Abstract
Purpose
The objective of this study was to offer a comprehensive synthesis of the existing Key performance indicators (KPIs) used in the evaluation of the pre-Hospital response to disasters and mass casualty incidents (MCIs).
Methods
At the end of December 2022 a scoping review has been performed on PubMed, Scopus, Embase, and Medline to identify articles describing the use of KPIs to assess the performance of first responders during the prehospital phase of an MCI (real or simulated). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, fourteen articles were included in the analysis.
Results
Eleven articles applied indicators in exercises and/or simulations. Two articles proposed new KPIs, and one used KPIs for developing a model for benchmarking pre-Hospital response. All articles analyzed quantitative indicators of time, whereas two studied indicators of structure, of process, and of outcome as well.
Conclusion
The findings from this review emphasize the need for employing common terminology and using uniformed data collection tools, if obtaining standardized evaluation method is the goal to be achieved.
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Introduction
Disasters are commonly defined as any event causing a “serious disruption of the functioning of a community or a society involving widespread human, material, economic or environmental losses and impacts, which exceeds the ability of the affected community or society to cope using its own resources”. Due to climate change, escalating migration and refugee crises, outbreaks of epidemics and pandemics, and civilian casualties in contemporary conflicts around the world, disasters are occurring more frequently putting more people at peril [1, 2]. Along with their frequency, the nature of disasters is changing as well. They are becoming more complex, unpredictable, and prolonged [3], thus calling for advancement in disaster management to bolster preparedness and fortify resilience against future calamities [4], as strongly advocated by the Sendai Framework for Disaster Risk Reduction 2015–2030 [2]. Disasters, induce among other consequences what in the literature is defined as mass casualty incidents (MCIs) [5]. The timely, effective, and efficient response of emergency medical services (EMS) personnel is crucial in mitigating the immediate human impact of MCIs [6], as well as in minimizing the risk of both short-term and long-term complications, and facilitating a prompt and effective management of the event, from the incident site (i.e. prehospital) to healthcare facilities [7, 8]. Nonetheless, such response has seldom been evaluated [9]. Identifying areas of improvement can enhance overall disaster health management and can strengthen the level of preparedness of a health system [10, 11], by allowing decision-makers to make well-informed decisions [12]. It can also help increase the quality of services during the response to a disaster in real life, by inducing an implementation of higher quality of education and training provided to the first responders [13].
Employing key performance indicators (KPIs) that concentrate on the evaluation of the response to an MCI, including the performance of first responders in the prehospital phase both in simulated and real events, has been useful for addressing such lack of evaluation [14].
According to the Oxford’s dictionary, a KPI is defined as a measurement of an individual’s, a team’s, or a department’s achievement, and its development is a part of a performance management system [15]. These indicators may be quantitative or qualitative depending on what they are evaluating, and the unit of measure used to express such evaluation [16]. Quantitative KPIs can be divided in two categories: of time and of structure. The temporal performance indicators use seconds, minutes or even hours as a unit, whereas the indicators of structure use multiples of whole positive numbers to describe how many units of items (an ambulance, a doctor, or a tabard) may be needed [17]. On the other hand, under the purview of the qualitative KPIs, all those indicators that assess a process unfolding in a certain specific sequence of events, or an outcome can be found [17].
Even though leading experts in the field of Disaster Medicine are continuously addressing the issue of establishing standards that may be used as templates for evaluation and research, there is currently no agreement on criteria for indicators that can be used as a tool for quality control and to assess performance in major incidents. Indeed, when a response is not evaluated using predetermined, high-quality data, it cannot be utilized for analysis, comparison, experience sharing, inter-agency cooperation, and the advancement of scientific methodology [18, 19]. The aim of this scoping review is therefore to offer a comprehensive synthesis of the existing KPIs used in the evaluation of the prehospital response to disasters and MCIs (real or simulated).
Methods
Search strategy and selection criteria
A systematic literature search was performed on PubMed, Scopus, Embase, and Medline to identify articles exploring KPIs used to assess the performance of first responders during the prehospital phase of an MCI (real or simulated). The search strategy concentrated on papers published in English until December 25, 2022, using the following search terms (including synonyms): “key performance indicator”, “process assessment”, “health care quality”, “performance evaluation” AND “mass casualty incidents”, “disaster”, “health crisis” AND “prehospital care”, “acute emergency care”.
No restrictions to the time period or any filters were applied.
Peer-reviewed studies, textbooks, consensus guidelines, protocols, framework, and models were included. Exclusion criteria were non-English papers, articles that did not focus specifically on KPIs used to assess the prehospital phase during an MCI, abstract and conference papers, or unverified or unsubstantiated press and news media reports.
References and cited articles were screened for additional relevant publications, consequently included in the selection process. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed.
Data collection and analysis
NMP and HL independently screened titles and abstracts of articles yielded by the search using the Rayyan Intelligent Systematic Review tool [20]. The same two investigators separately reviewed the full text of included articles and removed any paper that did not meet the inclusion criteria. After each phase of the screening process (based on titles/abstracts, and full text screening) a cross match of the decisions of the two investigators was made. When a conflict on whether to include or exclude one of the articles arose, it was resolved through a discussion and a final consensus was reached representing both parties. The investigators did not perform any kind of pooled analysis of the included papers due to the broad inclusion strategy, the anticipated significant heterogeneity and the paucity of literature on the subject. PRISMA and statement checklists guided the data extraction and evaluation process, following a combination of inductive and deductive approaches filtering thus the reports based on quality or bias risk. Key information such as the type of MCI, KPIs identified and related benchmarks, the elements of the prehospital phase assessed by the studied KPIs, and the approach to the studied KPIs (creation of new KPIs, test, and/or validation) were recorded through a pre-established extraction sheet. Results were discussed between authors (NMP, HL, and MC) before data analysis.
Results
Of 3960 articles identified in the database search, 243 met the eligibility criteria for full text screening. After full text screening, 188 articles were excluded, while 44 articles were not available (inaccessible due to access rights, full text not available etc.), leaving 11 articles meeting the full relevant criteria. After screening citation and references, 3 additional articles were identified and included (Fig. 1).
In Table 1, the details of each paper are presented. The included articles refer to a 22-year time span (from 1997 to 2019). Of note, 6 papers focusing on almost overlapping KPIs were published by a Swedish research group, although their research encompassed different settings (Sweden [14, 19, 21,22,23], Afghanistan [24]). Eight included articles [16, 17, 19, 22, 24,25,26,27] concentrated on the overall prehospital management of MCIs, including different aspects from the initial scene assessment to the evacuation of casualties. Among these, indicators examining triage, prehospital treatment, evacuation (MEDEVAC) can be found (Table 1). The remaining 5 articles concentrated on distinct facets of prehospital management, such as transportation, communication, triage and command and control, the latter referring to the management and coordination of emergency response activities by an established authority or hierarchy of authorities.
Out of the 14 articles, 2 are proposing new KPIs [16, 17], 1 is using KPIs for developing a model for benchmarking prehospital response, whereas the other 11 articles [14, 19, 21,22,23,24,25, 27,28,29,30] applied the studied indicators through exercises and/or simulations. In these 11 articles, the responders are professionals who have had training before their involvement in the different incidents or simulations. Most commonly the responders’ teams were composed by medical doctors, registered nurses and/or trained paramedics-namely EMS personnel. In one case the participants were military personnel with similar training and in another the participants were students majoring in Health Programs, with most of them being medics at a city EMS with 2 or 3 years of military experience [30].
In Table 2, information regarding the number, the type (quantitative/qualitative) and the benchmarks (when provided) for the KPIs in each article included, is summarised. Quantitative KPIs included time indicators and indicators of structure, for which the definition “a quantitative measure reflecting availability of resources, for example number of ambulances, involved in medical response at a major incident” provided by Rådestad was adopted [17]. Qualitative KPIs included indicators of process and indicators of outcome. For the former, Rådestad’s definition of “indicator describing activities or processes involved in medical response management at a major incident and is usually associated with patient outcome” was once again adopted [17], while the latter were defined either as “indicators describing the outcome of health care, in disaster medical care the reduction of morbidity and mortality of the survivors is the most important outcome” [17] or as “measures of the actual achievements intended” [16].
All articles included analysed quantitative indicators of time, whereas 2 papers expanded their study in all 4 different categories of KPIs abovementioned [16, 17]. Even though the identification of the benchmarks was not the aim of our study, it is important to note that more than half of the papers analysed, included a full list of benchmarks proposed [14, 19, 21,22,23,24, 28, 29]. The authors of one article did not provide any benchmark regarding the indicators that they examined [17] (Table 2).
Out of the 268 KPIs identified, 79 are unique to the papers studying them, 22 have been mentioned twice (Annex). The rest 145 have been mentioned in three or more papers and were clustered by the authors of this review according to the area of prehospital response they address. The most frequently examined areas are the Guidelines and Management, whereas the Second and First report come up as the secondly and thirdly most frequently assessed ones (Table 3).
Discussion
This systematic review offers a comprehensive synthesis of the existing KPIs used in the evaluation of the prehospital response to disasters and MCIs. The crucial need for standardized terminology, uniform data collection tools, and established benchmarks for assessing prehospital responder performance was highlighted.
Before delving into the content of the KPIs, the geographical distribution of included work is worth mentioning. While a global distribution of studies was anticipated, the majority of included articles were produced by Swedish research teams. To the authors’ understanding, this may have been facilitated by the necessity to implement the Swedish national preparedness plan and by the presence of KAMEDO (Katastrofmedicinska Organisationskommitten), a Swedish Organisation for Studies and Reports from International Disasters organized and funded by the Swedish National Board of Health and Welfare [21]. However, this raises the question of the applicability of these KPIs in other countries with different physical geography, environments, resources, and legal and regulatory frameworks. Echoing the relevance of such question is the study performed in Afghanistan [24]. The study’s aim was to test if the performance indicators for prehospital command and control developed for civilian use can be used in a military training setting. The finding that two KPIs were deemed non-relevant is significant, as it suggests that caution should be exercised when applying the same indicators universally and without reservation, given that not all prehospital emergency care is provided in optimal conditions [31].
Another aspect of interest is that the authors of some of the included papers were able to elaborate a series of KPIs only upon examination of after-action reports of MCIs that occurred in a time span of 22 years [21]. A possible explanation of why such a long period of time had to be reviewed to produce the aforementioned KPIs could be that MCI after-action reports are typically performed for purposes other than performance evaluation. Indeed, they often simply summarize different aspects of the response, while actions and decisions taken at the operational and tactical levels are rarely registered in a thorough and complete manner, thus preventing the comprehensive identification of indicators of performance [9, 21].
When attempting to determine the most studied element of the response phase, management, formation of guidelines (for either response in general or specifically to the evacuation of patients) and communication (whether it be the first or second report) were the most frequently examined. This finding may be explained by the fact that these areas are often identified as having shortcomings. Any intervention that could improve the standardization of prehospital response to MCIs and enhance communication efficiency could have a significant impact on the success of disaster management [32].
It becomes clear from the studies covered in this review that notwithstanding the introduction of multiple frameworks to enable uniform disaster research and evaluation [33], lack in use of consistent (or any) terminology across the various phases of a disaster persists. The epitome of this issue is the use of performance indicators of time: while all authors are either applying or proposing new KPIs, only two have been proposing definitions. Such a discovery contributes to the general confusion and sets back even more the search of commonly set, accepted, and used guidelines in the response evaluation.
Although the World Association for Disaster and Emergency Medicine (WADEM) has published a policy document on evaluation and research where the question of adopting a more evidence-based to disaster medicine research is raised [34], in all 14 articles included in this review the need for further validation of the indicators studies and used, is always highlighted. That leads, though, to the point that no validated set of KPIs on which to base further research, currently exists. This observation further underscores the need to improve the science behind the development, validation, and use of indicators.
When examining the use of quantitative and qualitative KPIs, it is clear that there is a discrepancy in the number of articles focusing on the former as opposed to the latter. Specifically, despite all 14 articles studied temporal performance indicators, 10 were looking into indicators of process [14, 16, 17, 19, 21,22,23,24, 27, 30], either that is accuracy or respect of the sequence of steps of which such process is comprised. An example that could function as the embodiment of such anomaly is the first report to the dispatch centre (METHANE). The focus appears to be primarily on the timely arrival of communication, rather than the accuracy of the report's content. However, this does not necessarily indicate that communicating something earlier is more important than communicating it correctly. The authors believe that a more plausible explanation for this discrepancy is the difficulty of evaluating communication quality. While the timing of communication can be assessed using time stamps and stopwatches, properly evaluating the quality of communication requires a validated training curriculum and a validated set of KPIs. Unfortunately, the latter still seems to be out of reach [22, 29].
To conclude, upon studying the articles included in this research, the reader may find it difficult to trace the origin and rationale behind many of the proposed benchmarks. Additionally, some authors only provided benchmarking for a portion of the examined performance indicators [16, 25,26,27, 30]. As previously mentioned, setting a value against which individual responders or the overall system performance can be evaluated is always a challenge [21]. However, the concept of benchmarks is inherent to the usefulness of a proposed indicator as long as it is explicit that the indicators are not being used to single out failures and to identify scapegoats, but rather to identify areas where improvements can be made [21].
Limitations
First, this review has only included articles in English. It is possible that other pertinent research in languages other than English was skipped over for this review. Secondly, a quality assessment of the included studies was not performed using a validated tool but by merely using the reviewers’ experience in research, this decision was taken because of the small number of papers that examined KPIs on the prehospital response found.
Recommendations
The findings of this review demonstrate the pressing need to establish standards for evaluating performance to disaster response. In the spirit of satisfying such need, some recommendations based on the results and discussion section of this review, are presented below:
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According to the authors -in complete accordance with Coats statement- set, accept, and employ the same definitions and terminology is the first step towards developing a more systematic research approach in Disaster Medicine and consequently, a better system for patient care [35].
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Data must be available and preferably recorded in a way that evaluation can be performed without delays and must include all decisions made, when they were taken, and by whom.
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An attempt to validate in a scientific way the already existing in the literature KPIs should go hand in hand with the proposal of new ones. The creation of a commonly accepted, validated performance indicators will push long way the evaluation of response to a disaster.
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Measurable KPIs should be built into the training of responders in management, command and control and, overall, in the different levels of response to major incidents and disasters. Making sure that the indicators from various training programmes are compatible is not a consideration to strive for.
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In the context of an ever-changing Disaster Medicine landscape, the introduction of the term Complex Public Health Crises in 2020 mirrors the need to change not only the way we respond to disasters but the way we approach them in total [3]. Even though it may seem premature, it is the authors adamant belief that developing KPIs measuring the public health and the mental health support interventions should be a priority.
Conclusion
This literature review systematically examines the published data on KPIs used to evaluate prehospital response during disasters and MCIs. The findings reveal that the absence of standardized terminology and inconsistent data collection methods have resulted in a limited number of KPIs. To address this issue, there is a need to establish standards for evaluating prehospital responders' performance in these situations. This includes using a common terminology, implementing structured data collection systems for both real and simulated events that cover all prehospital processes, and employing validated KPIs for proper performance evaluation. Objective and measurable data will enable experts and researchers to effectively assess and improve prehospital medical response to disasters and MCIs.
Data availability
No datasets were generated or analysed during the current study.
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Acknowledgements
This manuscript is the result of a study conducted in the framework of the Advanced Master of Science in Disaster Medicine (EMDM—European Master in Disaster Medicine), jointly organised by CRIMEDIM—Center for Research and Training in Disaster Medicine, Humanitarian Aid and Global Health of the Università del Piemonte Orientale (UPO) and REGEDIM—Research Group on Emergency and Disaster Medicine of the Vrije Universiteit Brussel (VUB).
Funding
Open access funding provided by Università degli Studi del Piemonte Orientale Amedeo Avogrado within the CRUI-CARE Agreement. This paper is supported by European Union's Horizon 2020 research and innovation programme under grant agreement N 101021957, project NIGHTINGALE Novel InteGrated toolkit for enhanced pre-Hospital life support and Triage IN challenGing And Large Emergencies.
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Conceptualization, N.M.P and H.L.; methodology, N.M.P, H.L and M.C.; software, N.M.P and H.L.; validation, M.C.; formal analysis, N.M.P and H.L.; investigation, N.M.P and H.L.; resources, N.M.P and H.L.; data curation, N.M.P and H.L.; writing—original draft preparation, N.M.P.; writing—review and editing, H.L., L.R. and M.C..; supervision, L.R. and M.C.; All authors have read and agreed to the published version of the manuscript.
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Markou-Pappas, N., Lamine, H., Ragazzoni, L. et al. Key performance indicators in pre-hospital response to disasters and mass casualty incidents: a scoping review. Eur J Trauma Emerg Surg (2024). https://doi.org/10.1007/s00068-024-02533-8
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DOI: https://doi.org/10.1007/s00068-024-02533-8