Dataset Information

Could we employ the queueing theory to improve efficiency during future mass causality incidents?

ABSTRACT:

Background

Preparation for a disaster or accident-related mass casualty events is often based on experience. The objective measures or tools for evaluating decision-making and effectiveness during such events are underdeveloped. Queueing theory has been suggested to evaluate the effectiveness of mass causality incidents (MCI) plans.

Objective

Using different types of real MCI, we aimed to determine if a queueing network model could be used as a tool to assist in preparing plans to address mass causality incidents.

Methods

We collected information from two types of mass casualty events: a motor vehicle accident and a dust explosion. Patient characteristics, time intervals of every working station, numbers of physicians and nurses attending, and time required by physicians and nurses during these two MCIs were collected and used for calculation in a queueing network model. Balanced efficiency was determined by calculating the numbers of server, i.e., nurses and physicians, in the two MCIs.

Results

Efficient patient flows were found in both MCIs. However, excessive medical manpower supply was revealed when the queueing network model was applied to assess the MCIs. The best fitting result, i.e., the most efficient man power utilization, can be calculated by the queueing network models. Furthermore, balanced efficiency may be a more suitable condition than the highest efficiency man power utilization when faced with MCIs.

Conclusion

The queueing network model is a flexible tool that could be used in different types of MCIs to observe the degree of efficiency when handling MCIs.

SUBMITTER: Lin CC

PROVIDER: S-EPMC6458797 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Could we employ the queueing theory to improve efficiency during future mass causality incidents?

Lin Chih-Chuan CC Wu Chin-Chieh CC Chen Chi-Dan CD Chen Kuan-Fu KF

Scandinavian journal of trauma, resuscitation and emergency medicine 20190411 1

<h4>Background</h4>Preparation for a disaster or accident-related mass casualty events is often based on experience. The objective measures or tools for evaluating decision-making and effectiveness during such events are underdeveloped. Queueing theory has been suggested to evaluate the effectiveness of mass causality incidents (MCI) plans.<h4>Objective</h4>Using different types of real MCI, we aimed to determine if a queueing network model could be used as a tool to assist in preparing plans to ...[more]

PMID: 30971299

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Project description:BackgroundCritical incident reporting and analysis is one of the key components of patient safety in anesthesiology. The aim of this study was to determine the frequency and characteristics of critical incidents during anesthesia, main causes and factors involved, influence on patient outcomes, prevalence of incident reporting and further analysis.MethodsA multicenter prospective audit was conducted at the clinical departments of the Bogomolets National Medical University during the period from 1 to 2021 to 1 December 2021. 13 hospitals from different Ukrainian regions took part in the study. Anesthesiologists voluntarily submitted critical incident reports into a Google form as they occurred during the working shifts, reporting the details of the incident, and the incident registration routine in their hospital. The study design was approved by the Bogomolets National Medical University (NMU) ethics committee, protocol #148, 07.09.2021.ResultsThe incidence of critical incidents was 9.35 cases per 1000 anesthetic procedures. Most common incidents were related to the respiratory system: difficult airway (26.8%), reintubation (6.4%), oxygen desaturation (13.8%); cardiovascular system: hypotension (14.9%), tachycardia (6.4%), bradycardia (11.7%), hypertension (5.3%), collapse (3.2%); massive hemorrhage (17%). Factors associated with critical incidents were elective surgery (OR 4.8 [3.1-7.5]), age from 45 to 75 years (OR 1.67 [1.1-2.5]), ASA II (OR 38 [13-106]}, III (OR 34 [12-98]) or IV (3.7 [1.2-11]) compared to ASA I; regional anesthesia (OR 0.67 95 CI 0.5-0.9) or general anesthesia (GA) and regional anesthesia combination (OR 0.55 95 CI 0.3-0.9] decreased the risk of incidents compared to GA alone. Procedural sedation was associated with increased risk of a critical incident, compared to GA (OR 0.55 95 CI 0.3-0.9). The incidents occurred most commonly during the maintenance phase (75/113, 40%, OR compared to extubation phase 20 95 CI 8-48) or the induction phases of anesthesia (70/118, 37%, OR compared to extubation phase 18 95 CI 7-43). Among common reasons that could lead to the incident, the physicians have identified: individual patient features (47%), surgical tactics (18%), anesthesia technique (16%) and human factor (12%). The most frequent failings contributing to the incident occurrence were: insufficient preoperative assessment (44%), incorrect interpretation of the patients' state (33%), faulty manipulation technique (14%), miscommunication with a surgical team (13%) and delay in emergency care (10%). Furthermore, 48% of cases, as judged by participating physicians, were preventable and the consequences of another 18% could be minimized. The consequences of the incidents were insignificant in over a half of the cases, but in 24.5% have led to prolonged hospital stay, in 16% patients required an urgent transfer to the ICU and 3% of patients died during their hospital stay. The majority of the critical incidents (84%) were reported through the hospital reporting system, using mostly paper forms (65%), oral reports (15%) and an electronic database (4%).ConclusionCritical incidents during anesthesia occur rather often, mainly during the induction or maintenance phases of anesthesia, and could lead to prolonged hospital stay, unplanned transfer to the ICU or death. Reporting and further analysis of the incident are crucial, so we should continue to develop the web-based reporting systems on both local and national levels.Study registrationNCT05435287, clinicaltrials.gov, 23/6/2022.

Project description:Introduction and objectiveScientific reporting on major incidents, mass-casualty incidents (MCIs), and disasters is challenging and made difficult by the nature of the medical response. Many obstacles might explain why there are few and primarily non-heterogenous published articles available. This study examines the process of scientific reporting through first-hand experiences from authors of published reports. It aims to identify learning points and challenges that are important to address to mitigate and improve scientific reporting after major incidents.MethodsThis was a qualitative study design using semi-structured interviews. Participants were selected based on a comprehensive literature search. Ten researchers, who had published reports on major incidents, MCIs, or disasters from 2013-2018 were included, of both genders, from eight countries on three continents. The researchers reported on large fires, terrorist attacks, shootings, complex road accidents, transportation accidents, and earthquakes.ResultsThe interview was themed around initiation, workload, data collection, guidelines/templates, and motivation factors for reporting. The most challenging aspects of the reporting process proved to be a lack of dedicated time, difficulties concerning data collection, and structuring the report. Most researchers had no prior experience in reporting on major incidents. Guidelines and templates were often chosen based on how easily accessible and user-friendly they were.Conclusion and relevanceThere are few articles presenting first-hand experience from the process of scientific reporting on major incidents, MCIs, and disasters. This study presents motivation factors, challenges during reporting, and factors that affected the researchers' choice of reporting tools such as guidelines and templates. This study shows that the structural tools available for gathering data and writing scientific reports need to be more widely promoted to improve systematic reporting in Emergency and Disaster Medicine. Through gathering, comparing, and analyzing data, knowledge can be acquired to strengthen and improve responses to future major incidents. This study indicates that transparency and willingness to share information are requisite for forming a successful scientific report.

Dataset Information

Could we employ the queueing theory to improve efficiency during future mass causality incidents?

Background

Objective

Methods

Results

Conclusion

Publications

Could we employ the queueing theory to improve efficiency during future mass causality incidents?

Similar Datasets

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