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The purpose of this realist review was to assess what works, for whom and in what context, regarding strategies that influence nurses' behaviour to improve triage quality in emergency departments (ED).
Realist review protocol.
This protocol follows the PRISMA‐P statement and will include any type of study on strategies to improve the triage process in the ED (using recognized and validated triage scales). The included studies were examined for scientific quality using the Mixed Methods Appraisal Tool. The framework for this realist review is based on the Behaviour Change Wheel (BCW) and the context‐mechanism‐outcome (CMO) models.
Nurses and ED decision makers will be informed on the evidence regarding strategies to improve the quality of triage and the factors required to maximize their effectiveness. Research gaps may also be identified to guide future research projects on the adoption of best practices in ED nursing triage.
Keywords: behaviour change wheel (BCW), emergency departments (ED), nurse, quality improvement, realist review, triage
Emergency departments (ED) are one of the main access points to the healthcare system (Wolf et al., 2018). Patients may consult the ED for various reasons such as major trauma, chest pain or mental health problems. Accurate triage is critical to ensure proper assessment and prioritization of each patient based on the severity of their symptoms and to maintain a safe and efficient patient flow (Visser & Montejano, 2018; Wolf et al., 2018). The priority level assigned to each patient following triage is directly linked to how quickly the patient should be treated, based on the severity of symptoms (Visser & Montejano, 2021). In other words, the sickest patient should receive care first. In order to achieve this, the triage nurse is guided by clinical judgement, experience, intuition and triage scales.
Different triage scales have been developed across the globe to achieve this goal. The validated scales that are the most commonly used in practice are the Canadian Triage and Acuity Scale (CTAS) (Bullard et al., 2014; Mirhaghi, Heydari, Mazlom, & Ebrahimi, 2015), the Emergency Severity Index (ESI) (Mirhaghi, Heydari, Mazlom, & Hasanzadeh, 2015), the Australasian Triage Scale (ATS) (Ebrahimi et al., 2015; Hodge et al., 2013) and the Manchester Triage Systems (MTS) (Mirhaghi et al., 2017). Guidelines on how to use these scales are available so that nurses can assign the appropriate priority level to each patient (AIIUQ, AGIUP, AMUQ, & ASMUQ, 2011; Bullard et al., 2008).These scales make it possible to assign the appropriate level of management priority, from P‐1 (urgent) to P‐5 (non‐urgent) (Solheim, 2016; Visser & Montejano, 2021; Zimmermann, 2006).
The priority level assigned by the triage nurse is one of many significant factors that determine the wait time for medical care or re‐evaluation by a nurse (e.g. for CTAS: P‐1: immediate, P‐2: 15 min, P‐3: 30 min, P‐4: 1 h, P‐5: 2 h). In this regard, patients sent back to the waiting room after triage may become unstable after prolonged wait time (Hodge et al., 2013). In such a situation, it is important for the triage nurse to reassess patients in the waiting room, as their health status is dynamic and may deteriorate. All patients waiting for a complete assessment of their health status should be monitored and their priority level updated according to any changes in their condition (Solheim, 2016). An error in triage can have negative impacts on priority assignation, patient flow in the ED and satisfaction with care (De Freitas et al., 2018; Hitchcock et al., 2014; Pollyane Liliane et al., 2016; Swedish Council on Health Technology, 2010).
It may be difficult to quantify the scope of the triage error problem (i.e. mis‐triage). Even though significant time and effort have been devoted to designing triage scales, less attention has been paid to assessing triage quality (Zachariasse et al., 2018; Zachariasse et al., 2019). Current literature on mis‐triage includes undertriage and overtriage. In most regions of the world using a five‐level grading scale, undertriage can be defined as ‘assigning patients to a triage tier of lower acuity on arrival (Registered Nurse assigned) than at close of encounter (physician‐assigned)’ (Oh & Kim, 2021, p. 2). Compared to overtriage, mild cases are classified as severe cases, resulting in patients with more stable conditions being seen before patients with more critical conditions. These triage errors result in patients spending more time in the ED and more hospitalizations. This is essentially due to a deterioration in patient condition during ED wait time, compared with those who received error‐free triage (Ausserhofer et al., 2021). Other authors suggest that triage errors may increase the risk of mortality up to 18% (Ahmad et al., 2006; Hitchcock et al., 2014; Najafi et al., 2019; Ryan et al., 2016; Stanfield, 2015). Bearing this in mind, it is important to ensure that continuous improvement processes are in place to monitor triage quality.
Several strategies have been recommended to optimize nursing practices with respect to triage, including audit and feedback (Robbie & Martin, 2013), education (Javadi et al., 2021; McNally, 1996), reminder systems, simulation (Terenzi, 2000; Uslu et al., 2019) and electronic decision‐support tools (Agnihotri et al., 2021) with artificial intelligence (IA). These strategies could influence nurses' capacity, motivation and opportunities to apply best practices in triage, referring to the mechanisms by which they operate to change clinician behaviours.
According to Pawson (2013), there are four contextual domains (individual, interpersonal relations, institutional setting, infrastructure) that might act as barriers to the implementation of best practices by healthcare professionals (see Table 1 ). For example, prior triage training and experience, quality of communication among team members, adequacy of human resources and access to required equipment (e.g. monitors, stretchers) (Solheim, 2016) and the population encountered (e.g. metropolitan vs, metropolitan vs. rural ED; paediatric vs. adult hospital) may influence the nurse's decision‐making process and should be considered when selecting strategies to improve the quality of nursing triage.
Realist terminology applied to this review based on the CMO model and BCW
Individual: nurses' education (Hodge et al., 2013), experience (Hardy & Calleja, 2019), belief (Göransson et al., 2006), intuition (Göransson et al., 2008; Simmons, 2010), triage fatigue (empathy burnout) (Reay et al., 2020; Yoder, 2010).
Interpersonal relations: nurses/other professionals (partnership, communication), nurses/patients (partnership, communication) (Burgess et al., 2019).
Institutional settings: type of computerized tool used (McNair, 2005), staffing (nurse/patient ratio), environment and appropriate triage equipment (Burgess et al., 2019; Solheim, 2016), local guidelines on nursing triage.
Infrastructure: type of emergency (Hardy & Calleja, 2019), ED crowding (Hitchcock et al., 2014; van der Linden et al., 2016).
Mechanisms refer to the sources of the behaviour that need to be modified with the use of specific strategies to help nurses triage patients accurately.
The sources of the behaviour are (first layer of BWC):
Capability is defined as ‘the individual's psychological and physical capacity to engage in the activity concerned. It includes having the necessary knowledge and skills’ (West et al., 2011, p. 4).
Motivation is defined as ‘all those brain processes that energize and direct behaviour, not just goals and conscious decision‐making. It includes habitual processes, emotional responding, as well as analytical decision‐making’ (West et al., 2011, p. 4).
Opportunity is defined as ‘all the factors that lie outside the individual that make the behaviour possible or prompt it’ (West et al., 2011, p. 4).
Potential strategies*:
Second layer of BWC
education (Delnavaz et al., 2018; Dong et al., 2007; Fry & Stainton, 2005; Hitchcock et al., 2014), persuasion, incentivization, training (Hardy & Calleja, 2019; Uslu et al., 2019), enablement, modelling, artificial intelligence (Agnihotri et al., 2021), environmental restructuring, restrictions.Third layer of BWC
guidelines (Burgess et al., 2019), environmental/social planning, communication/marketing (Hardy & Calleja, 2019), legislation, service provision, regulation (Burgess et al., 2019), fiscal measures.*It is important to remember that not all aspects of the BCW may be available in the literature. However, each of the strategies listed in the literature will be classified according to the aspects of the BCW.
The outcome depends on the contexts and mechanisms used (Pawson, 2006, p. 23). The final outcome is triage quality.
The following outcomes will be targeted in this review:
Adequate priority assignation (Hitchcock et al., 2014),Patient flow (De Freitas et al., 2018; Kienbacher et al., 2022; Swedish Council on Health Technology, 2010),
Patient satisfaction (Pollyane Liliane et al., 2016), Admission rate, adverse events and mortality (Ahmad et al., 2006), Length of stay (LOS) ED (McKenna et al., 2019), Health resource use (Ray et al., 2003),Proportion of patients that Left Without Being Seen (LWBS) (Shah et al., 2020; Spencer et al., 2019).
To date, there has been no comprehensive review of the strategies available to change nurses' behaviour to adopt best practices in triage, even though this has been identified as an important research and clinical gap (Bero et al., 1998; Corbett & Quinn Griffin, 2016; George et al., 1993; Hodge et al., 2013; Malmström et al., 2017; Michie et al., 2012). Furthermore, there is a lack of data regarding which strategies will improve triage quality (outcome), in what context, and for which nurses these strategies will be effective, as well as the mechanisms that may explain their effectiveness. Accordingly, considering that many professionals and factors are involved in the improvement of ED triage, a realist review will be undertaken for this synthesis (Pawson et al., 2005).
This realist review aims to assess what works, for whom and in what context when it comes to strategies to improve triage quality in the ED. The realist review will synthesize evidence and focused on explaining why and how strategies and their mechanisms may or may not work (outcome), and in what context (Bucknall et al., 2012; Geoff et al., 2013). Realist reviews seek to unpack the relationships between context, mechanism and outcome (CMO) (Geoff et al., 2013).
Throughout this process, we will perform an iterative review based on the Behaviour Change Wheel (BCW) model (Michie et al., 2014), reframed into CMO configurations, which is more explicitly detailed later on in Stage 1: Clarify the Scope.
Our research question and protocol were developed in collaboration with a research team including experts in nurse triage (n = 3), emergency nursing (n = 3) and emergency medicine (n = 2), implementation science and quality improvement (n = 4). Team members also provided their opinion and insights about the search strategy, which was adjusted accordingly. Our realist review will follow the Realist And Meta‐narrative Evidence Syntheses: Evolving Standards (RAMESES) (Geoff et al., 2013) and our protocol follows the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses Protocols guidelines (PRISMA‐P) (Moher et al., 2015). We registered the protocol with the Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/S59Q6).
The different stages of this realist review will follow the five steps proposed by Pawson (Pawson et al., 2005): (1) clarify the scope; (2) search for evidence; (3) appraise primary studies and extract data; (4) synthesize evidence and draw conclusions; (5) disseminate, implement and evaluate.
This step involves identifying the existing theories or frameworks that explain how the strategies to improve triage quality are meant to work. This realist review will adhere to the BCW framework (Michie et al., 2014; West et al., 2011). The BCW (Figure 1 ) is a synthesis of 19 frameworks of behaviour change found in the literature (West et al., 2011). The BCW consists of three layers that may impact behaviour: (1) barriers to the implementation of a behaviour (behaviour sources), (2) intervention functions and (3) policy categories. Table 1 provides a summary of realist terms used in the context‐mechanism‐outcome (CMO) model and how they are linked to this review project.
Behaviour change wheel (West et al., 2011)
The first layer, the sources of the behaviour to be changed or optimized, which in this review concerns the adoption of best practices for quality triage, are the cornerstone of the BCW. The sources of the behaviour layer are divided into three sub‐layers: capability (physical and psychological), opportunity (social and physical) and motivation (automatic and reflective). Barriers from the contextual domain of the CMO model (individual, interpersonal relations, institutional settings, infrastructure) can be grouped under sources of the behaviour within the BCW. Then, the mechanism component of the CMO model may explain how strategies to change or optimize nurses' behaviour may work. To achieve this goal, the nurse must develop physical capabilities or triage skills (e.g. perform all the steps of a triage, know about triage and the different health problems) and psychological capability (e.g. ability to work under pressure and continuous stress). The required conditions or opportunities to implement the expected behaviour must also be present. For example, nurses need social opportunities involving other people and organizations (e.g. clear communication mechanisms regarding the triage process, culture of continuous improvement in triage) (West & Michie, 2020) as well as physical opportunities (e.g. a triage room with adequate equipment) to implement changes. Finally, to achieve behaviour change, both reflective motivation (e.g. knowledge, positive belief with regard to the behavioural target) and automatic motivation (e.g. clear triage guidelines, culture for continuous improvement of triage performance) processes are needed. These can be fostered through the improvement of capabilities and opportunities.
The second layer of the BCW is intervention functions and consists of nine types of interventions, namely education, persuasion, incentivization, coercion, training, enablement, modelling, environmental restructuring and restrictions. These can be directly linked to the sources of the behaviour that needs to change. Similarly, the third layer consists of seven types of policy categories: guidelines, environmental/social planning, communication/marketing, legislation, service provision, regulation and fiscal measures.
In this realist review, the BCW will identify intervention functions and policy categories that can be used to improve capability, motivation and opportunity in nurses and, ultimately, support behaviour change or optimization. In addition, we will document how the implementation of these strategies will impact triage quality and clinical outcomes of the CMO model. Table 1 explains the realist terminology applied to this project.
The search strategy will include original studies from the databases that may include studies on the topic of interest: Embase, PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science and ProQuest Dissertations & Theses. The final search strategy is divided into four concepts: triage, emergency department (ED), nursing and strategies to improve quality of triage. Each of these concepts is divided into several text and MeSH (PubMed) or EMTREE (Embase) terms. To ensure the sensitivity of the search strategy, we will verify that a search returns five key articles meeting the inclusion criteria. An example of the search strategy for PudMed is presented in Table 2 . Since validated triage scales (i.e. CTAS, ESI, MTS, ATS) began to be implemented in the mid‐1990s, the databases will be queried from 1990. To keep the review up to date, when this realist review is near completion, a final search for additional studies will be conducted.
Search strategy for PudMed
| Concepts | Keywords |
|---|---|
| #1 Triage | “Triage”[Mesh] OR “Triage”[Majr] OR “undertriage”[Title/Abstract] OR “overtriage”[Title/Abstract] OR “triage”[Title/Abstract] OR “canadian triage and acuity scale”[Title/Abstract] OR “CTAS”[Title/Abstract] OR “emergency severity index”[Title/Abstract] OR “ESI”[Title/Abstract] OR “australasian triage scale”[Title/Abstract] OR “ATS”[Title/Abstract] OR “manchester triage system*”[Title/Abstract] OR “MTS”[Title/Abstract] |
| #2 Emergency | “emergency service, hospital”[MeSH Terms] OR “Emergency Medical Services”[MeSH Terms] OR “Emergency Nursing”[MeSH Terms] OR “Emergency Medicine”[MeSH Terms] OR “Hospitals”[Mesh] OR “Emergency”[Title/Abstract] OR “Emergencies”[Title/Abstract] OR “Hospital”[Title/Abstract] |
| #3 Nursing | Nurse[Title/Abstract] OR Nurses[Title/Abstract] OR Nursing[Title/Abstract] OR “Nursing”[Mesh] OR “Nurses”[Mesh] OR “Evidence‐Based Nursing”[Mesh] OR “Nursing Staff, Hospital”[Mesh] |
| #4 Strategies to improve nursing triage (free text) | Audit[Title/Abstract] OR Feedback[Title/Abstract] OR Education*[Title/Abstract] OR Workshop*[Title/Abstract] OR Meeting*[Title/Abstract] OR Champion*[Title/Abstract] OR Mentor*[Title/Abstract] OR Preceptor*[Title/Abstract] OR “Role model*”[Title/Abstract] OR “Role‐model*”[Title/Abstract] OR “Opinion leader*”[Title/Abstract] OR Reminder*[Title/Abstract] OR “Decision aid*”[Title/Abstract] OR “Decision support*”[Title/Abstract] OR “Mass media”[Title/Abstract] OR “Case scenario*”[Title/Abstract] OR “Case study packet*”[Title/Abstract] OR “Simulation*”[Title/Abstract] OR “Written information”[Title/Abstract] OR “Screening tool*”[Title/Abstract] OR Checklist*[Title/Abstract] OR Observation[Title/Abstract] OR “Self‐review*”[Title/Abstract] OR “Self review*”[Title/Abstract] OR “Paper charting”[Title/Abstract] OR “Paper‐charting”[Title/Abstract] OR Benchmarking[Title/Abstract] OR “Tailored intervention*”[Title/Abstract] OR Guideline*[Title/Abstract] OR Protocol*[Title/Abstract] OR Toolkit*[Title/Abstract] OR “Organizational polic*”[Title/Abstract] OR “Organizational polic*”[Title/Abstract] OR “Leadership support”[Title/Abstract] OR “artificial intelligence”[Title/Abstract] OR “software”[Title/Abstract] OR “digital triage”[Title/Abstract] OR “machine learning”[Title/Abstract] OR “digital phenotyping”[Title/Abstract] OR “deep learning”[Title/Abstract] OR “automated triage”[Title/Abstract] OR “computer‐aided decision*”[Title/Abstract] OR “computer aided decision*”[Title/Abstract] OR “decision‐making tool*”[Title/Abstract] OR “decision making tool*”[Title/Abstract] OR “clinical decision support”[Title/Abstract] OR “simulation*”[Title/Abstract] OR “virtual reality” [Title/Abstract] OR “Mobile application”[Title/Abstract] OR “E‐health” [Title/Abstract] OR “web‐based triage”[Title/Abstract] OR “Web based triage”[Title/Abstract] OR “ubiquitous computing”[Title/Abstract] OR “UbiTriagem”[Title/Abstract] OR “Ubiquitous health”[Title/Abstract] OR “Ubiquitous healthcare”[Title/Abstract] OR “MedTRIS”[Title/Abstract] OR “Medical triage[Title/Abstract] AND registration informatics system*”[Title/Abstract] OR “automated data collection”[Title/Abstract] OR “computerized system*”[Title/Abstract] |
| #5 Strategies to improve nursing triage (MeSH) | “Education”[Mesh] OR “Mentors”[Mesh] OR “Preceptorship”[Mesh] OR “Reminder Systems”[Mesh] OR “Decision Support Systems, Management”[Mesh] OR “Decision Support Techniques”[Mesh] OR “Mass Media”[Mesh] OR “Computer Simulation”[Mesh] OR “Checklist”[Mesh] OR “Observation”[Mesh] OR “Health Care Evaluation Mechanisms”[Mesh] OR “Benchmarking”[Mesh] OR “Leadership”[Mesh] OR “Guidelines as Topic”[Mesh] OR “Practice Guidelines as Topic”[Mesh] OR “Clinical Audit”[Mesh] OR “Nursing Audit”[Mesh] OR “Medical Audit”[Mesh] OR “Management Audit”[Mesh] OR “Formative Feedback”[Mesh] OR “Artificial Intelligence”[Mesh] OR “Software”[Mesh] OR “Machine Learning”[Mesh] OR “Deep Learning”[Mesh] OR “Decision Support Systems, Clinical”[Mesh] OR “Computer Simulation”[Mesh] OR “Virtual Reality”[Mesh] OR “Mobile Applications”[Mesh] OR “Medical Records Systems, Computerized”[Mesh] |
| Strategies | 1 AND 2 AND 3 AND (4 OR 5) |
We will include any type of study on strategies to improve the triage process, as long as they assess the relationship between strategies and targeted outcomes. Only studies using recognized and validated triage scales (i.e. CTAS, ESI, MTS, ATS) will be included. There will be no language restrictions. If studies are written in another language than those spoken by the research team (English, French, Portuguese, Spanish and Italian) and are considered relevant based on the title and abstract, Deep L Pro (DeepL GmbH) will be used for text translation. The research team is located in Quebec (Canada) with international collaborators.
We will exclude studies that are not conducted in the ED (e.g. pre‐hospital triage, simple triage and rapid treatment [START], telephone triage). We will also exclude studies dealing with disaster triage. This type of triage is not usually performed by nurses and providers do not use the same type of triage scales.
All articles (titles and abstracts) will be managed in Covidence. We will identify and remove duplicates using electronic and manual screening (Wichor et al., 2016). A random sample, including 10% of the citations identified through the formal searches, will be reviewed independently by the two reviewers and at least 75% agreement will be needed for the screening process to begin (Higgins et al., 2021). Titles, abstracts and then full texts will be screened by the two independent reviewers to determine whether articles are relevant or not, based on the eligibility criteria. The reference lists of the articles will also be reviewed to identify any other relevant studies. Any disagreement will be resolved through discussion between reviewers and, if necessary, in consultation with another senior scientist (MB). We will document the search strategy and study selection process using a PRISMA flow diagram (Page et al., 2021).
A standardized data extraction form (Table 3 ) has been developed and pilot tested on a sample of fives studies (Higgins et al., 2021). A pair of independent reviewers (SO, FS) with methodological and content expertise will extract information on the following themes from original studies: Study characteristics (country, study design, sample size), the context barriers to the implementation of best practices regarding triage, the mechanisms to which these barriers relate (capability, opportunity and motivation), the strategies used to overcome them (second and third layer of the BCW), the outcomes of these strategies on triage quality, along with the associated quantitative results (e.g. proportions, means) and qualitative results (author interpretations, themes and subthemes, text coding). Any disagreement will be resolved through discussion between reviewers and, if necessary, in consultation with a third senior reviewer (MB). We will contact the authors up to three times for missing data when deemed necessary.
Data extraction from quantitative and qualitative studies
| Author, year and title | Study design | Sample size | Contextual barriers (individual, interpersonal relations, institutional setting and infrastructure) | Mechanism (BCW: Capability, motivation, opportunity and behaviour) | Strategies (second and third layer of the BCW) | Outcomes | Quantitative results (e.g. proportion, mean) | Qualitative results (e.g. theme, subtheme, verbatim, expert opinions) |
|---|
The quality of the evidence will be critically appraised by two independent reviewers (SO, FS) with the Mixed Methods Appraisal Tool (MMAT) v.2018 (Hong et al., 2018; Hong et al., 2019). The MMAT is used to evaluate any type of study (qualitative, quantitative randomized controlled trials, quantitative nonrandomized, quantitative descriptive and mixed methods) according to five criteria rated as yes, no or cannot tell. It is not recommended to calculate an overall score based on the rating of each criterion. Instead, we will present the score for each criterion to provide a comprehensive outlook on the quality of the studies included (Hong et al., 2018).
Any disagreements on eligibility, extracted data or quality will be resolved through discussion between reviewers and in consultation with a senior reviewer (MB) when necessary.
Following data extraction according to the CMO model, each reviewer will provide a summary of the information collected. This step will make it possible to identify associations between the strategies to reduce the barriers to triage quality. We will also note the context in which they were implemented and whether the outcomes obtained were favourable or not (C + M = O) (Pawson, 2013).
At this stage of the process, it is important to use ‘contradictory’ evidence to generate insights about the influence of context (Pawson et al., 2005). In other words, it is important to also include CMO models that do not give the expected results. In this way, future researchers will be able to try other avenues to improve triage quality.
The findings of this realistic review will be shared with stakeholders such as nurses working in the emergency department, nurses involved in education and clinical decision makers influencing practices in different forums (meeting with staff, dissemination of results on social networks, scientific presentations and publications). An integrated knowledge approach involving these stakeholders in the preparation of the research protocol and in the interpretation of the data will also promote the dissemination and adoption of the findings into practice (Harrison & Graham, 2021; Straus et al., 2013). This knowledge synthesis will also identify research gaps by singling out barriers to quality triage and strategies to address these barriers. This may lay the groundwork for future research projects to promote the adoption of best practices in triage among ED nurses.
Considering the objective of this realist review—that is to assess what works, for whom and in what context, with respect to strategies for improved nurse triage in the ED—some limitations should also be noted. First, we do not know how much ground can be covered with this realist review (Geoff et al., 2014; Pawson et al., 2005). To address this issue, the researchers involved in data selection and extraction will focus on studies adhering to the inclusion and exclusion criteria and will meet regularly to ensure a clear understanding of these criteria.
Second, the information retrieved from each study could be limited, making it difficult to identify the contextual barriers and mechanisms involved in each strategy. Therefore, even though this step could be very time‐consuming, the researchers will pay particular attention to the proper categorization of data into CMO throughout this realist review. Categorizing results according to the CMO configuration will make it easier for nurses to understand and apply the resulting recommendations and to support behaviour changes to improve triage quality. In the event that it is not possible to identify context barriers and strategy mechanisms, this review will still provide an updated understanding of the strategies that can improve triage quality.
Thirdly, according to some authors (Pawson, 2013; Pawson et al., 2005), that realist reviews have difficulty identifying or fully describing the mechanisms that generate the outcome, especially since the outcomes are directly related to the context. This limitation will be kept in mind as we attempt to categorize the contexts, mechanism and outcomes (CMO) of nursing triage quality improvement strategies.
Finally, realist reviews do not provide results as concrete as RCT studies or Cochrane‐type reviews (Pawson et al., 2005), but this study will make it possible to propose recommendations adapted to the context of emergency care regarding the best strategies for improving the quality of nursing triage. Other studies will be necessary to test these recommendations, but the way will be paved for future researchers.
This realist review will use previously published data to assess what works, for whom and in what context with respect to strategies for improved nurse triage in the ED. There will be no participant recruitment; therefore, no informed consent process or formal ethics approval is necessary.
Our realist review will make an empirical contribution to the existing body of knowledge concerning quality improvement of nursing triage. In this regard, the goal of this realist review is to provide relevant results in the field and to understand in which context the mechanisms involved providing better outcomes. Triage remains the main gateway to the ED, and it is essential to secure this access for optimal ED functioning and safe care. Triage in the emergency department involves interdisciplinary collaboration with health care professionals who may have differing views (i.e. physicians do not feel nurses have triaged adequately and/or nurses do not feel physicians are responding quickly enough to high acuity patients). This realist review will identify these barriers, to facilitate the implementation of strategies and improve interprofessional collaboration and thereby patient outcomes. It will also offer the next steps for health care professionals, decision makers and researchers wishing to improve triage quality. Hopefully, this will ultimately contribute reduce triage errors and make access to emergency care safer.
SO and MB Made substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. SO, MG, CG, GF, PA, EM, FS and MB were involved in drafting the manuscript or revising it critically for important intellectual content and given final approval of the version to be published. Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content.
This project is funded by a doctoral excellence scholarship awarded by Université Laval (February 2021) and a grant from the Ministry of Higher Education (July 2021). MB has received a research salary award from the Fonds de Recherche du Québec – Santé (FRQS) and the Strategy for Patient‐Oriented Research Support (SPOR) unit of Quebec. CG, PA and EM have received research salary awards from the FRQS. GF is supported by a Banting Postdoctoral Fellowship (#202010BPF‐453,986‐255,367) from the Canadian Institutes of Health Research (CIHR), a Postdoctoral Fellowship Supplement from the University of Ottawa, and a Postdoctoral Fellowship from the Canadian Network on Hepatitis C. FS is supported by a CIHR professional master's scholarship.
The authors report no conflicts of interest.
We would like to thank Marc‐Aurèle Gagnon and Pier‐Alexandre Tardif for their participation in the development of the search strategy.
Ouellet, S. , Galliani, M. C. , Gélinas, C. , Fontaine, G. , Archambault, P. , Mercier, É. , Severino, F. , & Bérubé, M. (2023). Strategies to improve the quality of nurse triage in emergency departments: A realist review protocol . Nursing Open , 10 , 2770–2779. 10.1002/nop2.1550 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
