Diagnostic precision of triage algorithms for mass casualty incidents. English version

A Monte Carlo method for the quantitative analysis of triage algorithms in mass casualty events

Objective.In mass casualty scenarios, efficient triage algorithms are used to prioritize medical care when resources are outnumbered by victims. This research proposes a computational approach to quantitatively analyze and optimize triage algorithms by developing a Monte Carlo code which is subsequently validated against the few quantitative data.Approach. The developed Monte Carlo code is used to simulate several mass casualty events, namely car accidents, burns, shootings, sinking ships and a human stampede. Four triage algorithms- modified simple triage and rapid treatment, primäres Ranking zur initialen Orientierung im Rettungsdienst, CareFlight, and field triage score (FTS)-are evaluated using metrics like mortality, overtriage, undertriage, sensitivity, and specificity.Main results.Results indicate that, on average, the analyzed algorithms achieve about 35% accuracy in classifying critical casualties when compared to a perfect algorithm, with FTS being the less accurate. However, when all casualties are considered, algorithm performance improves to around 63% of a perfect algorithm, except for FTS. The study identifies an increased probability of false positives for red categorization due to comorbidities and a higher tendency for false negatives in casualties with burns or internal trunk injuries.Significance.Despite variations in vital sign measurements, triage classification results do not depend on the measurement uncertainties of the paramedics. The ethically challenging decision, of withholding medical care from low-survival probability victims, leads to a 63% reduction in mortality among critical casualties. This research establishes a quantitative method for triage algorithm studies, highlighting their robustness to measurement uncertainties.

Validation of secondary triage algorithms for mass casualty incidents : A simulation-based study-English version

BACKGROUND

In the event of a mass casualty incident (MCI), the situation-related shortage of medical resources does not end when the patients are transported from the scene of the incident. Consequently, an initial triage is required in the receiving hospitals. In the first step, the aim of this study was to create a reference patient vignette set with defined triage categories. This allowed a computer-aided evaluation of the diagnostic quality of triage algorithms for MCI situations in the second step.

METHODS

A total of 250 case vignettes validated in practice were entered into a multistage evaluation process by initially 6 and later 36 triage experts. This algorithm-independent expert evaluation of all vignettes-served as the gold standard for analyzing the diagnostic quality of the following triage algorithms: Manchester triage system (MTS module MCI), emergency severity index (ESI), Berlin triage algorithm (BER), the prehospital algorithms PRIOR and mSTaRT, and two project algorithms from a cooperation between the Federal Office of Civil Protection and Disaster Assistance (BBK) and the Hashemite Kingdom of Jordan-intrahospital Jordanian-German project algorithm (JorD) and prehospital triage algorithm (PETRA). Each patient vignette underwent computerized triage through all specified algorithms to obtain comparative test quality outcomes.

RESULTS

Of the original 250 vignettes, a triage reference database of 210 patient vignettes was validated independently of the algorithms. These formed the gold standard for comparison of the triage algorithms analyzed. Sensitivities for intrahospital detection of patients in triage category T1 ranged from 1.0 (BER, JorD, PRIOR) to 0.57 (MCI module MTS). Specificities ranged from 0.99 (MTS and PETRA) to 0.67 (PRIOR). Considering Youden's index, BER (0.89) and JorD (0.88) had the best overall performance for detecting patients in triage category T1. Overtriage was most likely with PRIOR, and undertriage with the MCI module of MTS. Up to a decision for category T1, the algorithms require the following numbers of steps given as the median and interquartile range (IQR): ESI 1 (1-2), JorD 1 (1-4), PRIOR 3 (2-4), BER 3 (2-6), mSTaRT 3 (3-5), MTS 4 (4-5) and PETRA 6 (6-8). For the T2 and T3 categories the number of steps until a decision and the test quality of the algorithms are positively interrelated.

CONCLUSION

In the present study, transferability of preclinical algorithm-based primary triage results to clinical algorithm-based secondary triage results was demonstrated. The highest diagnostic quality for secondary triage was provided by the Berlin triage algorithm, followed by the Jordanian-German project algorithm for hospitals, which, however, also require the most algorithm steps until a decision.

Covid-19 triage in the emergency department 2.0: how analytics and AI transform a human-made algorithm for the prediction of clinical pathways

The Covid-19 pandemic has pushed many hospitals to their capacity limits. Therefore, a triage of patients has been discussed controversially primarily through an ethical perspective. The term triage contains many aspects such as urgency of treatment, severity of the disease and pre-existing conditions, access to critical care, or the classification of patients regarding subsequent clinical pathways starting from the emergency department. The determination of the pathways is important not only for patient care, but also for capacity planning in hospitals. We examine the performance of a human-made triage algorithm for clinical pathways which is considered a guideline for emergency departments in Germany based on a large multicenter dataset with over 4,000 European Covid-19 patients from the LEOSS registry. We find an accuracy of 28 percent and approximately 15 percent sensitivity for the ward class. The results serve as a benchmark for our extensions including an additional category of palliative care as a new label, analytics, AI, XAI, and interactive techniques. We find significant potential of analytics and AI in Covid-19 triage regarding accuracy, sensitivity, and other performance metrics whilst our interactive human-AI algorithm shows superior performance with approximately 73 percent accuracy and up to 76 percent sensitivity. The results are independent of the data preparation process regarding the imputation of missing values or grouping of comorbidities. In addition, we find that the consideration of an additional label palliative care does not improve the results.

[Validation of secondary triage algorithms for mass casualty incidents-A simulation-based study-German version]

BACKGROUND

In the event of a mass casualty incident (MCI), the situation-related shortage of medical resources does not end when the patients are transported from the scene of the incident. Consequently, an initial triage is required in the receiving hospitals. In the first step, the aim of this study was to create a reference patient vignette set with defined triage categories. This allowed a computer-aided evaluation of the diagnostic quality of triage algorithms for MCI situations in the second step.

METHODS

A total of 250 case vignettes validated in practice were entered into a multistage evaluation process by initially 6 and later 36 triage experts. This algorithm-independent expert evaluation of all vignettes-served as the gold standard for analyzing the diagnostic quality of the following triage algorithms: Manchester triage system (MTS module MCI), emergency severity index (ESI), Berlin triage algorithm (BER), the prehospital algorithms PRIOR and mSTaRT, and two project algorithms from a cooperation between the Federal Office of Civil Protection and Disaster Assistance (BBK) and the Hashemite Kingdom of Jordan-intrahospital Jordanian-German project algorithm (JorD) and prehospital triage algorithm (PETRA). Each patient vignette underwent computerized triage through all specified algorithms to obtain comparative test quality outcomes.

RESULTS

Of the original 250 vignettes, a triage reference database of 210 patient vignettes was validated independently of the algorithms. These formed the gold standard for comparison of the triage algorithms analyzed. Sensitivities for intrahospital detection of patients in triage category T1 ranged from 1.0 (BER, JorD, PRIOR) to 0.57 (MCI module MTS). Specificities ranged from 0.99 (MTS and PETRA) to 0.67 (PRIOR). Considering Youden's index, BER (0.89) and JorD (0.88) had the best overall performance for detecting patients in triage category T1. Overtriage was most likely with PRIOR, and undertriage with the MCI module of MTS. Up to a decision for category T1, the algorithms require the following numbers of steps given as the median and interquartile range (IQR): ESI 1 (1-2), JorD 1 (1-4), PRIOR 3 (2-4), BER 3 (2-6), mSTaRT 3 (3-5), MTS 4 (4-5) and PETRA 6 (6-8). For the T2 and T3 categories the number of steps until a decision and the test quality of the algorithms are positively interrelated.

CONCLUSION

In the present study, transferability of preclinical algorithm-based primary triage results to clinical algorithm-based secondary triage results was demonstrated. The highest diagnostic quality for secondary triage was provided by the Berlin triage algorithm, followed by the Jordanian-German project algorithm for hospitals, which, however, also require the most algorithm steps until a decision.

A Scoping Review of the Essential Components of Emergency Medical Response Systems for Mass Casualty Incidents

OBJECTIVE

Emergency medical (EM) response systems require extensive coordination, particularly during mass casualty incidents (MCIs). The recognition of preparedness gaps and contextual priorities to MCI response capacity in low- and middle-income countries (LMICs) can be better understood through the components of EM reponse systems. This study aims to delineate essential components and provide a framework for effective emergency medical response to MCIs.

METHODS

A scoping review was conducted using 4 databases. Title and abstract screening was followed by full-text review. Thematic analysis was conducted to identify themes pertaining to the essential components and integration of EM response systems.

RESULTS

Of 20,456 screened citations, 181 articles were included in the analysis. Seven major and 40 sub-themes emerged from the content analysis as the essential components and supportive elements of MCI medical response. The essential components of MCI response were integrated into a framework demonstrating interrelated connections between essential and supportive elements.

CONCLUSIONS

Definitions of essential components of EM response to MCIs vary considerably. Most literature pertaining to MCI response originates from high income countries with far fewer reports from LMICs. Integration of essential components is needed in different geopolitical and economic contexts to ensure an effective MCI emergency medical response.

Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

BACKGROUND

Rapid on-site triage is critical after mass-casualty incidents (MCIs) and other mass injury events. Unmanned aerial vehicles (UAVs) have been used in MCIs to search and rescue wounded individuals, but they mainly depend on the UAV operator's experience. We used UAVs and artificial intelligence (AI) to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.

METHODS

This was a preliminary experimental study. We developed an intelligent triage system based on two AI algorithms, namely OpenPose and YOLO. Volunteers were recruited to simulate the MCI scene and triage, combined with UAV and Fifth Generation (5G) Mobile Communication Technology real-time transmission technique, to achieve triage in the simulated MCI scene.

RESULTS

Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs. Eight volunteers participated in the MCI simulation scenario. The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.

CONCLUSION

The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.

Consciousness Detection on Injured Simulated Patients Using Manual and Automatic Classification via Visible and Infrared Imaging

In a disaster scene, triage is a key principle for effectively rescuing injured people according to severity level. One main parameter of the used triage algorithm is the patient's consciousness. Unmanned aerial vehicles (UAV) have been investigated toward (semi-)automatic triage. In addition to vital parameters, such as heart and respiratory rate, UAVs should detect victims' mobility and consciousness from the video data. This paper presents an algorithm combining deep learning with image processing techniques to detect human bodies for further (un)consciousness classification. The algorithm was tested in a 20-subject group in an outside environment with static (RGB and thermal) cameras where participants performed different limb movements in different body positions and angles between the cameras and the bodies' longitudinal axis. The results verified that the algorithm performed better in RGB. For the most probable case of 0 degrees, RGB data obtained the following results: Mathews correlation coefficient (MMC) of 0.943, F1-score of 0.951, and precision-recall area under curve AUC (PRC) score of 0.968. For the thermal data, the MMC was 0.913, F1-score averaged 0.923, and AUC (PRC) was 0.960. Overall, the algorithm may be promising along with others for a complete contactless triage assessment in disaster events during day and night.

Einfluss der Reihenfolge von Items auf die diagnostische Qualität von Vorsichtungsalgorithmen hinsichtlich der Vergabe der Sichtungskategorie I

Hintergrund

Großschadenslagen stellen den Rettungsdienst vor die Herausforderung, vielen Patienten mit begrenzten Ressourcen das Überleben zu sichern. Um hier eine Fehlverteilung von Ressourcen zu verhindern, ist eine genaue Vorsichtung essenziell. Aktuelle Studien zeigen, dass bei den verwendeten Vorsichtungsalgorithmen weiterhin Verbesserungsbedarf besteht.

Ziel der Arbeit

In dieser Arbeit untersuchten wir, welchen Einfluss eine veränderte Reihenfolge der Abfragen/Items auf die Qualität der Vorsichtungsalgorithmen hat.

Material und Methoden

Wir verwendeten eine Datenbank von 492 Luftrettungseinsätzen. Allen Patienten wurde durch eine Gruppe von Notärzten eine Referenzsichtungskategorie (SK) vergeben. Die Vorsichtungsalgorithmen mSTaRT, ASAV und PRIOR wurden in Excel-Befehle übersetzt und die SK für jeden Patienten berechnet. Anschließend rotierte die Reihenfolge der Items. Die berechneten SK wurden hinsichtlich Sensitivität, Spezifität, Unter‑/Übertriage und Youden-Index für die SK I (rot) ausgewertet.

Ergebnisse

mSTaRT zeigte keinerlei Veränderung der Qualität. Die Originalvariante von ASAV erreichte die beste Performance. Eine Rotation der Items führte zu einer Zunahme der Übertriage um 15 % bei sinkender Qualität. PRIOR profitierte am meisten von den Rotationen, wobei insbesondere die Variante mit einer initialen Abfrage der Gehfähigkeit zu einer Abnahme der Übertriage von 22 % führte. Dies führte zur stärksten Verbesserung des Youden-Index (+0,12).

Diskussion

Wir konnten demonstrieren, dass eine Rotation der Items innerhalb der Vorsichtungsalgorithmen ASAV und PRIOR einen Einfluss auf Über- und Untertriage hat. Insbesondere die Position der Abfrage der Gehfähigkeit hat einen bedeutenden Einfluss auf die Spezifität der Algorithmen.

A translational triage research development tool: standardizing prehospital triage decision-making systems in mass casualty incidents

Background

There is no global consensus on the use of prehospital triage system in mass casualty incidents. The purpose of this study was to evaluate the most commonly used pre-existing prehospital triage systems for the possibility of creating one universal translational triage tool.

Methods

The Rapid Evidence Review consisted of (1) a systematic literature review (2) merging and content analysis of the studies focusing on similarities and differences between systems and (3) development of a universal system.

Results

There were 17 triage systems described in 31 eligible articles out of 797 identified initially. Seven of the systems met the predesignated criteria and were selected for further analysis. The criteria from the final seven systems were compiled, translated and counted for in means of 1/7’s. As a product, a universal system was created of the majority criteria.

Conclusions

This study does not create a new triage system itself but rather identifies the possibility to convert various prehospital triage systems into one by using a triage translational tool. Future research should examine the tool and its different decision-making steps either by using simulations or by experts’ evaluation to ensure its feasibility in terms of speed, continuity, simplicity, sensitivity and specificity, before final evaluation at prehospital level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13049-021-00932-z.

Consideraciones éticas y médico-legales sobre la limitación de recursos y decisiones clínicas en la pandemia de la COVID-19

La pandemia por la COVID-19 ha suscitado problemas éticos y médico-legales, entre los que destaca la asignación equitativa de recursos sanitarios, sobre todo en relación a la priorización de pacientes y el racionamiento de recursos. El establecimiento de prioridades está siempre presente en los sistemas sanitarios y depende de la teoría de justicia aplicable en cada sociedad. El racionamiento de recursos ha sido necesario en la pandemia por la COVID-19, por lo que se han publicado documentos de consenso para la toma de decisiones sustentadas en cuatro valores éticos fundamentales: maximización de los beneficios, tratar a las personas igualmente, contribuir en la creación de valor social y dar prioridad a la situación más grave. De ellos derivan recomendaciones específicas: maximizar beneficios; priorizar a los trabajadores de la salud; no priorizar la asistencia por orden de llegada; ser sensible a la evidencia científica; reconocer la participación en la investigación y aplicar los mismos principios a los pacientes COVID-19 que a los no COVID-19.

Medico-legal and ethical considerations on resource limitation and clinical decisions during the COVID-19 pandemic

The COVID-19 pandemic has raised ethical and medico-legal problems, which include the equitable allocation of health resources, especially in relation to the prioritization of patients and the rationing of resources. Priority setting is always present in healthcare systems and depends on the theory of justice applicable in each society. Resource rationing has been necessary in the COVID-19 pandemic, and therefore consensus documents have been published for decision-making based on four fundamental ethical values: maximization of benefits, treating people equally, contributing to creating social value and giving priority to the worst off, from which specific recommendations derive: maximize benefits; prioritize health workers; do not prioritize attendance on a first-COme, first-served basis; be sensitive to scientific evidence; recognize participation in research and apply the same principles to COVID-19 patients as to non-COVID-19 patients.

[The Berlin mass casualty hospital triage algorithm : Development, implementation and influence on exercise-based triage results]

BACKGROUND AND OBJECTIVE

Patient triage has a key function within the scope of the successful management of mass disasters and ensures the correct resource allocation. Analysis of unheralded hospital disaster training in Berlin hospitals revealed triage problems referring the correct classification of patients in the triage categories and relevant overtriaging and undertriaging. Therefore, a triage algorithm tailored to the clinical setting was developed in Berlin and after presentation and discussion within the circle of the representatives for clinical catastrophe protection, the algorithm was introduced as obligatory in 2015. This study was carried out to validate and investigate the effects of the triage algorithm.

MATERIAL AND METHODS

This prospective observational study evaluated all unheralded hospital disaster training exercises from 2016/2017 initiated by the senate administration, with 556 roughed persons after implementation of the new triage algorithm and compared the results with disaster training exercises from the years 2010/2011 without a triage algorithm (n = 601). The correct allocation of the prescribed injury patterns to the triage category (T1-3), specificity, sensitivity and positive likelihood ratio of the algorithm are described and group differences were calculated.

RESULTS

In 15 unheralded mass disaster drills with 556 actors in 2016-2017 a total of 85% of the category T1 (n = 83/98), 63% of the T2 category (n = 100/159) and 87% of the T3 category (n = 259/299) were correctly recognized. This corresponds to a significantly better triage result of 80% compared to 63% in 2010/2011. Overtriaging and undertriaging also were significantly reduced. The triage algorithm showed a specificity and sensitivity of 97% and 75%, respectively, for T1 (immediately life-threatening), 86%/67% for T2 (severely injured) and 85%/88% for T3 (slightly injured) patients.

DISCUSSION

The Berlin hospital triage algorithm was successfully validated. The triage category allocation was significantly improved in all relevant aspects after implementation with a significant reduction of overtriaging and undertriaging.

Technical Support by Smart Glasses During a Mass Casualty Incident: A Randomized Controlled Simulation Trial on Technically Assisted Triage and Telemedical App Use in Disaster Medicine

Background

To treat many patients despite lacking personnel resources, triage is important in disaster medicine. Various triage algorithms help but often are used incorrectly or not at all. One potential problem-solving approach is to support triage with Smart Glasses.

Objective

In this study, augmented reality was used to display a triage algorithm and telemedicine assistance was enabled to compare the duration and quality of triage with a conventional one.

Methods

A specific Android app was designed for use with Smart Glasses, which added information in terms of augmented reality with two different methods—through the display of a triage algorithm in data glasses and a telemedical connection to a senior emergency physician realized by the integrated camera. A scenario was created (ie, randomized simulation study) in which 31 paramedics carried out a triage of 12 patients in 3 groups as follows: without technical support (control group), with a triage algorithm display, and with telemedical contact.

Results

A total of 362 assessments were performed. The accuracy in the control group was only 58%, but the assessments were quicker (on average 16.6 seconds). In contrast, an accuracy of 92% (P=.04) was achieved when using technical support by displaying the triage algorithm. This triaging took an average of 37.0 seconds. The triage group wearing data glasses and being telemedically connected achieved 90% accuracy (P=.01) in 35.0 seconds.

Conclusions

Triage with data glasses required markedly more time. While only a tally was recorded in the control group, Smart Glasses led to digital capture of the triage results, which have many tactical advantages. We expect a high potential in the application of Smart Glasses in disaster scenarios when using telemedicine and augmented reality features to improve the quality of triage.

Impact of systolic blood pressure limits on the diagnostic value of triage algorithms

Background

Major incidents are characterized by a lack of resources compared to an overwhelming number of casualties, requiring a prioritization of medical treatment. Triage algorithms are an essential tool for prioritizing the urgency of treatment for patients, but the evidence to support one over another is very limited. We determined the influence of blood pressure limits on the diagnostic value of triage algorithms, considering if pulse should be palpated centrally or peripherally.

Methods

We used a database representing 500 consecutive HEMS patients. Each patient was allocated a triage category (T1/red, T2/yellow, T3/green) by a group of experienced doctors in disaster medicine, independent of any algorithm. mSTaRT, ASAV, Field Triage Score (FTS), Care Flight (CF), “Model Bavaria” and two Norwegian algorithms (Nor and TAS), all containing the question “Pulse palpable?”, were translated into Excel commands, calculating the triage category for each patient automatically. We used 5 blood pressure limits ranging from 130 to 60 mmHg to determine palpable pulse. The resulting triage categories were analyzed with respect to sensitivity, specificity and Youden Index (J) separately for trauma and non-trauma patients, and for all patients combined.

Results

For the entire population of patients within all triage algorithms the Youden Index (J) was highest for T1 (J between 0,14 and 0,62). Combining trauma and non-trauma patients, the highest J was obtained by ASAV (J = 0,62 at 60 mmHg). ASAV scored the highest within trauma patients (J = 0,87 at 60 mmHg), whereas Model Bavaria (J = 0,54 at 80 mmHg) reached highest amongst non-trauma patients. FTS performed worst for all patients (J = 0,14 at 60 mmHg), showing a lower score for trauma patients (J = 0,0 at 60 mmHg). Change of blood pressure limits resulted in different diagnostic values of all algorithms.

Discussion

We demonstrate that differing blood pressure limits have a remarkable impact on diagnostic values of triage algorithms. Further research is needed to determine the lowest blood pressure value that is possible to palpate at a peripheral artery compared to a central artery.

Conclusion

As a consequence, it might be important in which location pulses are palpated according to the algorithm at hand during triage of patients.