ABSTRACT
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.
Subject(s)
Mass Casualty Incidents , Triage , Humans , Triage/methods , Berlin , Algorithms , Computer SimulationABSTRACT
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.
Subject(s)
Mass Casualty Incidents , Triage , Humans , Triage/methods , Berlin , Algorithms , Computer SimulationABSTRACT
As of late 2019, the COVID-19 pandemic has been a challenge to health care systems worldwide. Rapidly rising local COVID-19 incidence rates, result in demand for high hospital and intensive care bed capacities on short notice. A detailed up-to-date regional surveillance of the dynamics of the pandemic, precise prediction of required inpatient capacities of care as well as a centralized coordination of the distribution of regional patient fluxes is needed to ensure optimal patient care. In March 2020, the German federal state of Saxony established three COVID-19 coordination centers located at each of its maximum care hospitals, namely the University Hospitals Dresden and Leipzig and the hospital Chemnitz. Each center has coordinated inpatient care facilities for the three regions East, Northwest and Southwest Saxony with 36, 18 and 29 hospital sites, respectively. Fed by daily data flows from local public health authorities capturing the dynamics of the pandemic as well as daily reports on regional inpatient care capacities, we established the information and prognosis tool DISPENSE. It provides a regional overview of the current pandemic situation combined with daily prognoses for up to seven days as well as outlooks for up to 14 days of bed requirements. The prognosis precision varies from 21% and 38% to 12% and 15% relative errors in normal ward and ICU bed demand, respectively, depending on the considered time period. The deployment of DISPENSE has had a major positive impact to stay alert for the second wave of the COVID-19 pandemic and to allocate resources as needed. The application of a mathematical model to forecast required bed capacities enabled concerted actions for patient allocation and strategic planning. The ad-hoc implementation of these tools substantiates the need of a detailed data basis that enables appropriate responses, both on regional scales in terms of clinic resource planning and on larger scales concerning political reactions to pandemic situations.
