Performance of triage systems in emergency care: a systematic review and meta-analysis

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study

BACKGROUND

Hospitals use triage systems to prioritize the needs of patients within available resources. Misclassification of a patient can lead to either adverse outcomes in a patient who did not receive appropriate care in the case of undertriage or a waste of hospital resources in the case of overtriage. Recent advances in machine learning algorithms allow for the quantification of variables important to under- and overtriage.

OBJECTIVE

This study aimed to identify clinical features most strongly associated with triage misclassification using a machine learning classification model to capture nonlinear relationships.

METHODS

Multicenter retrospective cohort data from 2 big regional hospitals in Norway were extracted. The South African Triage System is used at Bergen University Hospital, and the Rapid Emergency Triage and Treatment System is used at Trondheim University Hospital. Variables included triage score, age, sex, arrival time, subject area affiliation, reason for emergency department contact, discharge location, level of care, and time of death were retrieved. Random forest classification models were used to identify features with the strongest association with overtriage and undertriage in clinical practice in Bergen and Trondheim. We reported variable importance as SHAP (SHapley Additive exPlanations)-values.

RESULTS

We collected data on 205,488 patient records from Bergen University Hospital and 304,997 patient records from Trondheim University Hospital. Overall, overtriage was very uncommon at both hospitals (all <0.1%), with undertriage differing between both locations, with 0.8% at Bergen and 0.2% at Trondheim University Hospital. Demographics were similar for both hospitals. However, the percentage given a high-priority triage score (red or orange) was higher in Bergen (24%) compared with 9% in Trondheim. The clinical referral department was found to be the variable with the strongest association with undertriage (mean SHAP +0.62 and +0.37 for Bergen and Trondheim, respectively).

CONCLUSIONS

We identified subgroups of patients consistently undertriaged using 2 common triage systems. While the importance of clinical patient characteristics to triage misclassification varies by triage system and location, we found consistent evidence between the two locations that the clinical referral department is the most important variable associated with triage misclassification. Replication of this approach at other centers could help to further improve triage scoring systems and improve patient care worldwide.

[Structured triage in the emergency department via intelligent assistant service OPTINOFA : Results of a multicenter, cluster-randomized and controlled interventional study in Germany]

In Germany, a substantial reform of emergency care is strictly recommended. Regulation of patient flows into the ambulatory and stationary sectors remains a major issue.In the OPTINOFA project funded by Innovationsfunds, a new triage system was developed for a structured primary evaluation of both urgency and care level of emergency cases. OPTINOFA was evaluated in a cluster-randomized, controlled multicenter trial using a stepped-wedge design in eight emergency departments (ED) from 1 July 2019 to 31 May 2021. Additionally, data from one ED were used for comparison of temporal changes without intervention. The primary study endpoint represented the increase of patient transfers to the ambulatory sector; secondary endpoints included the outcome, process and quality indicators as well as mean emergency care costs.In the study, 46,558 emergency cases were included in the control period and 37,485 emergency cases in the intervention period. Concerning the primary endpoint, a significant increase of transfers to the ambulatory sector were detected in the per-protocol EDs (p < 0.001, odds ratio = 10.59). Waiting times were significantly reduced by an average 20 min in the intervention phase. Furthermore, a stable admission rate was found within 3 days after initial ED presentation. Cost analysis revealed no increase of treatment expenses within 28 days after ED admission.In this project a valid assistant service for structured primary evaluation of urgency and care level was successfully developed for emergency cases and served as a digital triage instrument with interoperable format. Clinical trial results revealed great potential for the OPTINOFA triage system to control patient flows in emergency and acute medicine.

The reliability and validity of triage tools in geriatric emergency departments: A scoping review

BACKGROUND

The nurse's ability to accurately identify urgent conditions and triage this vulnerable population tends to be complex and challenging. Little is known about the reliability and validity of common triage tools in geriatric patients.

AIM

To determine the reliability and validity of triage tools in geriatric emergency care and summarize the specific content of current triage tools for geriatric patients.

METHODS

The eligible literature was searched from the MEDLINE, CINAHL, EMBASE, and Cochrane Database using targeted search strategies. We defined the objectives and questions, set standards for article inclusion criteria, and conducted literature searching and screening. The mixed methods assessment tool (MMAT) appraised the article's quality. Finally, we extracted and analyzed the data from the included articles, summarizing the results. Endnote X9 was used for data extraction and collation.

RESULTS

Nine articles were eligible. These included six triage tools: CTAS, JTAS, KTAS, MTS, SETS, and ESI. The reliability of the CTAS was good when applied to triage geriatric patients. The SETS performed well in prehospital simulated triage. The ESI has moderate to excellent reliability. The CTAS has good to excellent validity, while the JTAS, KTAS, MTS, and ESI have fair to good results.

CONCLUSION

Several triage tools are useful in geriatrics, but the reliability and validity of these tools have mixed results. Applying triage tools to triage geriatric patients still has limitations.

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care

STUDY OBJECTIVE

This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critical care within 12 h of ED arrival.

METHODS

Three machine learning models (LASSO regression, gradient-boosted trees, and a deep learning model with embeddings) were developed using retrospective data from 670,841 ED visits to the Jewish General Hospital from June 2012 to Jan 2021. The model outcome was the need for critical care within the first 12 h of ED arrival. Metrics, including the areas under the receiver-operator characteristic curve (ROC) and precision-recall curve (PRC) were used for performance evaluation. Shapley additive explanation scores were used to compare predictor importance.

RESULTS

The three machine learning models (deep learning, gradient-boosted trees and LASSO regression) had areas under the ROC of 0.926 ± 0.003, 0.912 ± 0.003 and 0.892 ± 0.004 respectively, and areas under the PRC of 0.27 ± 0.01, 0.24 ± 0.01 and 0.23 ± 0.01 respectively. In comparison, the CTAS score had an area under the ROC of 0.804 ± 0.006 and under the PRC of 0.11 ± 0.01. The predictors of most importance were similar between the models.

CONCLUSIONS

Machine learning models outperformed CTAS in identifying, at the point of ED triage, patients likely to need early critical care. If validated in future studies, machine learning models such as the ones developed here may be considered for incorporation in future revisions of the CTAS triage algorithm, potentially improving discrimination and reliability.

What is the optimal outcome for evaluating the triage Systems? Insights from a prospective observational study

BACKGROUND

Currently, there is no universally accepted gold standard outcome for assessing the effectiveness of the Triage Systems. This study aimed to comprehensively evaluate and compare various outcomes utilized in triage studies.

METHODS

A prospective observational study was conducted at the Emergency Department (ED) of Merano Hospital from June 1 to December 31, 2023. We assessed the predictive capability of the Manchester Triage System (MTS) across multiple outcomes using areas under the receiver operating characteristic curve (AUROC), along with their corresponding 95% confidence intervals (95% CI), and frequency distributions.

RESULTS

The MTS demonstrated strong performance concerning the most objective outcomes, such as mortality (at 72 h: AUROC 0.914; 95 %CI: 0.815-1; at 7 days: 0.845; 95 %CI: 0.729-0.965; at 30 days: 0.794; 95 %CI: 0.706-0.881), admission to the intensive care unit (0.831; 95 %CI: 0.763-0.899), and need for life-saving interventions (0.870; 95 %CI: 0.806-0.934). Additionally, outcomes such as urgency status and clinical priority, as judged by physicians, exhibited excellent performance and optimal frequency distribution.

CONCLUSIONS

The performance of the MTS varied significantly depending on the specific outcome under evaluation. Currently, no single outcome appears superior to others, nor does any seem poised to serve as a potential gold standard for the assessment of triage systems. It is advisable for dedicated working groups to convene and reach a consensus on the most effective outcomes for evaluating the performance of MTS and other triage systems. This should be accomplished through a systematic, standardized, and transparent approach, grounded in the best available evidence.

Validation and comparison of triage-based screening strategies for sepsis

OBJECTIVE

This study sought to externally validate and compare proposed methods for stratifying sepsis risk at emergency department (ED) triage.

METHODS

This nested case/control study enrolled ED patients from four hospitals in Utah and evaluated the performance of previously-published sepsis risk scores amenable to use at ED triage based on their area under the precision-recall curve (AUPRC, which balances positive predictive value and sensitivity) and area under the receiver operator characteristic curve (AUROC, which balances sensitivity and specificity). Score performance for predicting whether patients met Sepsis-3 criteria in the ED was compared to patients' assigned ED triage score (Canadian Triage Acuity Score [CTAS]) with adjustment for multiple comparisons.

RESULTS

Among 2000 case/control patients, 981 met Sepsis-3 criteria on final adjudication. The best performing sepsis risk scores were the Predict Sepsis version #3 (AUPRC 0.183, 95 % CI 0.148-0.256; AUROC 0.859, 95 % CI 0.843-0.875) and Borelli scores (AUPRC 0.127, 95 % CI 0.107-0.160, AUROC 0.845, 95 % CI 0.829-0.862), which significantly outperformed CTAS (AUPRC 0.038, 95 % CI 0.035-0.042, AUROC 0.650, 95 % CI 0.628-0.671, p < 0.001 for all AUPRC and AUROC comparisons). The Predict Sepsis and Borelli scores exhibited sensitivity of 0.670 and 0.678 and specificity of 0.902 and 0.834, respectively, at their recommended cutoff values and outperformed Systemic Inflammatory Response Syndrome (SIRS) criteria (AUPRC 0.083, 95 % CI 0.070-0.102, p = 0.052 and p = 0.078, respectively; AUROC 0.775, 95 % CI 0.756-0.795, p < 0.001 for both scores).

CONCLUSIONS

The Predict Sepsis and Borelli scores exhibited improved performance including increased specificity and positive predictive values for sepsis identification at ED triage compared to CTAS and SIRS criteria.

Emergency Management and Nursing Considerations of Carotid Blowout Syndrome

INTRODUCTION

Carotid blowout syndrome is a rare but fatal complication often witnessed secondary to treating patients with head and neck cancer. It occurs when damage and necrosis lead to the carotid artery wall rupture. The symptoms encountered in these patients range from asymptomatic to cardiac arrest. Here, we present 5 cases of carotid blowout syndrome in the emergency department.

CASE PRESENTATIONS

Patients demonstrated symptoms ranging from subtle bleeding to hemodynamic instability, highlighting the diverse nature of carotid blowout syndrome in this population. Notably, while all patients had a history of radiotherapy, some had additional risk factors for carotid blowout syndrome, including prior surgery (n = 2), malnutrition (n = 3), and tracheostomies (n = 2). Definitive diagnoses were established through clinical evaluation and computed tomography angiography. Immediate interventions included bleeding control, resuscitation, and consultations with relevant specialties. Four patients underwent interventional radiology procedures, and 1 patient received otolaryngology care. While 2 patients recovered completely, 1 died in the emergency department, and 1 in the intensive care unit. One patient's clinical course was complicated by a stroke.

CONCLUSION

The approach to the carotid blowout syndrome patient includes complex steps that proceed in a multidisciplinary manner, starting from triage until discharge. Emergency nurses play crucial roles at every stage. They should be aware of carotid blowout syndrome when evaluating patients with head and neck cancer presenting with bleeding. When treating these patients, emergency nurses should be ready for airway interventions, bleeding control, and massive transfusion protocol. In this context, the multifaceted approaches made by nurses contribute significantly to carotid blowout syndrome management in the emergency department.

Evolution of the "Internet Plus Health Care" Mode Enabled by Artificial Intelligence: Development and Application of an Outpatient Triage System

BACKGROUND

Although new technologies have increased the efficiency and convenience of medical care, patients still struggle to identify specialized outpatient departments in Chinese tertiary hospitals due to a lack of medical knowledge.

OBJECTIVE

The objective of our study was to develop a precise and subdividable outpatient triage system to improve the experiences and convenience of patient care.

METHODS

We collected 395,790 electronic medical records (EMRs) and 500 medical dialogue groups. The EMRs were divided into 3 data sets to design and train the triage model (n=387,876, 98%) and test (n=3957, 1%) and validate (n=3957, 1%) it. The triage system was altered based on the current BERT (Bidirectional Encoder Representations from Transformers) framework and evaluated by recommendation accuracies in Xinhua Hospital using the cancellation rates in 2021 and 2022, from October 29 to December 5. Finally, a prospective observational study containing 306 samples was conducted to compare the system's performance with that of triage nurses, which was evaluated by calculating precision, accuracy, recall of the top 3 recommended departments (recall@3), and time consumption.

RESULTS

With 3957 (1%) records each, the testing and validation data sets achieved an accuracy of 0.8945 and 0.8941, respectively. Implemented in Xinhua Hospital, our triage system could accurately recommend 79 subspecialty departments and reduce the number of registration cancellations from 16,037 (3.83%) of the total 418,714 to 15,338 (3.53%) of the total 434200 (P<.05). In comparison to the triage system, the performance of the triage nurses was more accurate (0.9803 vs 0.9153) and precise (0.9213 vs 0.9049) since the system could identify subspecialty departments, whereas triage nurses or even general physicians can only recommend main departments. In addition, our triage system significantly outperformed triage nurses in recall@3 (0.6230 vs 0.5266; P<.001) and time consumption (10.11 vs 14.33 seconds; P<.001).

CONCLUSIONS

The triage system demonstrates high accuracy in outpatient triage of all departments and excels in subspecialty department recommendations, which could decrease the cancellation rate and time consumption. It also improves the efficiency and convenience of clinical care to fulfill better the usage of medical resources, expand hospital effectiveness, and improve patient satisfaction in Chinese tertiary hospitals.

Factors influencing the classification accuracy of triage nurses in emergency department: analysis of triage nurses' characteristics

BACKGROUND

Triage nurses play a vital role in emergency departments (Eds), with the accuracy of the triage nurse significantly impacting patient care and departmental efficiency. However, there is a lack of exploration into whether the time it takes for triage nurses to triage patients affects accuracy.

METHOD

This study analyzed the electronic medical records of 787 patients and the characteristics of triage nurses, using statistical methods to determine factors affecting classification accuracy. Data were collected from a single general hospital between November 1 and November 30, 2023.

RESULTS

Findings revealed an 84.9% accuracy rate. Longer clinical experience (p = .001, CI = 1.094-2.052), as well as extended classification time (p = .002, CI = 1.338-2.916), significantly improved accuracy. Age and gender had no notable effect.

CONCLUSION

Enhancing triage nurse experience and allowing adequate classification time can improve accuracy, optimizing patient care and ED operations.

Triage Discordance in an Academic Pediatric Emergency Department and Disparities by Race, Ethnicity, and Language for Care

BACKGROUND

Minoritized patients are disproportionately represented in low-acuity emergency department (ED) visits in the United States in part caused by lack of timely access to primary and urgent care. However, there is also the possibility that implicit bias during triage could contribute to disproportionate representation of minority groups in low-acuity ED visits. Triage discordance, defined as when ED resources used are different from initial triage score predictions, can be used as a proxy for triage accuracy. Recent data suggest that discordant triage may be common, although little is known about the interaction with race, ethnicity, and language for care.

OBJECTIVES

This study aims to determine the prevalence of discordant triage among moderate- and low-acuity pediatric ED encounters and the interaction with patient race, ethnicity, and language for care.

METHODS

We performed a retrospective analysis of pediatric ED encounters from 2019 with Emergency Severity Index (ESI) scores of 3, 4, or 5 at an academic referral hospital. The primary outcome was triage discordance, encompassing overtriage (ESI 3 and 4) and undertriage (ESI 4 and 5). Logistic and multinomial regressions were used to assess discordant triage by race, ethnicity, and language group.

RESULTS

Triage discordance occurred in 47% (n = 18,040) of encounters. Black and Hispanic patients had higher likelihood of undertriage for ESI 5 (adjusted odds ratio 1.21, 95% confidence interval [CI] 1.01-1.46 and 1.27, 95% CI 1.07-1.52, respectively), and Black patients were more likely to be overtriaged in ESI 3 (1.18, 95% CI 1.09-1.27). Those with a language other than English for care had higher proportions of overtriage for ESI 3 (1.08, 95% CI 1.04-1.12) and undertriage for ESI 5 (1.23, 95% CI 1.11-1.37).

CONCLUSIONS

We found high rates of triage discordance in our pediatric ED, with significant associations with race, ethnicity, and language for care. Future research should evaluate the source of triage discordance and develop quality improvement efforts to improve equitable care.

Expectations of emergency patients regarding triage system knowledge upon arrival: an interpretive study

BACKGROUND

One of the most important aspects of healthcare knowledge is having a thorough understanding of the triage system which is used in emergency departments. This study aims to assess the level of awareness of Jordanian patients who visit the ED about the triage procedure.

METHODS

A descriptive, cross-sectional design was utilized in the emergency department at the biggest public hospital in Jordan. A convenience sample of a self-administrated questionnaire utilizing a Discounted Cash Flow Interview (DCF) survey was filled out.

RESULTS

A total of 726 participants were recruited with a response rate of 90.8%. The mean age of the participants was M = 38.1 (SD = 12.9), and the age of the participants varied from 18 to 89 years. More than half of the participants were male (n = 383, 52.8%) and married (n = 425, 58.5%). A significant relationship between the overall perception of knowing what a teaching hospital is and patients' educational level (X2 = 11.9, P < 0.003), current job (X2 = 25.2, P < 0.001), nationality (X2 = 7.20, P < 0.007), and family income (X2 = 15.9, P < 0.001).

CONCLUSION

More investigation is required to determine the causes of the low knowledge of the triage system. The study suggests increasing staffing levels, giving nursing staff ongoing education and training, and integrating technology and automation to reduce the load of patient care.

Development and content validation of a risk classification instrument

OBJECTIVE

Develop and validate the content of an instrument for patient risk classification in emergency services of Primary Health Care.

METHOD

The study included two stages: item generation and content validity. A literature review and retrospective analysis of medical records were conducted to create the instrument items. The Content Validity Ratio (CVR) was used to assess agreement among judges during content validation.

RESULTS

In the first and second rounds, 75 and 71 judges validated the risk classification instrument, respectively. The minimum adherence score for the latent variable item based on the final number of judges was 0.22 and 0.18; thus, 52 items, divided into three classification categories (red, orange, and yellow), were retained.

CONCLUSION

The instrument was considered valid regarding clarity, relevance, pertinence, and agreement regarding the severity indicated in the item.

External validation of the TFC (triage frailty and comorbidity) tool: a prospective observational study

Assessing patient frailty during triage evaluations has become increasingly relevant in Emergency Departments (ED). This study aimed to externally validating the Triage Frailty and Comorbidity (TFC) tool. This prospective study was conducted from June 1 to December 31, 2023. During this period, 12 triage nurses applied the TFC tool during triage evaluation of ED patients. We used receiver operating characteristic (ROC) curves and Decision Curve Analysis to assess the predictive ability of the TFC tool for a 90-day mortality (the same endpoint used during tool development) and a 30-day mortality. 1270 patients were included and 56 of them died within 90 days. The TFC tool had an AUROC of 0.894 (0.858-0.929) for 90-day mortality and 0.885 (0.834-0.938) for 30-day mortality. In Decision Curve Analysis, it yielded higher net benefits up to a threshold probability of 0.30. The externally validated TFC tool appears very effective at identifying patients with increased risk of 90-day mortality after ED attendance. It could be implemented in clinical practice and enhance the predictive ability of standard triage systems.

Rabies post-exposure prophylaxis in the emergency department: A monocentric retrospective observational study

BACKGROUND

Emergency departments (ED) are frequently visited after suspected rabies exposure (SRE) and the potential need for rabies post-exposure prophylaxis (R-PEP). However, data on the number of visits, patients' demographics, travel history and the medical treatment is still rare. Therefore, the aim of this study was to assess the number of R-PEP and the appropriateness of medical management including wound treatment, vaccination regime and immunoglobulin application following SRE in a university hospital ED.

METHOD

We conducted a monocentric retrospective observational study on emergency patients treated in the ED of the LMU University Hospital, Ludwig-Maximilians-University Munich, Germany, between June 1st, 2023 and January 31st, 2024. Patients requiring post-exposure prophylaxis due to SRE abroad or in Germany were included. Demographic data, travel history, clinical findings, wound treatment, and R-PEP vaccination regimen were recorded.

RESULTS

During the observation period of 245 days 43 patients presented to our ED for R-PEP. There was a total of 51 presentation appointments, as 5 patients returned for further treatment. Most patients (27, 52.9 %) presented at the ED on a Saturday, Sunday, or a public holiday. 17 (39.5 %) patients had a category II exposure, and 26 (60.5 %) had a category III exposure. In our ED, there were 28 (55.0 %) active vaccinations and 23 (45.0 %) both active and passive vaccinations.

CONCLUSIONS

Our data show that patients frequently present for R-PEP in ED. Therefore, there is a high need for education on indication for R-PEP and for implementation of precise R-PEP treatment guidelines in daily clinical practice.

A Cross-Sectional Review of HIV Screening in High-Acuity Emergency Department Patients: A Missed Opportunity

Introduction

Emergency department (ED) patients requiring immediate treatment often bypass a triage process that includes HIV screening. In this study we aimed to investigate the potential missed opportunity to screen these patients for HIV.

Methods

We conducted this cross-sectional study in a municipal ED over a six-week period between June-August 2019. The patient population in this study arrived in the ED as a pre-notification from prehospital services or designated by the ambulance or walk-in triage nurse as requiring immediate medical attention. Medical student researchers collected demographic data and categorized patients into three clinical groups (trauma, medical, psychiatric). They documented the patient's eligibility for HIV screening as determined by a physician and confirmed that the patient met criteria of clear mental status, controlled pain, stable vital signs, and ability to contribute to a medical history and physical examination. The student researchers did this at initial presentation and then again during the patient's ED stay of up to eight hours. The study outcomes measured the percentage of total patients within each clinical group (trauma, medical, psychiatric) able to engage in the HIV screening process upon arrival and during an eight-hour ED stay.

Results

On average, 700 patients per month are announced on arrival via overhead page, indicating that they require immediate medical attention. During the six-week study, 205 patients (approximately 20% of total) were enrolled: 114 trauma; 56 medical; and 35 psychiatric presentations. The average patient age was 53; 60% of patients were male. Niney-eight (48%) patients were eligible for HIV screening within an eight-hour ED stay; 63 (31%) were able to be screened upon initial presentation and 35 (17%) in the first eight hours of their ED visit. Within medical and trauma subgroups, there was no significant difference in the proportion (36%) of patients that could be screened upon presentation. Among the psychiatric presentations, only five (14%) were able to be screened during their hospital stay.

Conclusion

Triage protocols for high-acuity medico-surgical patients resulted in a missed opportunity to screen 48% of patients for HIV. Acute psychiatric patients represented a particular missed opportunity. We advocate for universal HIV screening, facilitated through electronic best practice advisories and a modified triage tailored to higher acuity patients. Implementing these changes would ensure that HIV screening is not overlooked in high-acuity ED patients, leading to early detection and timely interventions.

Predictive validity of resource-adjusted Korean Triage and Acuity Scale in pediatric gastrointestinal tract foreign body patients

Although paediatric patients with gastrointestinal (GI) foreign bodies require multiple resources, they often present with few or no discernible symptoms and are typically assigned a low acuity level during triage. We compared the predictive accuracy of the revised Korean Triage and Acuity Scale (rKTAS), which elevates acuity by one step in relation to anticipated resource utilization, with that of the conventional KTAS for clinical outcomes. This was a retrospective study of National Emergency Department Information System data. Data on patient and ED characteristics, resources used, and clinical outcomes were collected from January 2018 to December 2021 for patients with GI foreign bodies aged under 19. The primary outcome was rKTAS accuracy in predicting hospitalization, ICU admission, operating room (OR) use, and ED length of stay (EDLOS). The AUROC was used to evaluate the performance via of the KTAS and rKTAS. In total, 25,324 paediatric patients visited the ED for GI tract foreign bodies. The mean age was 3.8 years, and 51% (12,923) were between 1 and 4 year old. Although most (23,658; 93.4%) were discharged, 4.9% required hospitalization. Two or more resources were utilized in 2514 (9.9%) cases, and 3,514 individuals had their triage levels increased by one step. Compared with those of the KTAS, the AUROCs of the rKTAS for predicting overall hospitalization (p < 0.05), admission to general wards (p < 0.05), ICU admission (p = 0.01), and admission via the OR (p < 0.05)were higher than KTAS. Compared with that with the KTAS, the EDLOS with the rKTAS was longer at levels 1, 2, and 3. The adjusted rKTAS is a better predictor of clinical outcomes for paediatric patients with GI tract foreign bodies than the KTAS.

Comparison of Two Symptom Checkers (Ada and Symptoma) in the Emergency Department: Randomized, Crossover, Head-to-Head, Double-Blinded Study

BACKGROUND

Emergency departments (EDs) are frequently overcrowded and increasingly used by nonurgent patients. Symptom checkers (SCs) offer on-demand access to disease suggestions and recommended actions, potentially improving overall patient flow. Contrary to the increasing use of SCs, there is a lack of supporting evidence based on direct patient use.

OBJECTIVE

This study aimed to compare the diagnostic accuracy, safety, usability, and acceptance of 2 SCs, Ada and Symptoma.

METHODS

A randomized, crossover, head-to-head, double-blinded study including consecutive adult patients presenting to the ED at University Hospital Erlangen. Patients completed both SCs, Ada and Symptoma. The primary outcome was the diagnostic accuracy of SCs. In total, 6 blinded independent expert raters classified diagnostic concordance of SC suggestions with the final discharge diagnosis as (1) identical, (2) plausible, or (3) diagnostically different. SC suggestions per patient were additionally classified as safe or potentially life-threatening, and the concordance of Ada's and physician-based triage category was assessed. Secondary outcomes were SC usability (5-point Likert-scale: 1=very easy to use to 5=very difficult to use) and SC acceptance net promoter score (NPS).

RESULTS

A total of 450 patients completed the study between April and November 2021. The most common chief complaint was chest pain (160/437, 37%). The identical diagnosis was ranked first (or within the top 5 diagnoses) by Ada and Symptoma in 14% (59/437; 27%, 117/437) and 4% (16/437; 13%, 55/437) of patients, respectively. An identical or plausible diagnosis was ranked first (or within the top 5 diagnoses) by Ada and Symptoma in 58% (253/437; 75%, 329/437) and 38% (164/437; 64%, 281/437) of patients, respectively. Ada and Symptoma did not suggest potentially life-threatening diagnoses in 13% (56/437) and 14% (61/437) of patients, respectively. Ada correctly triaged, undertriaged, and overtriaged 34% (149/437), 13% (58/437), and 53% (230/437) of patients, respectively. A total of 88% (385/437) and 78% (342/437) of participants rated Ada and Symptoma as very easy or easy to use, respectively. Ada's NPS was -34 (55% [239/437] detractors; 21% [93/437] promoters) and Symptoma's NPS was -47 (63% [275/437] detractors and 16% [70/437]) promoters.

CONCLUSIONS

Ada demonstrated a higher diagnostic accuracy than Symptoma, and substantially more patients would recommend Ada and assessed Ada as easy to use. The high number of unrecognized potentially life-threatening diagnoses by both SCs and inappropriate triage advice by Ada was alarming. Overall, the trustworthiness of SC recommendations appears questionable. SC authorization should necessitate rigorous clinical evaluation studies to prevent misdiagnoses, fatal triage advice, and misuse of scarce medical resources.

TRIAL REGISTRATION

German Register of Clinical Trials DRKS00024830; https://drks.de/search/en/trial/DRKS00024830.

Establishing a common ground: the future of triage systems

Triage systems, crucial for Emergency Departments, face unresolved doubts and issues that have not been addressed, coupled with increasing fragmentation due to a growing body of new evidence. International collaboration is essential for evidence-based triage solutions.

Assessing triage efficiency in Italy: a comparative study using simulated cases among nurses

BACKGROUND

Emergency Departments (EDs) across Italy use different triage systems, which vary from region to region. This study aimed to assess whether nurses working in different EDs assign triage codes in a similar and standardized manner.

METHODS

A multicenter observational simulation study involved the EDs of Bolzano Hospital, Merano Hospital, Pisa University Hospital, and Rovereto Hospital. All participating nurses were given 30 simulated clinical cases (vignettes) and asked to assign triage codes according to the triage systems used in their EDs. Subsequently, we assessed inter-rater agreement and evaluated if code assignment had different performance among hospitals in relation to different clinical outcomes.

RESULTS

Eighty-seven nurses participated in this study. There was marked variation in assigned triage codes both across hospitals and among individual operators. The kappa values for inter-rater agreement were 0.632 for Bolzano Hospital, 0.589 for Merano Hospital, 0.464 for Pisa University Hospital, and 0.574 for Rovereto Hospital. Sensitivity and specificity levels varied considerably for the same outcomes when comparing different hospitals.

CONCLUSION

There is a high degree of subjectivity in triage code assignment by ED nurses. In the interest of equitable care for patients, this variability within the same country is hardly acceptable.

Accuracy of Dental Symptom Checker Web Application in the Singapore Military Population

PURPOSE

Symptom checkers (SCs) are virtual health aids to assist laypersons in self-assessing dental complaints. This study aimed to investigate the triage performance, clinical efficacy, and user-perceived utility of a prototype dental SC, Toothbuddy, in assessing unscheduled dental complaints in Singapore.

METHODS

A pilot trial was conducted amongst all unscheduled dental attendees to military dental facilities in Singapore from January to May 2023. The accuracy of Toothbuddy to tele-triage dental conditions into 3 categories-routine, urgent, and emergency-was determined. Based on the patient-reported symptoms input, clinical recommendations were provided to users for each category. Thereafter, all dental attendees were clinically assessed to determine the definitive category. Finally, a user questionnaire assessed the application's functionality and utility and the user's satisfaction. Sensitivity and specificity analyses were performed.

RESULTS

During the study, 588 patients with unscheduled dental visits presented. Of these cases, 275 (46.8%) were evaluated to be routine dental conditions for which treatment could be delayed or self-managed, 243 (41.3%) required urgent dental care, and 60 (10.2%) required emergency dental intervention. The accuracy of Toothbuddy in identifying the correct category was 79.6% (468/588). Sensitivity and specificity in categorising routine vs non-routine conditions were 94.5% (95% confidence interval, 92.0%-97.1%) and 74.0% (95% confidence interval, 68.8%-79.2%), respectively. The app was generally well received and rated highly.

CONCLUSIONS

Preliminary data suggest that Toothbuddy can perform accurate dental self-assessment for a suitable range of common dental concerns and this is a promising platform for virtual advice on spontaneous dental issues. Furthermore, dental facilities are typically not sized to handle the large volumes of unplanned dental visits that may occur in the military population. SC apps to self-manage or delay treatment without adversely affecting disease prognosis may preserve the limited bandwidth of dental facilities in providing acute care and managing true dental emergencies expediently.

Enhancing triage accuracy: The influence of nursing education on risk prediction

AIM

This study aimed to compare the performance in risk prediction of various outcomes between specially trained triage nurses and the Manchester Triage System (MTS).

DESIGN

Prospective observational study.

METHODS

The study was conducted from June 1st to December 31st, 2023, at the Emergency Department of Merano Hospital. Triage nurses underwent continuous training through dedicated courses and daily audits. We compared the risk stratification performed by expert nurses with that of MTS on various outcomes such as mortality, hospitalisation, and urgency defined by the physicians. Comparisons were made using the Areas Under the Receiver Operating Characteristic curve (AUROC).

RESULTS

The agreement in code classification between the MTS and the expert nurse was very low. The AUROC curve analysis showed that the expert nurse outperformed the MTS in all outcomes. The triage nurse's experience led to statistically significant better stratification in admission rates, ICU admissions, and all outcomes based on the physician's assessment.

CONCLUSIONS

The continuous training of nurses enables them to achieve better risk prediction compared to standardized triage systems like MTS, emphasizing the utility and necessity of implementing continuous training pathways for these highly specialised personnel.

Comparison between the Smart Triage model and the Emergency Triage Assessment and Treatment guidelines in triaging children presenting to the emergency departments of two public hospitals in Kenya

Several triage systems have been developed, but little is known about their performance in low-resource settings. Evaluating and comparing novel triage systems to existing triage scales provides essential information about their added value, reliability, safety, and effectiveness before adoption. This study included children aged < 15 years who presented to the emergency departments of two public hospitals in Kenya between February and December 2021. We compared the performance of Emergency Triage Assessment and Treatment (ETAT) guidelines and Smart Triage (ST) models (ST model with independent triggers, and recalibrated ST model with independent triggers) in categorizing children into emergency, priority, and non-urgent triage categories. Sankey diagrams were used to visualize the distribution of children into similar or different triage categories by ETAT and ST models. Sensitivity, specificity, negative and positive predictive values for mortality and admission were calculated. 5618 children were enrolled, and the majority (3113, 55.4%) were aged between one and five years of age. Overall admission and mortality rates were 7% and 0.9%, respectively. ETAT classified 513 (9.2%) children into the emergency category compared to 1163 (20.8%) and 1161 (20.7%) by the ST model with independent triggers and recalibrated model with independent triggers, respectively. ETAT categorized 3089 (55.1%) children as non-urgent compared to 2097 (37.4%) and 2617 (46.7%) for the respective ST models. ETAT classified 191/395 (48.4%) admitted patients as emergencies compared to more than half by all the ST models. ETAT and ST models classified 25/49 (51%) and 39/49 (79.6%) deceased children as emergencies. Sensitivity for admission and mortality was 48.4% and 51% for ETAT and 74.9% and 79.6% for the ST models, respectively. Smart Triage shows potential for identifying critically ill children in low-resource settings, particularly when combined with independent triggers and performs comparably to ETAT. Evaluation of Smart Triage in other contexts and comparison to other triage systems is required.

Using primary healthcare facilities and patients' expectations about triage system: Patients' perspective from multisite Jordanian hospitals

BACKGROUND

Using primary healthcare facilities can decrease the tension and workload in emergency departments (EDs). This study aim to examine the patient's use of primary healthcare facilities before EDs visits and their expectations about the triage.

METHODS

A cross-sectional design was utilized in at various EDs in different hospitals. A convenience sample of 726 patients were enrolled and completed a self-administrated questionnaire.

RESULTS

The mean age of the participants was 38.1 (SD = 12.9). Most participants (68.2 %) did not have primary care physicians and did not want to know how long other patients waited (61.4 %). There are significant relationships between participants' desired to know how long other patients have been waiting and their age (X2 = 4.02, P < .05), education level (X2 = 13.5, P < .001), and current job (X2 = 9.90, p < .05). Also, periodic updates from EDs staff about the delays were significantly related to participants' age (X2 = 3.29), current job (X2 = 28.4), marital status (X2 = 8.93), and residency place (X2 = 9.94).

CONCLUSION

Educating patients about the triage system and the importance of using primary healthcare facilities is recommended to reduce ED waiting times and overload.

Nurses' moral judgements during emergency department triage - A prospective mixed multicenter study

INTRODUCTION

In EDs, triage ensures that patients whose condition requires immediate care are prioritized while reducing overcrowding. Previous studies have described the manifestation of caregivers' moral judgements of patients in EDs. The equal treatment of patients in clinical practice presents a major issue. Studying the impact of prejudice on clinical practice in the ED setting provides an opportunity to rethink clinical tools, organizations and future training needs. Our study sought to describe the moral judgements expressed by triage nurses during admission interviews in emergency departments and to assess their impact on patient management.

METHODS

An exploratory sequential mixed-method study was performed. The study was conducted between January 1, 2018, and February 18, 2018, in the EDs of three French hospitals. Five hundred and three patients and 79 triage nurses participated in the study. Audio recordings, observations and written handover reports made by nurses during admission triage interviews were analyzed with a view to discerning whether moral judgements were expressed in them. We studied the impact of moral judgements on patient management in the emergency department.

RESULTS

Abstract Moral judgements were made in 70% of the triage situations studied (n=351/503). They could be classified in seven categories. Patients were more likely to be subjected to moral judgements if they were over 75 years old, visibly disabled or if they had visible signs of alcohol intoxication. Being subjected to moral judgement was associated with differential treatment, including assignment of a triage score that differed from the theoretical triage score.

CONCLUSION

More than two thirds of patients admitted to EDs were triaged using moral criteria. Patients who were morally judged at the admission interview were more likely to be treated differently.

Efficacy and safety of a digital check-in and triage kiosk in emergency departments: a systematic review protocol

INTRODUCTION

Increasing demand for healthcare services worldwide has led to unprecedented challenges in managing patient flow and delivering timely care in emergency care settings. Overcrowding, prolonged waiting times, reduced patient satisfaction and increased mortality are some of the consequences of this increased demand. To address this issue, some healthcare providers have turned to digital systems, such as self-check-in kiosks, for efficient patient triage and prioritisation. While digital triage systems hold promise for efficient patient prioritisation, reduced data duplication, shorter waiting times, improved patient satisfaction, the impact on workflow, the accuracy of triage and staff workload require further exploration for successful implementation in emergency care settings. This systematic review aims to assess the efficacy and safety of digital check-in and triage kiosk implementation within emergency departments.

METHODS AND ANALYSIS

A systematic review will be conducted in MEDLINE (Ovid), Web of Science, Scopus and Science Direct and will include quantitative and mixed method studies with a significant quantitative component, related to self-service kiosk implementation in emergency departments. The outcomes of interest will focus on the efficacy and safety of digital triage, including triage time, workflow, the diagnostic accuracy of triage and adverse events. Risk of bias will be assessed using the Cochrane Risk of Bias Tool. A narrative synthesis will be used to summarise the findings of the included studies.

ETHICS AND DISSEMINATION

This review is exempt from ethical approval because it will be analysing published studies containing non-identifiable data. The findings will be disseminated through peer-reviewed publications.

PROSPERO REGISTRATION NUMBER

CRD42024481506.

Predictability of the emergency department triage system during the COVID-19 pandemic

OBJECTIVE

Emergency department (ED) triage systems are used to classify the severity and urgency of emergency patients, and Korean medical institutions use the Korean Triage and Acuity Scale (KTAS). During the COVID-19 pandemic, appropriate treatment for emergency patients was delayed due to various circumstances, such as overcrowding of EDs, lack of medical workforce resources, and increased workload on medical staff. The purpose of this study was to evaluate the accuracy of the KTAS in predicting the urgency of emergency patients during the COVID-19 pandemic.

METHODS

This study retrospectively reviewed patients who were treated in the ED during the pandemic period from January 2020 to June 2021. Patients were divided into COVID-19-screening negative (SN) and COVID-19-screening positive (SP) groups. We compared the predictability of the KTAS for urgent patients between the two groups.

RESULTS

From a total of 107,480 patients, 62,776 patients (58.4%) were included in the SN group and 44,704 (41.6%) were included in the SP group. The odds ratios for severity variables at each KTAS level revealed a more evident discriminatory power of the KTAS for severity variables in the SN group (P<0.001). The predictability of the KTAS for severity variables was higher in the SN group than in the SP group (area under the curve, P<0.001).

CONCLUSION

During the pandemic, the KTAS had low accuracy in predicting patients in critical condition in the ED. Therefore, in future pandemic periods, supplementation of the current ED triage system should be considered in order to accurately classify the severity of patients.

Drinking from the Holy Grail-Does a Perfect Triage System Exist? And Where to Look for It?

The Emergency Department (ED) is a facility meant to treat patients in need of medical assistance. The choice of triage system hugely impactsed the organization of any given ED and it is important to analyze them for their effectiveness. The goal of this review is to briefly describe selected triage systems in an attempt to find the perfect one. Papers published in PubMed from 1990 to 2022 were reviewed. The following terms were used for comparison: "ED" and "triage system". The papers contained data on the design and function of the triage system, its validation, and its performance. After studies comparing the distinct means of patient selection were reviewed, they were meant to be classified as either flawed or non-ideal. The validity of all the comparable segregation systems was similar. A possible solution would be to search for a new, measurable parameter for a more accurate risk estimation, which could be a game changer in terms of triage assessment. The dynamic development of artificial intelligence (AI) technologies has recently been observed. The authors of this study believe that the future segregation system should be a combination of the experience and intuition of trained healthcare professionals and modern technology (artificial intelligence).

Accuracy of telephone triage for predicting adverse outcomes in suspected COVID-19: an observational cohort study

OBJECTIVE

To assess accuracy of telephone triage in identifying need for emergency care among those with suspected COVID-19 infection and identify factors which affect triage accuracy.

DESIGN

Observational cohort study.

SETTING

Community telephone triage provided in the UK by Yorkshire Ambulance Service NHS Trust (YAS).

PARTICIPANTS

40 261 adults who contacted National Health Service (NHS) 111 telephone triage services provided by YAS between 18 March 2020 and 29 June 2020 with symptoms indicating COVID-19 infection were linked to Office for National Statistics death registrations and healthcare data collected by NHS Digital.

OUTCOME

Accuracy of triage disposition was assessed in terms of death or need for organ support up to 30 days from first contact.

RESULTS

Callers had a 3% (1200/40 261) risk of serious adverse outcomes (death or organ support). Telephone triage recommended self-care or non-urgent assessment for 60% (24 335/40 261), with a 1.3% (310/24 335) risk of adverse outcomes. Telephone triage had 74.2% sensitivity (95% CI: 71.6 to 76.6%) and 61.5% specificity (95% CI: 61% to 62%) for the primary outcome. Multivariable analysis suggested respiratory comorbidities may be overappreciated, and diabetes underappreciated as predictors of deterioration. Repeat contact with triage service appears to be an important under-recognised predictor of deterioration with 2 contacts (OR 1.77, 95% CI: 1.14 to 2.75) and 3 or more contacts (OR 4.02, 95% CI: 1.68 to 9.65) associated with false negative triage.

CONCLUSION

Patients advised to self-care or receive non-urgent clinical assessment had a small but non-negligible risk of serious clinical deterioration. Repeat contact with telephone services needs recognition as an important predictor of subsequent adverse outcomes.

The Effects of Displaying the Time Targets of the Manchester Triage System to Emergency Department Personnel: Prospective Crossover Study

BACKGROUND

The use of triage systems such as the Manchester Triage System (MTS) is a standard procedure to determine the sequence of treatment in emergency departments (EDs). When using the MTS, time targets for treatment are determined. These are commonly displayed in the ED information system (EDIS) to ED staff. Using measurements as targets has been associated with a decline in meeting those targets.

OBJECTIVE

This study investigated the impact of displaying time targets for treatment to physicians on processing times in the ED.

METHODS

We analyzed the effects of displaying time targets to ED staff on waiting times in a prospective crossover study, during the introduction of a new EDIS in a large regional hospital in Germany. The old information system version used a module that showed the time target determined by the MTS, while the new system version used a priority list instead. Evaluation was based on 35,167 routinely collected electronic health records from the preintervention period and 10,655 records from the postintervention period. Electronic health records were extracted from the EDIS, and data were analyzed using descriptive statistics and generalized additive models. We evaluated the effects of the intervention on waiting times and the odds of achieving timely treatment according to the time targets set by the MTS.

RESULTS

The average ED length of stay and waiting times increased when the EDIS that did not display time targets was used (average time from admission to treatment: preintervention phase=median 15, IQR 6-39 min; postintervention phase=median 11, IQR 5-23 min). However, severe cases with high acuity (as indicated by the triage score) benefited from lower waiting times (0.15 times as high as in the preintervention period for MTS1, only 0.49 as high for MTS2). Furthermore, these patients were less likely to receive delayed treatment, and we observed reduced odds of late treatment when crowding occurred.

CONCLUSIONS

Our results suggest that it is beneficial to use a priority list instead of displaying time targets to ED personnel. These time targets may lead to false incentives. Our work highlights that working better is not the same as working faster.

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.

Performance of the Interagency Integrated Triage Tool in a resource-constrained emergency department during the COVID-19 pandemic

BACKGROUND

The Interagency Integrated Triage Tool (IITT) is a three-tier triage instrument recommended by the World Health Organization, but only the pilot version of the tool has been comprehensively assessed for its validity and reliability. This study sought to evaluate the performance of the IITT in a resource-constrained emergency department (ED) during the COVID-19 pandemic.

METHODS

This prospective observational study was conducted at ANGAU Memorial Provincial Hospital in Lae, Papua New Guinea. The study period commenced approximately six weeks after introduction of the IITT, coinciding with a major COVID-19 wave. The primary outcome was sensitivity for the detection of time-critical illness, defined by eight pre-specified conditions. Secondary outcomes included the relationship between triage category and disposition. Inter-rater reliability was assessed using Cohen's Kappa.

RESULTS

There were 759 eligible presentations during the study period. Thirty patients (4.0%) were diagnosed with one of the eight pre-specified time-critical conditions and 21 were categorised as red or yellow, equating to a sensitivity of 70.0% (95%CI 50.6-85.3). There was a clear association between triage category and disposition, with 22 of 53 red patients (41.5%), 72 of 260 yellow patients (27.7%) and 22 of 452 green patients (4.9%) admitted (p = <0.01). Negative predictive values for admission and death were 95.1% (95%CI 92.7-96.9) and 99.3% (95%CI 98.1-99.9) respectively. Among a sample of 106 patients, inter-rater reliability was excellent (κ = 0.83) and the median triage assessment time was 94 seconds [IQR 57-160].

CONCLUSION

In this single-centre study, the IITT's sensitivity for the detection of time-critical illness was comparable to previous evaluations of the tool and within the performance range reported for other triage instruments. There was a clear relationship between triage category and disposition, suggesting the tool can predict ED outcomes. Health service pressures related to COVID-19 may have influenced the findings.

The Value of Emergency Care Data Set (ECDS) Presentation Codes for Predicting Mortality and Inpatient Admission

BACKGROUND

 Early identification of patients at higher risk of death and hospital admission is an important problem in Emergency Departments (ED). Most triage scales were developed before current electronic healthcare records were developed. The implementation of a national Emergency Care Data Set (ECDS) allows for the standardised recording of presenting complaints and the use of Electronic Patient Records (EPR) offers the potential for automated triage. The mortality risk and need for hospital admission associated with the different presenting complaints in a standardised national data set has not been previously reported. This study aimed to quantify the risks of death and hospitalisation from presenting complaints. This would be valuable in developing automated triage tools and decision support software.

METHODS

We conducted an observational retrospective cohort study on patients who visited a single ED in 2021. The presenting complaints related to subsequent attendances were excluded. This patient list was then manually matched with a routinely collected list of deaths. All deaths that occurred within 30 days of attendance were included.

RESULTS

Data was collected from 84,999 patients, of which 1,159 people died within 30 days of attendance. The mortality rate was the highest in cardiac arrest [32 (78.1%)], cardiac arrest due to trauma [2(50%)] and respiratory arrest [3(50%)]. Drowsy [17(12%)], hypothermia [3(13%)] and cyanosis [1(10%)] were also high-risk categories. Chest pain [34(0.6%)] was not a high-risk presenting complaint.

CONCLUSION

The initial presenting complaint in ECDS may be useful to identify people at higher and lower risk of death. This information is useful for building automated triage models.

Systematic review: What is the impact of triage implementation on clinical outcomes and process measures in low- and middle-income country emergency departments?

INTRODUCTION

Triage is widely regarded as an essential function of emergency care (EC) systems, especially in resource-limited settings. Through a systematic search and review of the literature, we investigated the effect of triage implementation on clinical outcomes and process measures in low- and middle-income country (LMIC) emergency departments (EDs).

METHODS

Structured searches were conducted using MEDLINE, CENTRAL, EMBASE, CINAHL, and Global Health. Eligible articles identified through screening and full-text review underwent risk-of-bias assessment using the Newcastle-Ottawa Scale. The quality of evidence for each effect measure was summarized using GRADE.

RESULTS

Among 10,394 articles identified through the search strategy, 58 underwent full-text review and 16 were included in the final synthesis. All utilized pre-/postintervention methods and a majority were single center. Effect measures included mortality, waiting time, length of stay, admission rate, and patient satisfaction. Of these, ED mortality and time to clinician assessment were evaluated most frequently. The majority of studies using these outcomes identified a positive effect, namely a reduction in deaths and waiting time among patients presenting for EC. The quality of the evidence was moderate for these measures but low or very low for all other outcomes and process indicators.

CONCLUSIONS

There is moderate quality of evidence supporting an association between the introduction of triage and a reduction in deaths and waiting time. Although the available data support the value of triage in LMIC EDs, the risk of confounding and publication bias is significant. Future studies will benefit from more rigorous research methods.

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

BACKGROUND

Robust and accurate prediction of severity for patients with COVID-19 is crucial for patient triaging decisions. Many proposed models were prone to either high bias risk or low-to-moderate discrimination. Some also suffered from a lack of clinical interpretability and were developed based on early pandemic period data. Hence, there has been a compelling need for advancements in prediction models for better clinical applicability.

OBJECTIVE

The primary objective of this study was to develop and validate a machine learning-based Robust and Interpretable Early Triaging Support (RIETS) system that predicts severity progression (involving any of the following events: intensive care unit admission, in-hospital death, mechanical ventilation required, or extracorporeal membrane oxygenation required) within 15 days upon hospitalization based on routinely available clinical and laboratory biomarkers.

METHODS

We included data from 5945 hospitalized patients with COVID-19 from 19 hospitals in South Korea collected between January 2020 and August 2022. For model development and external validation, the whole data set was partitioned into 2 independent cohorts by stratified random cluster sampling according to hospital type (general and tertiary care) and geographical location (metropolitan and nonmetropolitan). Machine learning models were trained and internally validated through a cross-validation technique on the development cohort. They were externally validated using a bootstrapped sampling technique on the external validation cohort. The best-performing model was selected primarily based on the area under the receiver operating characteristic curve (AUROC), and its robustness was evaluated using bias risk assessment. For model interpretability, we used Shapley and patient clustering methods.

RESULTS

Our final model, RIETS, was developed based on a deep neural network of 11 clinical and laboratory biomarkers that are readily available within the first day of hospitalization. The features predictive of severity included lactate dehydrogenase, age, absolute lymphocyte count, dyspnea, respiratory rate, diabetes mellitus, c-reactive protein, absolute neutrophil count, platelet count, white blood cell count, and saturation of peripheral oxygen. RIETS demonstrated excellent discrimination (AUROC=0.937; 95% CI 0.935-0.938) with high calibration (integrated calibration index=0.041), satisfied all the criteria of low bias risk in a risk assessment tool, and provided detailed interpretations of model parameters and patient clusters. In addition, RIETS showed potential for transportability across variant periods with its sustainable prediction on Omicron cases (AUROC=0.903, 95% CI 0.897-0.910).

CONCLUSIONS

RIETS was developed and validated to assist early triaging by promptly predicting the severity of hospitalized patients with COVID-19. Its high performance with low bias risk ensures considerably reliable prediction. The use of a nationwide multicenter cohort in the model development and validation implicates generalizability. The use of routinely collected features may enable wide adaptability. Interpretations of model parameters and patients can promote clinical applicability. Together, we anticipate that RIETS will facilitate the patient triaging workflow and efficient resource allocation when incorporated into a routine clinical practice.

Reliability of ChatGPT for performing triage task in the emergency department using the Korean Triage and Acuity Scale

Background

Artificial intelligence (AI) technology can enable more efficient decision-making in healthcare settings. There is a growing interest in improving the speed and accuracy of AI systems in providing responses for given tasks in healthcare settings.

Objective

This study aimed to assess the reliability of ChatGPT in determining emergency department (ED) triage accuracy using the Korean Triage and Acuity Scale (KTAS).

Methods

Two hundred and two virtual patient cases were built. The gold standard triage classification for each case was established by an experienced ED physician. Three other human raters (ED paramedics) were involved and rated the virtual cases individually. The virtual cases were also rated by two different versions of the chat generative pre-trained transformer (ChatGPT, 3.5 and 4.0). Inter-rater reliability was examined using Fleiss' kappa and intra-class correlation coefficient (ICC).

Results

The kappa values for the agreement between the four human raters and ChatGPTs were .523 (version 4.0) and .320 (version 3.5). Of the five levels, the performance was poor when rating patients at levels 1 and 5, as well as case scenarios with additional text descriptions. There were differences in the accuracy of the different versions of GPTs. The ICC between version 3.5 and the gold standard was .520, and that between version 4.0 and the gold standard was .802.

Conclusions

A substantial level of inter-rater reliability was revealed when GPTs were used as KTAS raters. The current study showed the potential of using GPT in emergency healthcare settings. Considering the shortage of experienced manpower, this AI method may help improve triaging accuracy.

Triage Accuracy of Emergency Nurses: An Evidence-Based Review

INTRODUCTION

Accurate triage assessment by emergency nurses is essential for prioritizing patient care and providing appropriate treatment. Undertriage and overtriage remain an ongoing issue in care of patients who present to the emergency department. The purpose of this literature review was to examine factors associated with triage accuracy in the emergency department.

METHODS

We conducted an evidence-based literature review using the Cumulative Index to Nursing and Allied Health Literature, PubMed, and Embase. The search focused on peer-reviewed articles in English, available in full text, published between January 2011 and December 2021.

RESULTS

A total of 14 articles met inclusion criteria and revealed the following 3 themes for triage accuracy: triage nurse characteristics, patient characteristics, and work environment. Triage nurses' accuracy rates ranged from 59.3% to 82%, with experience in triage associated with higher accuracy. Patient characteristics influenced triage accuracy, with nontrauma patients being undertriaged and trauma patients often overtriaged. The work environment played a role, as accuracy rates varied based on shift time and patient volume. Competing systems between prehospital and ED triage posed challenges and affected accuracy during fluctuations in patient volumes.

DISCUSSION

This review underscores the complex nature of ED triage accuracy. It highlights the importance of nurse experience, training programs, patient characteristics, and the work environment in enhancing triage decision making. Enhanced understanding of these factors can inform strategies to optimize triage accuracy and improve patient outcomes.

Applications of natural language processing at emergency department triage: A narrative review

INTRODUCTION

Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this scoping review is to evaluate how NLP has been applied to data acquired at ED triage, assess if NLP based models outperform humans or current risk stratification techniques when predicting outcomes, and assess if incorporating free-text improve predictive performance of models when compared to predictive models that use only structured data.

METHODS

All English language peer-reviewed research that applied an NLP technique to free-text obtained at ED triage was eligible for inclusion. We excluded studies focusing solely on disease surveillance, and studies that used information obtained after triage. We searched the electronic databases MEDLINE, Embase, Cochrane Database of Systematic Reviews, Web of Science, and Scopus for medical subject headings and text keywords related to NLP and triage. Databases were last searched on 01/01/2022. Risk of bias in studies was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST). Due to the high level of heterogeneity between studies and high risk of bias, a metanalysis was not conducted. Instead, a narrative synthesis is provided.

RESULTS

In total, 3730 studies were screened, and 20 studies were included. The population size varied greatly between studies ranging from 1.8 million patients to 598 triage notes. The most common outcomes assessed were prediction of triage score, prediction of admission, and prediction of critical illness. NLP models achieved high accuracy in predicting need for admission, triage score, critical illness, and mapping free-text chief complaints to structured fields. Incorporating both structured data and free-text data improved results when compared to models that used only structured data. However, the majority of studies (80%) were assessed to have a high risk of bias, and only one study reported the deployment of an NLP model into clinical practice.

CONCLUSION

Unstructured free-text triage notes have been used by NLP models to predict clinically relevant outcomes. However, the majority of studies have a high risk of bias, most research is retrospective, and there are few examples of implementation into clinical practice. Future work is needed to prospectively assess if applying NLP to data acquired at ED triage improves ED outcomes when compared to usual clinical practice.

Factors influencing the occurrence of ambulatory care sensitive conditions in the emergency department - a single-center cross-sectional study

Background and importance

The differentiation between patients who require urgent care and those who could receive adequate care through ambulatory services remains a challenge in managing patient volumes in emergency departments (ED). Different approaches were pursued to characterize patients that could safely divert to ambulatory care. However, this characterization remains challenging as the urgency upon presentation is assessed based on immediately available characteristics of the patients rather than on subsequent diagnoses. This work employs a core set of Ambulatory Care Sensitive Conditions (core-ACSCs) in an ED to describe conditions that do not require inpatient care if treated adequately in the ambulatory care sector. It subsequently analyzes the corresponding triage levels and admission status to determine whether core-ACSCs relevantly contribute to patient volumes in an ED.

Settings and participants

Single center cross-sectional analysis of routine data of a tertiary ED in 2019.

Outcome measures and analysis

The proportion of core-ACSCs among all presentations was assessed. Triage levels were binarily classified as "urgent" and "non-urgent," and the distribution of core-ACSCs in both categories was studied. Additionally, the patients presenting with core-ACSCs requiring inpatient care were assessed based on adjusted residuals and logistic regression. The proportion being discharged home underwent further investigation.

Main results

This study analyzed 43,382 cases of which 10.79% (n = 4,683) fell under the definition of core-ACSC categories. 65.2% of all core-ACSCs were urgent and received inpatient care in 62.8% of the urgent cases. 34.8% of the core-ACSCs were categorized as non-urgent, 92.4% of wich were discharged home. Age, triage level and sex significantly affected the odds of requiring hospital admission after presenting with core-ACSCs. The two core-ACSCs that mainly contributed to non-urgent cases discharged home after the presentation were "back pain" and "soft tissue disorders."

Discussion

Core-ACSCs contribute relevantly to overall ED patient volume but cannot be considered the primary drivers of crowding. However, once patients presented to the ED with what was later confirmed as a core-ACSC, they required urgent care in 65.2%. This finding highlights the importance of effective ambulatory care to avoid emergency presentations. Additionally, the core-ACSC categories "back pain" and "soft tissue disorders" were often found to be non-urgent and discharged home. Although further research is required, these core-ACSCs could be considered potentially avoidable ED presentations.

Clinical trial registration

The study was registered in the German trials register (DRKS-ID: DRKS00029751) on 2022-07-22.

Machine learning model identification and prediction of patients' need for ICU admission: A systematic review

BACKGROUND

The emergency department (ED) triage process serves as a crucial first step for patients seeking acute care, This initial assessment holds crucial implications for patient survival and prognosis. In this study, a systematic review of the existing literature was performed to investigate the performance of machine learning (ML) models in recognizing and predicting the need for intensive care among ED patients.

METHODS

Four prominent databases (PubMed, Embase, Cochrane Library and Web of Science) were searched for relevant literature published up to April 28, 2023. The Prediction model study Risk of Bias Assessment Tool (PROBAST) was employed to evaluate the risk of bias and feasibility of prediction models.

RESULTS

In ten studies, the main algorithms used were Gradient Boostin, Logistic Regressio, Neural Network, Support Vector Machines, Random Forest. The performance of each model was as follows: Gradient Boosting had a sensitivity range of 0.3 to 0.96, specificity range of 0.6 to 0.99, accuracy range of 0.37 to 0.99, precision range of 0.3 to 0.96, and AUC value range of 0.68 to 0.93; Logistic Regression had a sensitivity range of 0.46 to 0.97, specificity range of 0.28 to 0.99, accuracy range of 0.66 to 0.97, precision range of 0.27 to 0.63, and AUC value range of 0.72 to 0.97; Neural Networks had a sensitivity range of 0.45 to 0.96, specificity range of 0.58 to 0.99, accuracy range of 0.36 to 0.97, precision range of 0.27 to 0.96, and AUC value range of 0.67 to 0.91; Support Vector Machines had a sensitivity range of 0.49 to 0.83, specificity range of 0.94 to 0.98, accuracy range of 0.33 to 0.97, precision range of 0.53 to 0.94, and AUC values were not reported; Random Forests had a sensitivity range of 0.75 to 0.91, specificity range of 0.77 to 0.94, accuracy range of 0.35 to 0.77, precision range of 0.36 to 0.94, and AUC value of 0.83.

CONCLUSION

ML models have demonstrated good performance in identifying and predicting critically ill patients in ED triage. However, because of the limited number of studies on each model, further high-quality prospective research is needed to validate these findings.

Triage: A Global Perspective

Triage is a process by which patients are assessed, classified, and sorted based on their presenting complaint and clinical urgency, providing assurance for timely access to emergency care. The goal is to get the right person to the right place, in the right amount of time, for the right reason, and within the context of resource availability. In many countries, a standardized triage system, underpinned through the use of guidelines, is used to provide clinicians with support and guidance. Triage is a globally adopted principle, and although triage guidelines are used in many countries, no single system has been internationally adopted. This paper discusses the importance of how triage process standardization improves patient care, resource management, and benchmarking at local, national, and international levels by applying 5 internationally recognized triage systems to fictional case studies. Evaluation of similarities and differences in severity scores, with a gap analysis, occurs.

Prospective study of pain and patient outcomes in the emergency department: a tale of two pain assessment methods

BACKGROUND

Accurate pain assessment is essential in the emergency department (ED) triage process. Overestimation of pain intensity, however, can lead to unnecessary overtriage. The study aimed to investigate the influence of pain on patient outcomes and how pain intensity modulates the triage's predictive capabilities on these outcomes.

METHODS

A prospective observational cohort study was conducted at a tertiary care hospital, enrolling adult patients in the triage station. The entire triage process was captured on video. Two pain assessment methods were employed: (1) Self-reported pain score in the Taiwan Triage and Acuity Scale, referred to as the system-based method; (2) Five physicians independently assigned triage levels and assessed pain scores from video footage, termed the physician-based method. The primary outcome was hospitalization, and secondary outcomes included ED length of stay (EDLOS) and ED charges.

RESULTS

Of the 656 patients evaluated, the median self-reported pain score was 4 (interquartile range, 0-7), while the median physician-rated pain score was 1.5 (interquartile range, 0-3). Increased self-reported pain severity was not associated with prolonged EDLOS and increased ED charges, but a positive association was identified with physician-rated pain scores. Using the system-based method, the predictive efficacy of triage scales was lower in the pain groups than in the pain-free group (area under the receiver operating curve, [AUROC]: 0.615 vs. 0.637). However, with the physician-based method, triage scales were more effective in predicting hospitalization among patients with pain than those without (AUROC: 0.650 vs. 0.636).

CONCLUSIONS

Self-reported pain seemed to diminish the predictive accuracy of triage for hospitalization. In contrast, physician-rated pain scores were positively associated with longer EDLOS, increased ED charges, and enhanced triage predictive capability for hospitalization. Pain, therefore, appears to modulate the relationship between triage and patient outcomes, highlighting the need for careful pain evaluation in the ED.

COVID-19: Association of risk classification with the Modified Early Warning Score and hospital outcomes

OBJECTIVE

to evaluate the association of the risk classification categories with the Modified Early Warning Score and the outcomes of COVID-19 patients in the emergency service.

METHOD

a crosssectional study carried out with 372 patients hospitalized with a COVID-19 diagnosis and treated at the Risk Classification Welcoming area from the Emergency Room. In this study, the patients' Modified Early Warning Score was categorized into without and with clinical deterioration, from 0 to 4 and from 5 to 9, respectively. Clinical deterioration was considered to be acute respiratory failure, shock and cardiopulmonary arrest.

RESULTS

the mean Modified Early Warning Score was 3.34. In relation to the patients' clinical deterioration, it was observed that, in 43%, the time for deterioration was less than 24 hours and that 65.9% occurred in the Emergency Room. The most frequent deterioration was acute respiratory failure (69.9%) and the outcome was hospital discharge (70.3%).

CONCLUSION

COVID-19 patients who had a Modified Early Warning Scores > 4 were associated with the urgent, very urgent and emergency risk classification categories, had more clinical deterioration, such as respiratory failure and shock, and evolved more to death, which shows that the Risk Classification Protocol correctly prioritized patients at risk of life.

Improved patient mortality predictions in emergency departments with deep learning data-synthesis and ensemble models

The triage process in emergency departments (EDs) relies on the subjective assessment of medical practitioners, making it unreliable in certain aspects. There is a need for a more accurate and objective algorithm to determine the urgency of patients. This paper explores the application of advanced data-synthesis algorithms, machine learning (ML) algorithms, and ensemble models to predict patient mortality. Patients predicted to be at risk of mortality are in a highly critical condition, signifying an urgent need for immediate medical intervention. This paper aims to determine the most effective method for predicting mortality by enhancing the F1 score while maintaining high area under the receiver operating characteristic curve (AUC) score. This study used a dataset of 7325 patients who visited the Yonsei Severance Hospital's ED, located in Seoul, South Korea. The patients were divided into two groups: patients who deceased in the ED and patients who didn't. Various data-synthesis techniques, such as SMOTE, ADASYN, CTGAN, TVAE, CopulaGAN, and Gaussian Copula, were deployed to generate synthetic patient data. Twenty two ML models were then utilized, including tree-based algorithms like Decision tree, AdaBoost, LightGBM, CatBoost, XGBoost, NGBoost, TabNet, which are deep neural network algorithms, and statistical algorithms such as Support Vector Machine, Logistic Regression, Random Forest, k-nearest neighbors, and Gaussian Naive Bayes, as well as Ensemble Models which use the results from the ML models. Based on 21 patient information features used in the pandemic influenza triage algorithm (PITA), the models explained previously were applied to aim for the prediction of patient mortality. In evaluating ML algorithms using an imbalanced medical dataset, conventional metrics like accuracy scores or AUC can be misleading. This paper emphasizes the importance of using the F1 score as the primary performance measure, focusing on recall and specificity in detecting patient mortality. The highest-ranked model for predicting mortality utilized the Gaussian Copula data-synthesis technique and the CatBoost classifier, achieving an AUC of 0.9731 and an F1 score of 0.7059. These findings highlight the effectiveness of machine learning algorithms and data-synthesis techniques in improving the prediction performance of mortality in EDs.

Comparison between local and three validated triage systems in an emergency department for 2126 children under 3 months

AIM

Triage of patients less than 3 months old was not already studied. The aim was to evaluate Paediatric Emergency Department triage in patients less than 3 months old and newborns using a local system in comparison with three validated paediatric triage systems (Canadian Triage and Acuity Scale, Manchester Triage System and Emergency Severity Index) and to determine inter-system agreement.

METHODS

All admissions of patients less than 3 months old admitted to the Emergency Department of the Saint Vincent University Hospital between April 2018 and December 2019 were included. The local triage system level was determined prospectively for comparison with retrospectively calculated triage levels of the validated systems. Hospitalisation rates were compared and inter-system agreements determined.

RESULTS

Among emergency admissions, 2126 were included (55% males, mean age 45 days). Hospitalisation rate increased with priority severity as determined by all triage systems studied. Cohen's kappa showed slight agreement between the local triage system and the Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System (weighted kappa = 0.133, 0.185 and 0.157 respectively).

CONCLUSION

Whether prospective or retrospective triage used, the systems studied exhibited good association with hospitalisation rate for patients aged less than 3 months and newborn infants.

Patterns and outcome of unplanned care in lung cancer patients: an observational study in a medical oncology department

Background

There is increasing interest in unplanned care utilization among lung cancer patients and its evaluation should allow the identification of areas for quality improvement. Being a major priority for transformation in oncology, we aim to measure the risk and burden of unplanned care in a medical oncology department and identify factors that determine acute care.

Methods

This was an observational retrospective cohort study that included all lung cancer patients treated at Puerta de Hierro-Majadahonda University Hospital between January 1st 2016 and December 31st 2020. Data cut off: June 30th, 2021. The main objective was to assess the incidence of unplanned care, emergency department (ED) visits and unplanned hospital admissions, from the first visit to the medical oncology service and its potential conditioning variables, considering patient death as a competitive event. As secondary objectives, a description and a quality of unplanned care evaluation was carried out.

Results

A total of 821 lung cancer patients, all histologies and stages, were included (median follow-up: 32.8 months). Six hundred and eighty-one patients required consultation in the ED (82.9%), and 558 required an unplanned admission (68%). Eighty-six percent of ED consultations and 80.9% of unplanned hospital admissions were related to cancer or its treatment. The 1-year cumulative incidence for ED consultation and for unplanned hospital admission was 71.3% (95% CI: 67.8-74.5%) and 56.7% (95% CI: 53-60%), respectively. In the multivariable analysis, a higher tumor stage increased the risk of consultation in the ED, while a higher stage, Eastern Cooperative Oncology Group performance status (ECOG PS) 2 compared to ECOG PS 0, male sex, opioid or steroid use at first consultation increased the risk of unplanned admission.

Conclusions

Our study shows that lung cancer patients have an extremely high demand for unplanned care. It is an early need and related to cancer in the majority of consultations and admissions and therefore a key issue for the management of oncology departments. We must optimize the follow-up of patients with a higher risk of unplanned care, advanced lung cancer or symptomatic patients, incorporating remote monitoring strategies and early interventions, as developing specific urgent care pathways for a better comprehensive cancer care.

Validation of a modified South African triage scale in a high-resource setting: a retrospective cohort study

BACKGROUND

Triage systems are widely used in emergency departments, but are not always validated. The South African Triage Scale (SATS) has mainly been studied in resource-limited settings. The aim of this study was to determine the validity of a modified version of the SATS for the general population of patients admitted to an ED at a tertiary hospital in a high-income country. The secondary objective was to study the triage performance according to age and patient categories.

METHODS

We conducted a retrospective cohort study of patients presenting to the Emergency Department of Haukeland University Hospital in Norway during a four-year period. We used short-term mortality, ICU admission, and the need for immediate surgery and other interventions as the primary endpoints.

RESULTS

A total of 162,034 emergency department visits were included in the analysis. The negative predictive value of a low triage level to exclude severe illness was 99.1% (95% confidence interval: 99.0-99.2%). The level of overtriage, defined as the proportion of patients assigned to a high triage level who were not admitted to the hospital, was 4.1% (3.9-4.2%). Receiver operating characteristic (ROC) curves showed an area under the ROC for the detection of severe illness of 0.874 (95% confidence interval: 0.870-0.879) for all patients and 0.856 (0.837-0.875), 0.884 (0.878-0.890) and 0.869 (0.862-0.876) for children, adults and elderly individuals respectively.

CONCLUSION

We found that the modified SATS had a good sensitivity to identify short-term mortality, ICU admission, and the need for rapid surgery and other interventions. The sensitivity was higher in adults than in children and higher in medical patients than in surgical patients. The over- and undertriage rates were acceptable.

Red cell distribution width and mortality in older patients with frailty in the emergency department

BACKGROUND

The red cell distribution width (RDW) reflects the degree of heterogeneity of red blood cells. Elevated RDW is associated both with frailty and with increased mortality in hospital-admitted patients. In this study we evaluate whether high RDW values are associated with mortality in older emergency department (ED) patients with frailty, and if the association is independent of the degree of frailty.

METHODS

We included ED patients with the following criteria: ≥ 75 years of age, Clinical Frailty Scale (CFS) score of 4 to 8, and RDW % measured within 48 h of ED admission. Patients were allocated to six classes by their RDW value: ≤ 13%, 14%, 15%, 16%, 17%, and ≥ 18%. The outcome was death within 30 days of ED admission. Crude and adjusted odds ratios (OR) with 95% confidence intervals (CI) for a one-class increase in RDW for 30-day mortality were calculated via binary logistic regression analysis. Age, gender and CFS score were considered as potential confounders.

RESULTS

A total of 1407 patients (61.2% female), were included. The median age was 85 with an inter-quartile range (IQR) of 80-89, median CFS score 6 (IQR: 5-7), and median RDW 14 (IQR: 13-16). Of the included patients, 71.9% were admitted to hospital wards. A total of 85 patients (6.0%) died during the 30-day follow-up. Mortality rate was associated with RDW increase (p for trend < .001). Crude OR for a one-class increase in RDW for 30-day mortality was 1.32 (95% CI: 1.17-1.50, p < .001). When adjusted for age, gender and CFS-score, OR of mortality for one-class RDW increase was still 1.32 (95% CI: 1.16-1.50, p < .001).

CONCLUSION

Higher RDW values had a significant association with increased 30-day mortality risk in frail older adults in the ED, and this risk was independent of degree of frailty. RDW is a readily available biomarker for most ED patients. It might be beneficial to include it in risk stratification of older frail ED patients to identify those who could benefit from further diagnostic assessment, targeted interventions, and care planning.

"I Was Here First, Why Did They Go Before Me": Examining Patients'Perceptions of Priority in a Psychometric Study of Emergency Department Triage

INTRODUCTION

Unrealistic patient expectations for wait times can lead to poor satisfaction. This study's dual purpose was: (1) to address disparities between patients' perceived priority level and the Emergency Severity Index (ESI) assigned by emergency room triage nurses; and (2) to evaluate validity and reliability of using the Patient Perception of Priority to be Seen Survey (PPPSS) to investigate patient expectations for emergency department urgency.

METHODS

A two-group pretest-posttest quasi-experimental approach compared patient urgency opinions to nurse urgency ratings with and without a scripted educational intervention. This tested how closely patient perceptions were related to triage nurse ratings.

RESULTS

Reliability for the PPPSS was acceptable (reliability = 0.75). Patients who were rated lower urgency on the ESI by triage nurses tended to self-report higher urgency (rho = -0.44, P < .01). Attitudes were more consistent in the posttest patient group who were exposed to the scripted verbal description of emergency department procedures (χ² (1, N = 352) = 8.09, P < .01). Patients who disagreed with emergency nurse scores tended to be younger on average (eg, < 40 years old; rho = 0.69, P < .01). Male identified patients tended to be rated both by nurses and themselves as higher urgency (beta = 0.18, P = .02).

DISCUSSION

We recommend the PPPSS for nurses and researchers to quickly assess patient expectations. Additionally, promoting patient understanding through a scripted educational strategy about the ESI system may also result in improvements in communication between patients and nurses.