to ensure confidentiality. To minimise respondent bias, participants were assured of anonymity, and the interview setting was made private to encourage honest responses. Additionally, efforts were made to include nurses with diverse levels of experience and backgrounds.
The data was analysed using SPSS (version 26). Descriptive statistics (means, standard deviations) were calculated to summarise demographic and questionnaire data. Inferential tests (Pearson correlation, chi-square) were employed to examine relationships between variables. Fisher's exact test (use when the frequency of any categories is less than five).
The research obtained ethical exemption from the Ministry of Higher Education and Scientific Research University of Warith AI-Anbiyaa College of Nursing Ethical Approval Committee, Indonesia, with reference number 210 on 25th August 2023.
RESULTS
Variables | Categories | Frequency | Percentage (%) |
Age | <= 20.00 | 9 | 3.9 |
21.00 - 25.00 | 128 | 55.7 | |
26.00 - 30.00 | 81 | 35.2 | |
31.00 - 35.00 | 7 | 3.0 | |
36.00 - 40.00 | 5 | 2.2 | |
Mean+ SD | 25.09 | 3.31 | |
Gender | Male | 115 | 50.0 |
Female | 115 | 50.0 | |
Total | 230 | 100.0 | |
Level of Education | Secondary School | 53 | 23.0 |
Diploma | 116 | 50.4 | |
Graduated | 61 | 26.5 | |
Total | 230 | 100.0 | |
Year of Experience in Emergency | 1 year | 79 | 34.3 |
2-5 years | 136 | 59.1 | |
6-11 years | 5 | 2.2 | |
12-17 years | 2 | 0.9 | |
18 and more | 8 | 3.5 | |
Total | 230 | 100.0 | |
Training Course | Yes | 158 | 68.7 |
No | 72 | 31.3 | |
Total | 230 | 100.0 |
Table 1 reveals that half of the study sample are (50%) males and within the age group (21-25) years old (55.7%); (50.4%) of the study nurses had a diploma level of education, and (59.1%) had (2-5) years of experience. In relation to the training courses, the results also indicated that 68.7% of nurses reported that they received training about the implementation of the triage system in the emergency department.
Sl No | Knowledge Questions | Resp. | F. | % | MS | SD | RS | Asses. |
1 | Triage is | False | 78 | 33.9 | 1.66 | 0.47 | 83 | Pass |
True | 152 | 66.1 | ||||||
2 | Classification of patients is based on | False | 87 | 37.8 | 1.62 | 0.49 | 81 | Pass |
True | 143 | 62.2 | ||||||
3 | How many levels of triage | False | 153 | 66.5 | 1.33 | 0.47 | 67 | Fail |
True | 77 | 33.5 | ||||||
4 | One of the levels of sorting is | False | 119 | 51.7 | 1.48 | 0.50 | 74 | Fail |
True | 111 | 48.3 | ||||||
5 | Criteria of resuscitation is | False | 119 | 51.7 | 1.48 | 0.50 | 74 | Fail |
True | 111 | 48.3 | ||||||
6 | Criteria of emergent is | False | 93 | 40.4 | 1.60 | 0.49 | 80 | Pass |
True | 137 | 59.6 | ||||||
7 | Criteria of urgent is | False | 113 | 49.1 | 1.51 | 0.50 | 75 | Pass |
True | 117 | 50.9 | ||||||
8 | Criteria of less urgent is | False | 109 | 47.4 | 1.53 | 0.50 | 76 | Pass |
True | 121 | 52.6 | ||||||
9 | Criteria of non-urgent is | False | 119 | 51.7 | 1.48 | 0.50 | 74 | Fail |
True | 111 | 48.3 | ||||||
10 | For the sorting process you must first evaluate | False | 140 | 60.9 | 1.39 | 0.49 | 70 | Fail |
True | 90 | 39.1 | ||||||
11 | Goals of triage is | False | 136 | 59.1 | 1.41 | 0.49 | 70 | Fail |
True | 94 | 40.9 | ||||||
12 | Factor can effect on triage of patient | False | 135 | 58.7 | 1.41 | 0.49 | 71 | Fail |
True | 95 | 41.3 | ||||||
13 | Advantages of Triage are | False | 105 | 45.7 | 1.54 | 0.50 | 77 | Pass |
True | 125 | 54.3 | ||||||
14 | Overall, Knowledge | Pass | 128 | 55.7 | 1.50 | 0.18 | 75 | Good |
Fail | 102 | 44.3 | ||||||
Total | 230 | 100.0 |
MS= mean of the score, SD = standard deviation, F. = Frequency, % = Percentage, R.S. =Relative sufficiency, assess = Assessment, Fail = MS less than (1.5), Pass = MS equal or more than (1.5).
Table 2 indicates that among the nurses working in the emergency department, approximately half demonstrated a good level of knowledge (55.7) regarding triage.
Sl No | Challenges Questions | Resp. | F. | % | MS | SD | Asses. |
1 | I think that there are major challenges and obstacles that will face the implementation of the triage system at paediatric emergency department | Strongly Disagree | 15 | 6.5 | 3.63 | 1.20 | High |
Disagree | 36 | 15.7 | |||||
Neutral | 24 | 10.4 | |||||
Agree | 99 | 43.0 | |||||
Strongly Agree | 56 | 24.3 | |||||
2 | The working environment is appropriate and suitable for the possibility of the triage system implementation. | Strongly Disagree | 24 | 10.4 | 3.32 | 1.14 | High |
Disagree | 24 | 10.4 | |||||
Neutral | 65 | 28.3 | |||||
Agree | 88 | 38.3 | |||||
Strongly Agree | 29 | 12.6 | |||||
3 | The decision-makers motivated to implement the triage system | Strongly Disagree | 9 | 3.9 | 3.53 | 1.12 | High |
Disagree | 35 | 15.2 | |||||
Neutral | 64 | 27.8 | |||||
Agree | 70 | 30.4 | |||||
Strongly Agree | 52 | 22.6 | |||||
4 | The nursing staff currently in my department is sufficient to implement the triage system | Strongly Disagree | 29 | 12.6 | 3.44 | 1.30 | High |
Disagree | 26 | 11.3 | |||||
Neutral | 43 | 18.7 | |||||
Agree | 79 | 34.3 | |||||
Strongly Agree | 53 | 23.0 | |||||
5 | The nursing staff has the real motivation to apply the triage system | Strongly Disagree | 6 | 2.6 | 3.69 | 1.06 | High |
Disagree | 27 | 11.7 | |||||
Neutral | 58 | 25.2 | |||||
Agree | 81 | 35.2 | |||||
Strongly Agree | 58 | 25.2 | |||||
6 | Cases overcrowding is one of the obstacles to the implementation of the triage system | Strongly Disagree | 14 | 6.1 | 3.77 | 1.22 | High |
Disagree | 30 | 13.0 | |||||
Neutral | 29 | 12.6 | |||||
Agree | 78 | 33.9 | |||||
Strongly Agree | 79 | 34.3 |
7 | I think the public has enough idea about how the triage system works | Strongly Disagree | 35 | 15.2 | 3.17 | 1.22 | High |
Disagree | 32 | 13.9 | |||||
Neutral | 40 | 17.4 | |||||
Agree | 106 | 46.1 | |||||
Strongly Agree | 17 | 7.4 | |||||
8 | There is a strong desire among the public to implement the triage system | Strongly Disagree | 21 | 9.1 | 3.36 | 1.08 | High |
Disagree | 26 | 11.3 | |||||
Neutral | 51 | 22.2 | |||||
Agree | 113 | 49.1 | |||||
Strongly Agree | 19 | 8.3 | |||||
9 | The department has material resources that allow the triage system to be easily implemented | Strongly Disagree | 9 | 3.9 | 3.60 | 1.11 | High |
Disagree | 27 | 11.7 | |||||
Neutral | 69 | 30.0 | |||||
Agree | 66 | 28.7 | |||||
Strongly Agree | 59 | 25.7 | |||||
10 | Human security controls are available that can control any mess in the triage hall and contribute to the time limitations of the triage system | Strongly Disagree | 13 | 5.7 | 3.73 | 1.11 | High |
Disagree | 20 | 8.7 | |||||
Neutral | 42 | 18.3 | |||||
Agree | 95 | 41.3 | |||||
Strongly Agree | 60 | 26.1 | |||||
11 | Triage room contain adjustment banners that guide people and help to understand triage working method | Strongly Disagree | 40 | 17.4 | 3.35 | 1.34 | High |
Disagree | 20 | 8.7 | |||||
Neutral | 28 | 12.2 | |||||
Agree | 104 | 45.2 | |||||
Strongly Agree | 38 | 16.5 | |||||
12 | There is a sufficient time for nurses to implement triage at emergency | Strongly Disagree | 11 | 4.8 | 3.77 | 1.03 | High |
Disagree | 14 | 6.1 | |||||
Neutral | 47 | 20.4 | |||||
Agree | 103 | 44.8 | |||||
Strongly Agree | 55 | 23.9 | |||||
13 | Work load at emergency impedes triage implementation | Strongly Disagree | 45 | 19.6 | 3.48 | 1.40 | High |
Disagree | 8 | 3.5 | |||||
Neutral | 22 | 9.6 | |||||
Agree | 102 | 44.3 |
Strongly Agree | 53 | 23.0 | |||||
Overall Challenges | 3.53 | 0.47 | High Challenges | ||||
MS = mean of the score, SD = standard deviation, F = frequency, % = percentage, assess = assessment, High = Cut off more than (2.66).
Table 3 reveals the subjects' response regarding overall challenges affecting the implementation of triage in the emergency department: the majority of them have a high level of challenges.
Challenges | ||
C.C. | P-value | |
Knowledge | 0.13 | 0.048 S |
Age | -0.19 | 0.004 S |
Gender | -0.006 | 0.923 NS |
Year of experience | -0.065 | 0.327 NS |
Level of Education | 0.059 | 0.37 NS |
Training Course | 0.006 | 0.928 NS |
C.C. = Correlation Coefficient, S = Significant, NS = non-significant
Table 4 demonstrates that there is significant correlation between the challenges and the nurse’s knowledge and age at p-value (0.048, 0.004), respectively. However, there is a non-significant correlation which observed between challenges and gender, years of experience, level of education and training sessions at p-values of 0.923, 0.723, 0.370 and 0.006, respectively.
Variable | Categories | Statistics | Knowledge | F.E.T. | P-value | |
Poor | Good | |||||
Age | <= 20.00 | F. | 8 | 1 | 6.1467 | 0.194 NS |
% | 88.9% | 11.1% | ||||
21.00 - 25.00 | F. | 74 | 54 | |||
% | 57.8% | 42.2% | ||||
26.00 - 30.00 | F. | 40 | 41 | |||
% | 49.4% | 50.6% | ||||
31.00 - 35.00 | F. | 4 | 3 | |||
% | 57.1% | 42.9% | ||||
36.00 - 40.00 | F. | 2 | 3 | |||
% | 40.0% | 60.0% | ||||
F.E.T. = Fisher's exact test (use when the frequency of any categories is less than five)
Table 5 shows that there is no significant relationship between total nurse’s knowledge and age at p-value (0.194).
Variable | Categories | Statistics | Knowledge | Chi- square | df | P-value | |
Poor | Good | ||||||
Gender | Male | F. | 66 | 49 | 0.282 | 1 | 0.595 NS |
% | 57.4% | 42.6% | |||||
Female | F. | 62 | 53 | ||||
% | 53.9% | 46.1% | |||||
Table 6 shows that there is no significant relationship between total nurse’s knowledge and gender at p-value (0.595).
Variable | Categories | Statistics | Knowledge | Chi- square | P-value | |
Poor | Good | |||||
Level of Education | Secondary school | F. | 40 | 13 | 12.084 | 0.002 S. |
% | 75.5% | 24.5% | ||||
Diploma | F. | 61 | 55 | |||
% | 52.6% | 47.4% | ||||
Graduated | F. | 27 | 34 | |||
% | 44.3% | 55.7% | ||||
Table 7 illustrates that there is a significant correlation between total nurse’s knowledge and level of education at p-value (0.002).
Variable | Categories | Statistics | Knowledge | F.E.T. | P-value | |
Poor | Good | |||||
Year of experience in emergency | 1 year | F. | 43 | 36 | 4.367 | 0.287 NS |
% | 54.4% | 45.6% | ||||
2-5 years | F. | 80 | 56 | |||
% | 58.8% | 41.2% | ||||
6-11 years | F. | 2 | 3 | |||
% | 40.0% | 60.0% | ||||
12-17 years | F. | 0 | 2 | |||
% | 0.0% | 100.0% | ||||
18 and more | F. | 3 | 5 | |||
% | 37.5% | 62.5% | ||||
Table 8 shows that there is no significant relationship between total nurse’s knowledge and years of experience in emergencies at p-value (0.287).
Variable | Categories | Statistics | Knowledge | Chi- square | df | P-value | |
Poor | Good | ||||||
Training Course | Yes | F. | 100 | 58 | 11.933 | 1 | 0.0005 S |
% | 63.3% | 36.7% | |||||
No | F. | 28 | 44 | ||||
% | 38.9% | 61.1% | |||||
Table 9 shows that there is a significant relationship between total nurse’s knowledge and training session at p-value (0.0005).
DISCUSSION
The results of this study reveal that the majority of nurses in emergency departments possess moderate to excellent knowledge regarding triage systems, with approximately 55.7% demonstrating satisfactory understanding. This aligns with findings by Yadav and Thakur (2022), who reported that structured educational interventions significantly enhance nursing knowledge in emergency care. The moderate level of knowledge can be attributed to prior training programmes, as indicated by 68.7% of participants acknowledging previous exposure to triage education. However, gaps were identified in specific areas such as the classification of patients and criteria for resuscitation. These findings highlight the need for targeted training modules that address critical knowledge deficiencies. Previous studies support this observation. Malak, Al-Faqeer, and Yehia (2022) emphasised that comprehensive training tailored to triage protocols improves clinical judgement and decision-making among nurses (Phukubye, Mbombi, & Mothiba, 2021). noted that emergency nurses equipped with robust triage knowledge are better prepared to manage patient priorities effectively. While the current study indicates an overall excellent understanding of triage among nurses, it underscores the necessity of continual professional development to sustain and enhance these competencies. A more in-depth look reveals that the learning process in triage is not only dependent on formal education but also, to a significant extent, on experiential learning and mentorship. For example, nurses who frequently confront critical situations may develop practical insights that complement their theoretical knowledge.
The research identified significant barriers that impede effective triage system deployment. Among the major challenges were resource limitations, insufficient numbers of staff, and lack of support from decision-makers. These findings are in line with the conclusions of Bahlibi et al. (2022), which highlighted resource constraints as one major barrier to implementing triage in emergency departments. Besides, systemic inefficiencies—like overcrowding and the lack of an appropriate infrastructure—aggravate these challenges, as stated by Hammad et al. (2017). It also revealed that public awareness of triage systems is low and that such ignorance contributes to implementation difficulties. These findings are supported by previous observations made by Seda (2020), which indicate that the public's misperceptions of triage worsen the workload burden experienced by emergency nurses. Such challenges demand a multi-level approach in place, including raising public education on triage and increasing resource allocation in emergency departments. A closer look at the challenges reveals a potential gap between existing policies and their implementation in reality. While triage guidelines may be put on paper, their practical application is hindered by operational inefficiencies. Overcrowded emergency departments not only delay patient care but also put undue stress on nursing staff, leading to burnout and a lower adherence to triage guidelines.
A significant correlation was found between nurses' knowledge levels and the challenges of triage systems implementation. This finding was also mentioned by Kaakinen et al. (2016), who reported that nurses with good training and understanding of triage protocols meet fewer barriers in clinical practice. On the other hand, insufficient knowledge can lead to inadequacies and errors, further complicating the implementation process. The results show that a higher degree of knowledge helps nurses better navigate systemic barriers. For example, nurses with a solid understanding of triage principles are better able to prioritise care and efficiently utilise the limited availability of resources, as highlighted by Malak, Al-Faqeer and Yehia (2022) and Abbas, Mustafa and Abozaid (2023). Additionally, studies by Elgazzar (2021) and Phukubye, Mbombi and Mothiba (2021) emphasise that empowering nurses through education moderate’s implementation challenges, leading to improved patients’ outcomes. An interesting insight from this study is the role of continuous education in mitigating challenges. Nurses who had attended recent training sessions reported fewer challenges, suggesting that ongoing professional development acts as a buffer against systemic inefficiencies. However, the result raises questions about the accessibility and frequency of such training programmes, particularly in regions with limited resources. Policymakers must consider scaling up training initiatives to ensure sustained improvements in triage implementation. "Triage", a term originating from the French word meaning "to sort", refers to the process of prioritising patients in emergency care based on the severity of their medical conditions. This finding aligns with Abdul-Hussein and Mustafa (2024), who observed similar trends in Iraqi emergency departments. The table also highlights specific areas of weakness, such as resuscitation criteria, which require immediate attention in future training programmes. The challenges table underscores resource limitations and systemic inefficiencies as primary barriers. These findings are supported by Bahlibi et al. (2022), who identified similar obstacles in low-resource settings. The table's data suggest that addressing these challenges through policy reforms and resource allocation can significantly enhance the efficacy of triage systems. The table demonstrates a significant relationship between nurses' knowledge and the challenges they face. This observation is consistent with studies by Malak, Al-Faqeer and Yehia (2022) and Abbas Mustafa and Abozaid (2023), which highlight the role of education in overcoming systemic barriers. These findings highlight the need to combine targeted educational initiatives with organizational reforms, such as improved staffing and resource allocation, to enhance the sustainability of triage system implementation. Finally, this deeper analysis reaffirms the critical role of nursing knowledge and systemic support in the effective implementation of triage systems. While challenges persist, targeted interventions, informed by empirical evidence and contextual understanding, hold the potential to transform emergency care practices. By addressing both individual and systemic barriers, healthcare systems can achieve more equitable and efficient patient outcomes.
This study provides a framework for future research to further explore these relationships by its demonstration of dynamic interplay between knowledge, systemic challenges, and demographic variables.
Limitation
The generalisability of this study is hindered by the fact that it employed a non-probability sampling method, which may have an implication on the applicability of the results. Moreover, the study was carried out in a single geographic location (Al-Najaf Al-Ashraf, Iraq) that may restrict its applicability to other environments. Furthermore, the use of self-reporting may also yield response bias regardless of the confidentiality assurance measures that were implemented. Future research must adopt a multicentre design and include qualitative methods to further explore the problems associated with the implementation of triage.
CONCLUSION
The study results show that emergency department nurses have moderate knowledge of triage, with about half of them demonstrating adequate knowledge. However, most need more training to improve their competence. The principal impediments to the implementation of triage systems are staff shortages, lack of support from decision-makers, and low public awareness. From this study it is seen that knowledge and age are significantly associated with perceived barriers to implementation, while demographic factors such as level of education and training show strong associations with knowledge of triage. Future research could focus on investigating the long-term effects of training programmes on triage knowledge and practice. While short-term improvements are often visible immediately after training, it is equally important to examine whether these gains are sustained over extended periods and how they influence actual decision-making in high-pressure clinical settings. Such studies will provide deeper insights into the durability of training interventions and their overall impact on patient outcomes.
Another promising area for future inquiry lies in conducting comparative studies across different regions to identify best practices in triage implementation. Since healthcare systems vary significantly in terms of resources, policies, and cultural factors, comparative analysis can highlight which strategies are most effective and adaptable. This evidence would not only strengthen global standards of triage but also provide region-specific recommendations tailored to diverse healthcare environments.
Finally, exploring the integration of technological innovations, such as digital triage tools and artificial intelligence–based decision support systems, represents a crucial avenue for future work. These tools can help address systemic challenges such as staff shortages, inconsistent application of protocols, and delays in patient care. Research into the feasibility, effectiveness, and ethical considerations of such technologies could pave the way for more efficient and equitable triage practices worldwide.
Conflict of Interest
The authors declare that they have no competing interests.
ACKNOWLEDGEMENT
The authors extend their sincere gratitude to all the nurses who participated in this study, as well as to the administrative and academic staff at the hospitals involved for their generous cooperation. They are particularly grateful for providing the resources and guidance necessary to conduct this study.
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