Using the Five-Level Taiwan Triage and Acuity Scale Computerized System: Factors in Decision Making by Emergency Department Triage Nurses

Using machine learning and natural language processing in triage for prediction of clinical disposition in the emergency department

BACKGROUND

Accurate triage is required for efficient allocation of resources and to decrease patients' length of stay. Triage decisions are often subjective and vary by provider, leading to patients being over-triaged or under-triaged. This study developed machine learning models that incorporated natural language processing (NLP) to predict patient disposition. The models were assessed by comparing their performance with the judgements of emergency physicians (EPs).

METHOD

This retrospective study obtained data from patients visiting EDs between January 2018 and December 2019. Internal validation data came from China Medical University Hospital (CMUH), while external validation data were obtained from Asia University Hospital (AUH). Nontrauma patients aged ≥ 20 years were included. The models were trained using structured data and unstructured data (free-text notes) processed by NLP. The primary outcome was death in the ED or admission to the intensive care unit, and the secondary outcome was either admission to a general ward or transferal to another hospital. Six machine learning models (CatBoost, Light Gradient Boosting Machine, Logistic Regression, Random Forest, Extremely Randomized Trees, and Gradient Boosting) and one Logistic Regression derived from triage level were developed and evaluated using EPs' predictions as reference.

RESULT

A total of 17,2101 and 41,883 patients were enrolled from CMUH and AUH, respectively. EPs achieved F1 core of 0.361 and 0.498 for the primary and secondary outcomes, respectively. All machine learning models achieved higher F1 scores compared to EPs and Logistic Regression derived from triage level. Random Forest was selected for further evaluation and fine-tuning, because of its robust calibration and predictive performance. In internal validation, it achieved Brier scores of 0.072 and 0.089 for the primary and secondary outcomes, respectively, and 0.076 and 0.095 in external validation. Further analysis revealed that incorporating unstructured data significantly enhanced the model's performance. Threshold adjustments were applied to improve clinical applicability, aiming to balance the trade-off between sensitivity and positive predictive value.

CONCLUSION

This study developed and validated machine learning models that integrate structured and unstructured triage data to predict patient dispositions, distinguishing between general ward and critical conditions like ICU admissions and ED deaths. Integrating both structured and unstructured data significantly improved model performance.

Factors influencing nurse manager retention, intent to stay or leave and turnover: A systematic review update

AIMS

To understand factors influencing nurse manager retention or intention to leave, develop a preliminary theoretical model and identify strategies and interventions for workforce planning.

DESIGN

Systematic review update of literature with integrated design of mixed research synthesis.

METHODS

We included peer-reviewed articles examining factors influencing retention or intention to leave for front-line, middle or patient care nurse managers. Authors independently screened articles for inclusion and assessed included articles for quality. We adhered to a convergent synthesis approach.

DATA SOURCES

Nine databases included MEDLINE, EMBASE, PsychINFO, CINAHL Plus with Full Text, ERIC, Health Source Nursing/Academic Edition, Scopus, ProQuest Dissertations and Theses and LILACS in January 2023.

RESULTS

Thirty-five studies published between 1990 and 2022, 22 quantitative and 13 qualitative or mixed methods, were included. 155 factors influencing nurse manager retention, intention to stay, or turnover were reported. Job satisfaction was most frequently examined (n = 7), followed by factors such as empowerment (n = 3), decision-making (n = 3) and resilience (n = 2). We developed a preliminary theoretical model demonstrating staff relations and leadership, organizational and job characteristics, socio-demographics, personal characteristics, well-being and nurse manager relationship with work influence managers' intention to stay or to leave.

CONCLUSIONS

Nurse managers who were empowered, satisfied with their work, received constructive feedback and found meaning in their roles showed greater intent to stay.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

Nurse administrators can ensure managers are provided with authority to make decisions that promote autonomy. Work cultures that allow for regular meaningful constructive feedback from staff and leaders may contribute to nurse managers feeling valued.

IMPACT

Understanding factors that influence job retention or intention to leave may help nurse managers and their supervisors identify areas for strategy and intervention design to ensure sustainability of this workforce.

REPORTING METHOD

PRISMA 2020 Guidelines.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

The accuracy of triage classification using Emergency Severity Index

INTRODUCTION

Accurate emergency triage is essential for timely and appropriate care based on patient acuity. We sought to evaluate triage accuracy among emergency department (ED) nurses and examine potential influencing factors.

METHODS

We conducted an observational study using an electronic medical record chart review of 100 patients admitted at one of three EDs in a large academic medical system in the southern United States from December 1 to 7, 2021. Descriptive statistics were used to summarize the data. We compared the nurses' initial assigned triage acuity level documented in the medical chart with triage acuity assigned using the Emergency Severity Index Version 4 handbook and assessed inter-rater agreement using Cohen's kappa coefficient.

RESULTS

Overall triage accuracy was 67%, with most patients (62%) triaged as ESI level 3; under- and over-triage occurred in 25% and 8% of cases, respectively. Cohen's kappa coefficient was 0.437, indicating moderate interrater reliability between the triage nurses and the ESI handbook. Triage accuracy varied across ED locations and patient characteristics of sex (male: 55.6%, female: 72.3%), type of complaint (trauma: 57.1%, non-trauma: 69.4%), shift (day: 63.5%, night: 73.0%), and mode of arrival (ambulance: 80.8%, ambulatory: 65.2%, and private vehicle: 37.5%).

CONCLUSION

Triage inaccuracy may be attributed to a combination of nursing- and patient-specific factors. Further study of those factors associated with triage accuracy is warranted.

Emergency department triage decision-making by registered nurses: An instrument development study

AIM

To develop and psychometrically test the triage decision-making instrument, a tool to measure Emergency Department Registered Nurses decision-making.

DESIGN

Five phases: (1) defining the concept, (2) item generation, (3) face validity, (4) content validity and (5) pilot testing.

METHODS

Concept definition informed by a grounded theory study from which four domains emerged. Items relevant to the four domains were generated and revised. Face validity was established using three focus groups. The target population upon which the reliability and validity of the triage decision-making instrument was explored were triage registered nurses in emergency departments. Three expert judges assessed 89 items for content and domain designation using a 4-point scale. Psychometric properties were assessed by exploratory factor analysis, following which the names of the four domains were modified.

RESULTS

The triage decision-making instrument is a 22-item tool with four factors: clinical judgement, managing acuity, professional collaboration and creating space. Focus group data indicated support for the domains. Expert review resulted in 46 items with 100% agreement and 13 with 66% agreement. Fifty-nine items were distributed to a convenience sample of 204 triage nurses from six hospitals in 2019. The Kaiser-Meyer-Olkin measures indicated that the data were sufficient for exploratory factor analysis. Bartlett's test indicated patterned relationships among the items (X 2 (231) = 1156.69). An eigenvalue of >1.0 was used and four factors explained 48.64% of the variance. All factor loadings were ≥0.40. Internal consistency was demonstrated by Cronbach's alphas of .596 factor 1, .690 factor 2, .749 factor 3 and .822 for factor 4.

CONCLUSION

The triage decision-making instrument meets the criteria for face validity, content validity and internal consistency. It is suitable for further testing and refinement.

IMPACT

The instrument is a first step in quantifying triage decision-making in real-world clinical environments. The triage decision-making instrument can be used for targeted triage interventions aimed at improving throughput and staff education.

STATISTICAL SUPPORT

Dr. Tak Fung who is a member of the research team is a statistician.

STATISTICAL METHODS

Development, validation and assessment of instruments/scales. Descriptive statistics.

REPORTING METHOD

STROBE cross-sectional checklist.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

The TDI makes the complexity of triage decision-making visible. Identifying the influence of decision-making factors in addition to acuity that affect triage decisions will enable nurse managers and educators to develop targeted interventions and staff development initiatives. By extension, this will enhance patient care and safety.

Patient stratification based on the risk of severe illness in emergency departments through collaborative machine learning models

OBJECTIVES

Emergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily rely on the judgment of the triage staff could fail to detect subtle symptoms in critical patients, thus leading to delayed treatment. Unlike previous rivalry-focused approaches, our study aimed to establish a collaborative machine learning (ML) model that renders risk scores for severe illness, which may assist the triage staff to provide a better patient stratification for timely critical cares.

METHODS

This retrospective study was conducted at a tertiary teaching hospital. Data were collected from January 2015 to October 2022. Demographic and clinical information were collected at triage. The study focused on severe illness as the outcome. We developed artificial neural network (ANN) models, with or without utilizing the Taiwan Triage and Acuity Scale (TTAS) score as one of the predictors. The model using the TTAS score is termed a machine-human collaborative model (ANN-MH), while the model without it is referred to as a machine-only model (ANN-MO). The predictive power of these models was assessed using the area under the receiver-operating-characteristic (AUROC) and the precision-recall curves (AUPRC); their sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score were compared.

RESULTS

The study analyzed 668,602 ED visits from 2015 to 2022. Among them, 278,724 visits from 2015 to 2018 were used for model training and validation, while 320,201 visits from 2019 to 2022 were for testing model performance. Approximately 2.6% of visits were by severely ill patients, whose TTAS scores ranged from 1 to 5. The ANN-MH model achieved a testing AUROC of 0.918 and AUPRC of 0.369, while for the ANN-MO model the AUROC and AUPRC were 0.909 and 0.339, respectively. Based on these metrics, the ANN-MH model outperformed the ANN-MO model, and both surpassed human triage classification. Subgroup analyses further highlighted the models' capability to identify higher-risk patients within the same triage level.

CONCLUSIONS

The traditional 5-level triage system often falls short, leading to under-triage of critical patients. Our models include a score-based differentiation within a triage level to offer advanced risk stratification, thereby promoting patient safety.

Use of Reverse Shock Index Multiplied by Simplified Motor Score in a Five-Level Triage System: Identifying Trauma in Adult Patients at a High Risk of Mortality

Background and Objectives: The Taiwan Triage and Acuity Scale (TTAS) is reliable for triaging patients in emergency departments in Taiwan; however, most triage decisions are still based on chief complaints. The reverse-shock index (SI) multiplied by the simplified motor score (rSI-sMS) is a more comprehensive approach to triage that combines the SI and a modified consciousness assessment. We investigated the combination of the TTAS and rSI-sMS for triage compared with either parameter alone as well as the SI and modified SI. Materials and Methods: We analyzed 13,144 patients with trauma from the Taipei Tzu Chi Trauma Database. We investigated the prioritization performance of the TTAS, rSI-sMS, and their combination. A subgroup analysis was performed to evaluate the trends in all clinical outcomes for different rSI-sMS values. The sensitivity and specificity of rSI-sMS were investigated at a cutoff value of 4 (based on previous study and the highest score of the Youden Index) in predicting injury severity clinical outcomes under the TTAS system were also investigated. Results: Compared with patients in triage level III, those in triage levels I and II had higher odds ratios for major injury (as indicated by revised trauma score < 7 and injury severity score [ISS] ≥ 16), intensive care unit (ICU) admission, prolonged ICU stay (≥14 days), prolonged hospital stay (≥30 days), and mortality. In all three triage levels, the rSI-sMS < 4 group had severe injury and worse outcomes than the rSI-sMS ≥ 4 group. The TTAS and rSI-sMS had higher area under the receiver operating characteristic curves (AUROCs) for mortality, ICU admission, prolonged ICU stay, and prolonged hospital stay than the SI and modified SI. The combination of the TTAS and rSI-sMS had the highest AUROC for all clinical outcomes. The prediction performance of rSI-sMS < 4 for major injury (ISS ≥ 16) exhibited 81.49% specificity in triage levels I and II and 87.6% specificity in triage level III. The specificity for mortality was 79.2% in triage levels I and II and 87.4% in triage level III. Conclusions: The combination of rSI-sMS and the TTAS yielded superior prioritization performance to TTAS alone. The integration of rSI-sMS and TTAS effectively enhances the efficiency and accuracy of identifying trauma patients at a high risk of mortality.

Understanding triage assessment of acuity by emergency nurses at initial adult patient presentation: A qualitative systematic review

BACKGROUND

Nurses make complex triage decisions within emergency departments, which significantly affect patient outcomes. Understanding how nurses make these decisions and why they deviate from triage algorithms facilitates interventions that work with their decision-making processes, increasing acceptability and effectiveness.

AIMS

This qualitative systematic review aimed to understand decision-making processes emergency nurses use to make acuity decisions during triage assessment at initial patient presentation.

METHODOLOGY

Medline, CINAHL and Academic Search Complete were systematically searched to 15th December 2022. Data were analysed using thematic synthesis. Established themes were reviewed with GRADE-CERQual to evaluate certainty of evidence.

RESULTS

28 studies were included in the review. Data analysis uncovered three superordinate themes of holistic reasoning, situational awareness, and informed decision-making. The findings show nurses value holistic assessments over algorithms and rely on knowledge and experience. They also assess the wider situation in the emergency department.

CONCLUSIONS

This review presents new perspectives on nurses' decision-making processes about patient's acuity. Nurses holistically gather information about patients before translating that information into acuity scores. These actions are informed by their knowledge and experience; however, the wider situation also impacts their decisions. In turn, the nurses use interpretations of patients' acuity to control the wider situation.

Triage Knowledge and Practice and Associated Factors Among Emergency Department Nurses

Objective

The study aims at assessing the triage knowledge and practices and their associated factors among emergency department nurses employed in King Fahad Medical City (KFMC), Saudi Arabia.

Method

The study employed a cross-sectional, descriptive, and correlational design. Data collection was carried out from February 11, 2021, until April 27, 2021. The study included all emergency department nurses who were working in the KFMC during the data collection period and excluded those who were on leave at the time of data collection. A self-reported questionnaire with adequate validity and reliability was used. Statistical analysis was performed using the IBM SPSS Version 25 employing descriptive statistics, independent t-test, one-way ANOVA, and Pearson correlation test.

Results

A total of 147 emergency department nurses completed the study. Participants demonstrated generally high levels of triage knowledge and triage practice. However, knowledge deficit and incorrect practice related to some aspects were noted. There were no significant differences in triage knowledge and practice according to participants’ demographics including gender, job title, qualification, emergency nursing training, and previous training in triage (P > 0.05). Most participants (n = 141, 95.9%) had access to their triage systems and the majority (n = 79, 53.7%) utilize triage systems on a daily basis. Half said that only professional nurses performed the triage role (n = 69, 46.9%). There was a significant positive relationship between triage knowledge and practice (r = 0.486, P < 0.01).

Conclusion

The respondents had a high level of triage knowledge and practice. However, they have some areas of knowledge deficit and some deficiencies in the conversion of their knowledge into practice. The study recommends the development of further training and education in emergency nursing to address knowledge deficits and incorrect triage practices.

Patient-physician communication in the emergency department in Taiwan: physicians’ perspectives

Background

Effective patient-physician communication promotes trust and understanding between physicians and patients and reduces medical disputes. In this study, the Roter Interaction Analysis System was used to explore physician-patient communication behaviors in the emergency departments of Taiwanese hospitals.

Method

Data was collected from the dialogues between 8 emergency physicians and 54 patients through nonparticipant observation, and 675 pieces of data were quantitatively and qualitatively analyzed.

Results

The results showed that: 1. Emergency physicians’ communication behaviors are task-focused. They usually ask closed-ended questions to collect data to identify the symptoms quickly and provide medical treatment. 2. Socioemotion-oriented physician-patient communication behaviors are less common in the emergency department and only serve as an aid for health education and follow-up. Due to time constraints, it is difficult to establish relationships with patients and evoke their positivity.

Conclusions

It is suggested that future education programs on physician-patient communication in the emergency department should focus on strengthening physicians’ ability to communicate with patients in a more open way. They should adopt socioemotional-oriented communication skills, expressing respect and kindness, and allowing patients to briefly describe their symptoms and participate in the treatment process to achieve physician-patient consensus.

Machine Learning Algorithms to Predict In-Hospital Mortality in Patients with Traumatic Brain Injury

Traumatic brain injury (TBI) can lead to severe adverse clinical outcomes, including death and disability. Early detection of in-hospital mortality in high-risk populations may enable early treatment and potentially reduce mortality using machine learning. However, there is limited information on in-hospital mortality prediction models for TBI patients admitted to emergency departments. The aim of this study was to create a model that successfully predicts, from clinical measures and demographics, in-hospital mortality in a sample of TBI patients admitted to the emergency department. Of the 4881 TBI patients who were screened at the emergency department at a high-level first aid duty hospital in northern Taiwan, 3331 were assigned in triage to Level I or Level II using the Taiwan Triage and Acuity Scale from January 2008 to June 2018. The most significant predictors of in-hospital mortality in TBI patients were the scores on the Glasgow coma scale, the injury severity scale, and systolic blood pressure in the emergency department admission. This study demonstrated the effective cutoff values for clinical measures when using machine learning to predict in-hospital mortality of patients with TBI. The prediction model has the potential to further accelerate the development of innovative care-delivery protocols for high-risk patients.

Emergency nurse triage in the hospital information management system: A quality improvement study

BACKGROUND

Assessment of nurse triage decision accuracy and triage times is currently carried out through paper-based methods. This quality improvement study aims to develop a method that can assess the accuracy and duration of nurse triage decisions based on a computerized system and to share an example of the application of this method.

METHODS

This is a descriptive quality improvement study. The study was carried out in two stages between March and May 2019. The functionality of the developed method was examined using 3835 patients' triage data, which were obtained between June 1 and 14, 2019.

RESULTS

With this study, the determination of the accuracy and duration of nurse triage decisions was accomplished with a computerized process based on real patient outputs, and the accuracy and duration of these decisions were continuously measured, monitored, and assessed, which is different from paper-based methods. The functionality of the method was evaluated with data from 3835 real patients. The triage decision accuracy rate was 64.4%, and the average duration of triage was 81.3s. Positive feedback on the method was received from all triage nurses.

CONCLUSION

The study result outputs can be integrated into quality processes and can be used internationally as performance assessment criteria and quality indicators for triage nursing.

Facilitators and Barriers of the Triage Process based on Emergency Nurses' Experience with the Korean Triage and Acuity Scale (KTAS): A Qualitative Content Analysis

PURPOSE

Since 2016, the Korean Triage and Acuity Scale (KTAS) algorithm has been applied to the triage process in the emergency departments (EDs) of Korea. This study aimed to investigate the facilitators of and barriers to a well-run triage function based on how Korean emergency nurses perceived the triage process and their experiences with it.

METHODS

Data were collected using focus group interviews from June 2018 to January 2019. Twenty emergency nurses were divided into 2 junior and 4 senior groups based on their level of clinical experience. All interviews were recorded as they were spoken and transcribed. Data were analyzed using qualitative content analysis.

RESULTS

The participants recognized the need for the KTAS algorithm to efficiently classify emergency patients, and were working on it properly. According to the data, we extracted 4 themes and 20 sub-themes. Four themes were as follows; (1) awareness about the necessity of triage, (2) facilitators to triage process, (3) barriers to triage process, and (4) suggestions for the establishment and development of triage.

CONCLUSIONS

From the findings of this study, various vulnerabilities of the triage process were identified, and solutions were suggested from the emergency nurses' perspective. Educational, staffing, financial support, and periodic updates of the KTAS are needed to promote the triage process in the future.

Identifying a Clinical Risk Triage Score for Adult Emergency Department

Emergency triage is crucial for the treatment and prognosis of emergency patients, but its validity needs further improvement. The purpose of this study was to identify a risk score for adult triage. We conducted a regression analysis of physiological and biochemical data from 1,522 adult patients. A 60-point triage scoring model included temperature, pulse, systolic blood pressure, oxygen saturation, consciousness, dyspnea, admission mode, syncope history, chest pain or chest tightness, complexion, hematochezia or hematemesis, hemoptysis, white blood count, creatinine, bicarbonate, platelets, and creatine kinase. The area under curve in predicting ICU admission was 0.929 (95% CI [0.913-0.944]) for the derivation cohort and 0.911 (95% CI [0.884-0.938]) for the validation cohort. Four categories: critical level (≥13 points), severe level (6-12 points), urgency level (1-5 points), and sub-acute level (0 points) were divided, which significantly distinguished the severity of emergency patients.

Developing and validating a model for predicting 7-day mortality of patients admitted from the emergency department: an initial alarm score by a prospective prediction model study

OBJECTIVES

To set up a prediction model for the 7-day in-hospital mortality of patients admitted from the emergency department (ED) because it is high but no appropriate initial alarm score is available.

DESIGN

This is a prospective cohort study for prediction model development.

SETTING

In a tertiary referred hospital in northern Taiwan.

PARTICIPANTS

ED-admitted medical patients in hospitalist care wards were enrolled during May 2010 to October 2016. Two-thirds of them were randomly assigned to a derivation cohort for development of the model and cross-validation was performed in the validation cohort.

PRIMARY OUTCOME MEASURED

7-day in-hospital mortality.

RESULTS

During the study period, 8649 patients were enrolled for analysis. The mean age was 71.05 years, and 51.91% were male. The most common admission diagnoses were pneumonia (36%) and urinary tract infection (20.05%). In the derivation cohort, multivariable Cox proportional hazard regression revealed that a low Barthel Index Score, triage level 1 at the ED, presence of cancer, metastasis and admission diagnoses of pneumonia and sepsis were independently associated with 7 days in-hospital mortality. Based on the probability developed from the multivariable model, the area under the receiver operating characteristic curve in the derivation group was 0.81 (0.79-0.85). The result in the validation cohort was comparable. The prediction score modified by the six independent factors had high sensitivity of 88.03% and a negative predictive value of 99.51% for a cut-off value of 4, whereas the specificity and positive predictive value were 89.61% and 10.55%, respectively, when the cut-off value was a score of 6.

CONCLUSION

The 7-day in-hospital mortality in the hospitalist care ward is 2.8%. The initial alarm score could help clinicians to prioritise or exclude patients who need urgent and intensive care.

Implementation of a Standardized Initial Assessment for Demand Management in Outpatient Emergency Care in Germany: Early Qualitative Process Evaluation

BACKGROUND

Inadequate assessment of the severity and urgency of medical problems is one of the factors contributing to unnecessary emergency department (ED) visits. The implementation of a software-based instrument for standardized initial assessment-Standardisierte medizinische Ersteinschätzung in Deutschland (SmED) (Standardized medical Initial Assessment in Germany in English)-aims to support health care professionals and steer patients toward the right health care provider. This study aimed to explore the implementation process of SmED from a user perspective.

OBJECTIVE

This study aims to evaluate the overall perception of SmED by health care professionals using the software, to examine to what extent SmED influences the workload and work routines of health care professionals, and to determine which factors are associated with the use of SmED.

METHODS

An early qualitative process evaluation on the basis of interviews was carried out alongside the implementation of SmED in 26 outpatient emergency care services within 11 federal states in Germany. Participants were 30 health care professionals who work with SmED either at the joint central contact points of the outpatient emergency care service and the EDs of hospitals (ie, the Joint Counter; Gemeinsamer Tresen in German) or at the initial telephone contact points of the outpatient emergency care service (phone number 116117). Matrix-based framework analysis was applied to analyze the interview data.

RESULTS

Health care professionals perceived that workload increased initially, due to additional time needed per patient. When using SmED more frequently and over a longer time period, its use became more routine and the time needed per call, per patient, decreased. SmED was perceived to support decision making regarding urgency for medical treatment, but not all types of patients were eligible. Technical problems, lack of integration with other software, and lack of practicability during peak times affected the implementation of SmED.

CONCLUSIONS

Initial experiences with SmED were positive, in general, but also highlighted organizational issues that need to be addressed to enhance sustainability.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00017014; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00017014.

Experiences of nurses working in a triage area: An integrative review

OBJECTIVES

The aim of the study is to review the literature on the experiences of nurses working in triage within emergency departments in hospitals.

REVIEW METHOD

This is an integrative review based on Cooper's five-stage framework.

DATA SOURCES

Primary research articles published from January 2008 to January 2018 were identified from seven databases: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, PsycINFO, Cochrane, ProQuest, and Scopus. A manual search of the end references from the published studies was also conducted to ensure a comprehensive search.

REVIEW METHOD

The included studies were evaluated independently by two authors based on the Joanna Briggs Institute appraisal checklist for Interpretive and Critical Research and Descriptive/Case Series to ensure methodological rigour and validity of the review.

RESULTS

The literature review included 35 articles; of which, 18 were qualitative studies, 13 were quantitative studies, and four were mixed-method studies. The findings from this review were categorised into three themes: (1) making judgement, (2) service delivery, and (3) effective communication.

CONCLUSIONS

The results from the review suggest that triage is a complex process involving decision-making and interprofessional communication. Nurses need to make judgement, consider factors affecting service delivery, and engage in effective communication, which is central to triaging. Decision-making is contextual and requires judicious judgement. Effective communication with fellow healthcare personnel and with patients and their caregivers is paramount to optimise care delivery. Finally, more support is needed to empower the nurses to cope with the work involved in triaging.

Reliability of Korean Triage and Acuity Scale: Interrater Agreement between Two Experienced Nurses by Real-Time Triage and Analysis of Influencing Factors to Disagreement of Triage Levels

BACKGROUND

All emergency centers in Korea use the Korean Triage and Acuity Scale (KTAS) as their initial triage tool. However, KTAS has been used without verification of its reliability. In this study, we assess the interrater agreement of KTAS by two independent nurses in real-time and analyse the factors which have an effect on the disagreement of KTAS levels.

METHODS

This study was a prospective observational study conducted with patients who visited an emergency department (ED). Two teams, each composed of two nurses, triaged patients and recorded KTAS level and the main complaint from the list of 167 KTAS complaints, as well as modifiers. Interrater reliability between the two nurses in each team was assessed by weighted-kappa. Pearson's χ² test was conducted to determine if there were differences between each nurse's KTAS levels, depending on whether they chose the same complaints and the same modifiers or not.

RESULTS

The two teams triaged a total of 1,998 patients who visited the ED. Weighted-kappa value was 0.772 (95% confidence interval [CI], 0.750-0.794). Patients triaged by different chosen complaints showed (38.0%) higher inconsistency rate in KTAS levels than those triaged by the same complaint (10.9%, P < 0.001). When nurses chose the same complaint and different modifiers, the ratio of different levels (50.5%) was higher than that of the same complaint and same modifier (8.1%, P < 0.001).

CONCLUSION

This study showed that KTAS is a reliable tool. Selected complaints and modifiers are confirmed as important factors for reliability; therefore, selecting them properly should be emphasized during KTAS training courses.

A Multicenter Observational Prospective Cohort Study of Association of the Prehospital National Early Warning Score 2 and Hospital Triage with Early Mortality

Aim of the Study

To evaluate the ability of the prehospital National Early Warning Score 2 scale (NEWS2) to predict early mortality (within 48 hours) after the index event based on the triage priority assigned for any cause in the emergency department.

Methods

This is a multicenter longitudinal observational cohort study on patients attending Advanced Life Support units and transferred to the emergency department of their reference hospital. We collected demographic, physiological, and clinical variables, main diagnosis, and hospital triage level as well as mortality. The main outcome variable was mortality from any cause within two days of the index event.

Results

Between April 1 and November 30, 2018, a total of 1054 patients were included in our study. Early mortality within the first 48 hours after the index event affected 55 patients (5.2%), of which 23 cases (41.8%) had causes of cardiovascular origin. In the stratification by triage levels, the AUC of the NEWS2 obtained for short-term mortality varied between 0.77 (95% CI: 0.65-0.89) for level I and 0.94 (95% CI: 0.79-1) for level III.

Conclusions

The Prehospital Emergency Medical Services should evaluate the implementation of the NEWS2 as a routine evaluation, which, together with the structured hospital triage system, effectively serves to predict early mortality and detect high-risk patients.

Prognostic value of Modified Early Warning Score generated in a Chinese emergency department: a prospective cohort study

OBJECTIVES

This study aimed to validate the performance of the Modified Early Warning Score (MEWS) in a Chinese emergency department and to determine the best cut-off value for in-hospital mortality prediction.

DESIGN

A prospective, single-centred observational cohort study.

SETTING

This study was conducted at a tertiary hospital in South China.

PARTICIPANTS

A total of 383 patients aged 18 years or older who presented to the emergency department from 17 May 2017 through 27 September 2017, triaged as category 1, 2 or 3, were enrolled.

OUTCOMES

The primary outcome was a composite of in-hospital mortality and admission to the intensive care unit. The secondary outcome was using MEWS to predict hospitalised and discharged patients.

RESULTS

A total of 383 patients were included in this study. In-hospital mortality was 13.6% (52/383), and transfer to the intensive care unit was 21.7% (83/383). The area under the receiver operating characteristic curve of MEWS for in-hospital mortality prediction was 0.83 (95% CI 0.786 to 0.881). When predicting in-hospital mortality with the cut-off point defined as 3.5, 158 patients had MEWS >3.5, with a specificity of 66%, a sensitivity of 87%, an accuracy of 69%, a positive predictive value of 28% and a negative predictive value of 97%, respectively.

CONCLUSION

Our findings support the use of MEWS for in-hospital mortality prediction in patients who were triaged category 1, 2 or 3 in a Chinese emergency department. The cut-off value for in-hospital mortality prediction defined in this study was different from that seen in many other studies.

Acolhimento com classificação de risco em unidade de pronto atendimento: estudo avaliativo

RESUMO Objetivo Descrever a avaliação da estrutura, processo e resultado do Acolhimento com Classificação de Risco, na perspectiva dos médicos e enfermeiros de uma Unidade de Pronto Atendimento. Método Estudo avaliativo, descritivo, quantitativo, desenvolvido em Santa Catarina. Dados coletados com instrumento validado e adaptado, constituído por 21 itens distribuídos nas dimensões Estrutura (instalações), Processo (atividades e relações no atendimento) e Resultado (efeitos do atendimento). Na análise, aplicaram-se a estatística descritiva, o cálculo do Ranking Médio e o da Pontuação Média. Resultados A amostra foi de 37 participantes. Dos 21 itens avaliados, 11 (52,4%) tiveram Ranking Médio entre 3 e 4, e nenhum atingiu o máximo (5 pontos). A “Priorização dos casos graves” e o “Atendimento primário por gravidade do caso” obtiveram maior Ranking Médio (4,5), enquanto a “Discussão sobre fluxograma” revelou menor Ranking (2,1). As dimensões Estrutura, Processo e Resultado atingiram, respectivamente, as pontuações médias 23,9, 21,9 e 25,5, indicando avaliação Precária (17,5 a 26,1 pontos). Conclusão Há precarização do Acolhimento com Classificação de Risco, em especial no que se refere ao processo, que obteve menor nível de satisfação dos participantes.