Skip to content

Advertisement

  • Original research
  • Open Access

A consensus based template for reporting of pre-hospital major incident medical management

  • 1, 2Email author,
  • 1, 3, 4,
  • 5, 6,
  • 6,
  • 1, 3 and
  • 2, 7, 8
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine201422:5

https://doi.org/10.1186/1757-7241-22-5

©  Fattah et al.; licensee BioMed Central Ltd. 2014

  • Received: 28 October 2013
  • Accepted: 16 December 2013
  • Published:

The Erratum to this article has been published in Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine 2014 22:42

Abstract

Background

Structured reporting of major incidents has been advocated to improve the care provided at future incidents. A systematic review identified ten existing templates for reporting major incident medical management, but these templates are not in widespread use. We aimed to address this challenge by designing an open access template for uniform reporting of data from pre-hospital major incident medical management that will be tested for feasibility.

Methods

An expert group of thirteen European major incident practitioners, planners or academics participated in a four stage modified nominal group technique consensus process to design a novel reporting template. Initially, each expert proposed 30 variables. Secondly, these proposals were combined and each expert prioritized 45 variables from the total of 270. Thirdly, the expert group met in Norway to develop the template. Lastly, revisions to the final template were agreed via e-mail.

Results

The consensus process resulted in a template consisting of 48 variables divided into six categories; pre-incident data, Emergency Medical Service (EMS) background, incident characteristics, EMS response, patient characteristics and key lessons.

Conclusions

The expert group reached consensus on a set of key variables to report the medical management of pre-hospital major incidents and developed a novel reporting template. The template will be freely available for downloading and reporting on http://www.majorincidentreporting.org. This is the first global open access database for pre-hospital major incident reporting. The use of a uniform dataset will allow comparative analysis and has potential to identify areas of improvement for future responses.

Keywords

  • Major incident
  • Disaster
  • Emergency medicine
  • Reporting
  • Medical management

Background

Major incidents such as natural disasters, complex road traffic accidents, terrorism attacks and violence in general, are global problems. Over the decade 2001–2010, an average of more than 700 natural and technological emergencies occurred globally every year, affecting approximately 270 million people and causing over 130 000 deaths annually [1]. In 2011 natural disasters alone cost more than 30 000 lives and caused some 245 million victims worldwide [2]. Road traffic injury (RTI) is a global public health problem causing some 1,2 million deaths yearly and another 20–50 million people sustain non-fatal injuries. RTI rates are twice as high in low-and middle- income countries compared to high-income countries [3]. Further, terrorism caused over 86 000 injured and some 25 000 fatalities in the period from 1968 until 2004 [4]. Conflict-related emergencies are yet another challenge affecting over 1.5 billion people or one quarter of the world’s population who live in countries affected by violent conflict [5].

In the last sixty years disaster medicine has been recognised as a distinct scientific discipline [6]. However the medical reporting of major incidents has been inconsistent leading to several calls for more structured reporting [7–11]. A systematic review to identify templates for reporting major incident medical management revealed that 10 such templates exist globally [12]. The templates were heterogeneous and their implementation has been limited. Further, no feasibility testing has been performed.

Current literature identifies challenges in major incident medical management such as communication [13, 14], coordination [15], triage [16, 17] and distribution of patients [18]. We aim to address the challenges by designing a template that is feasible and freely accessible to allow rapid dissemination of information for practical and comparative analysis. Based on a modified nominal group technique, we conducted a consensus process to identify data variables that should be incorporated into such a template.

Methods

Definition

Major incident was defined as ‘an incident that requires the mobilization of extraordinary EMS resources and is identified as a major incident in that system’.

The experts

European experts who had published previous major incident reporting templates were identified through a systematic literature review [12] and were invited to participate. Six authors were identified and four were able to take part in the consensus process. The organizers were each asked to nominate two experts with experience as a major incident practitioner, planner or academic. Nine nominated experts were able to participate. In total 13 experts from 10 European countries participated.

The modified nominal group technique

The four-stage consensus process was based on the Nominal Group Technique [19] modified according to the experience gained by researchers in the Norwegian Air Ambulance Foundation in undertaking recent consensus processes [20–24]. The process consisted of three written stages where experts worked individually and one collective meeting with verbal negotiations. The process began in December 2012 and final modifications were made in October 2013.

Stage 1

The experts were each asked to suggest 30 data variables that they believed to be of greatest value concerning pre-hospital major incident medical management reporting.

Stage 2

One month later, the experts were asked to choose the 45 most important variables from all suggested variables in stage 1. The reason for choosing 45 variables was to prevent the experts from only choosing their 30 suggested variables from stage 1. During this stage experts were also allowed to combine variables considered to have the same core meaning. The 45 variables suggested by each expert were given a point value: a ranking of first place gave 45 points, second place 44 points and so on until the priority on 45th place received 1 point. In addition each suggested variable received 2 points for every time it was nominated in an expert’s top 45 lists.

A month later a list containing the variables that scored more than 100 points together with their comments was sent to the experts. This step allowed the experts to perform a second examination of relevant scientific material prior to the consensus meeting.

Stage 3

Two weeks later the expert group attended a 2-day meeting in Torpomoen, Norway. The highest ranked variables were discussed and a draft of the final template agreed upon. Variables and definitions were collated with existing Utstein templates for reporting from trauma care and major incidents [22, 25].

Stage 4

The organisers edited this draft into a consistent structure and circulated it to the experts for final revision two weeks after the consensus. The group undertook revisions in August 2013. Experts with experience in testing questionnaires for Statistics Norway reviewed the template and provided suggestions for improvement from a user point-of-view. Most of these suggestions were incorporated into the template before it was distributed to the consensus group for final approval in October 2013.

Results

Stage 1 resulted in 339 suggested data variables that were categorized without modifying the experts’ suggestions. Only identical or very similar variables were merged, resulting in a total list of 270 variables. Stage 2 resulted in a list of 41 variables that scored more than 100 points. These were discussed at the consensus meeting and resulted in a template consisting of 48 variables each allocated into one of six categories to create a structure for the final template (Additional file 1: Printer friendly version of template).

Pre-incident data

This section gives the reader a brief overview of the geographical setting and infrastructure in the affected area before the incident occurred. It will ask for information such as the population and population density, pre-existing infrastructure stating accessibility in the area (by road, train, boat, foot) and the telecommunications network. It will also allow the author to provide information on specific local issues, such as civil unrest or political situation.

Emergency medical system (EMS) background

These variables aim to describe pre-incident EMS characteristics in the affected area before the incident, and will allow the reader to evaluate its relevance to their own EMS system. The data includes information on the EMS, response activation, staffing of ambulance services, availability of resources, triage and major incident training. Variables describing staffing of ambulance services were modified from a previous template [21] (Additional file 1: Questions 1-11).

Incident characteristics

This section consists of eight variables pertaining to incident background, access, evacuation of patient, infrastructure damage, sites with separate EMS infrastructures and hazards. These variables will allow users of the database to stratify incidents by type (e.g. earthquake, nuclear accident) and enables comparative analysis of incidents within the same category (Additional file 1: Questions 12-19).

EMS response data

A previously published template [25] influenced variables concerning EMS response: initial actions by first medical team, medical coordination, medical communications and medical command structure. Variables concerning timings and hospitals receiving patients are similar to another existing template [26]. Other data in this section are: personnel, transport and material resources on scene and data on patient surge. Many of these variables will be considered quality indicators that will not only describe the response, but also allow researchers to compare medical response, and identify strengths and weaknesses (Additional file 1: Questions 20-32).

Patient characteristics

The variables include population at risk from the incident and actual casualties, gender, number of dead and patient distribution. The patient distribution variables include both EMS response data (surge data) and patient characteristics (triage data). Paediatric patients were subcategorized according to existing age categories [27]. The aim of these variables will be to identify factors that may affect patient mortality and morbidity (Additional file 1: Questions 33-46).

Key lessons

This section allows the report author to communicate the key successes and problems in the major incident medical response and give the readers an overview of main lessons. For research purposes this section together with the first category will provide data for qualitative analysis (Additional file 1: Questions 47-48).

Online reporting

Following the consensus process, a webpage allowing online reporting using the template has been developed. The template can be accessed, freely downloaded and reports submitted free of article processing charge on: http://www.majorincidentreporting.org (Figure 1). The editorial process for submitted reports will be described on the webpage.
Figure 1
Figure 1

Front page of .http://www.majorincidentreporting.org The first global open access webpage for reporting from major incidents and accessing existing reports.

Discussion

Through this consensus process, a group of European major incident experts have developed a template for the global reporting from pre-hospital major incident medical management. The authors of several existing templates contributed to this process aiming to create a practical and accessible template focused on the pre-hospital phase of major incident response. The template consisting of 48 variables in 6 categories can be completed and freely accessed online. An aim is that the template be widely implemented and accessible. It will be feasibility tested and revised in collaboration with experts working in this field.

The data variables and outcome

Informed scientific evaluation of the impact of pre-hospital interventions on patient outcomes is vital [28]. Measures of outcome used in previous studies of daily EMS have been analysed according to the six Ds: death, disease, discomfort, disability, dissatisfaction and debt (cost). Death and disease were the most common outcomes evaluated and the other 4 Ds were infrequently measured [29]. Little is published regarding the validity, reliability and responsiveness of instruments for measuring outcome following major trauma [30]. In the template 30-day mortality is included, however different definitions influence how performance outcome is evaluated [31]. The template also includes data on proxy outcomes such as triage, surge and safety on site that reflect the immediate major incident medical management without being influenced by other phases such as the hospital phase and rehabilitation.

Implementation of the template

The template will be implemented using an online database http://www.majorincidentreporting.org.

Using this template and contributing to creating an open access global database for reporting major incidents is an act of solidarity towards improving the outcome of disasters. The template is intentionally focused upon the variables that the expert group believes are likely to be of most importance to future incidents. The template content and availability of a database for reporting aims to reduce the threshold for reporting and increase global capture of critical information. In addition to the humanitarian aspect in the development of a global major incident database and dissemination of key lessons, we aim to maximise contribution by waiving the fee for report submission. The reporting of experiences through the website should not prevent individual publications in other journals.

Ethical considerations

The template has been created to avoid compromising patient confidentiality, therefore no identifiable patient data will be reported to the database nor will there be the facility to upload images. Pre-approval from ethics committees to access data necessary for filling in the template would be preferable to allow reporting to take place quickly after an incident and prevent time delay in disseminating relevant knowledge to others. However, it is uncertain how practical it will be to obtain such ethics approvals. The greatest impact of major incidents in the form of natural disasters are in low-and middle-income countries [2], the same applies for road traffic accidents [3]. Due to these facts it is morally and scientifically important that a template be available and relevant for reporting and analysis also in these areas. Whether this is the case for this template will be sought answered in a feasibility study.

Strengths and limitations

Using a nominal group technique consensus process may be a limitation with regards to selection of participants and wording of the question influencing the outcome [19]. The composition of experts ensures a valid mix of practical and theoretical approach to major incident management. Stages 1 and 2 ensured that each expert opinion was equally weighted in the nomination of variables. Disaster terminology is yet another challenge [32] and various definitions exist [33–35]. Our definition of a major incident aligns with previous definitions [36], and aims to be easily comprehensible.

Accurate data collection in extreme circumstances may be challenging and may be reflected in erroneous data collection. Moreover there may be difficulties in gaining complete data capture following incidents particularly when security, military and political sensitivities are involved or infrastructure damage is such that no data collection occurs. The database will not provide the basis for calculating denominators and nominators for use in major incident epidemiology, for this purpose, mandatory national registries are necessary [37]. These issues as well as feasibility regarding the type and amount of data to be reported, and whether including only European experts in this process was a limitation will be addressed in feasibility studies.

Conclusions

Consensus was achieved amongst experts on key data variables for reporting the pre-hospital major incident medical management. The template is the basis for the first global open access database for major incidents and is available for downloading and reporting on http://www.majorincidentreporting.org. The use of a uniform dataset after each major incident will allow for comparative analysis to take place and aims to identify improvements for future medical response. We invite those directly involved in the response to or management of a previous or future major incident to freely use the template and publish reports open access.

Notes

Declarations

Acknowledgements

The authors acknowledge the continuous support from the members of the NAAF making this project possible, and thank Drs Andreas Kruger, Espen Fevang, Kjetil Ringdal and Assoc. professor Stephen JM Sollid for sharing their experiences from previous similar processes, Annette Krampl and Frode Flesjø for organising the meeting at Torpomoen, Bjørn Are Holth and Tore Nøtnæs at Statistics Norway for providing expert opinion on the template.

We are grateful for Professor Per Kullings participation in the consensus process before his tragic and untimely death. This paper is published in memory of his great work.

Collaborators: Gareth Davies, Michel Debacker, Erika Frischknecht Christensen, Juhana Hallikainen, Troels Martin Hansen, Jorine Juffermans, Per Kulling, Vidar Magnusson, Jannicke Mellin-Olsen, Kai Milke, Anders Rüter, Stephen JM Sollid, Wolfgang Voelckel.

Funding

The Norwegian Air Ambulance Foundation (NAAF) employs SF, MR and HML. DL, JT and TW received departmental funding only. No additional funding was obtained. All expenses for the consensus meeting in Torpomoen and development of the online reporting system were covered by the NAAF.

Authors’ Affiliations

(1)
Department of Research and Development, Norwegian Air Ambulance Foundation, Drøbak, Norway
(2)
Anaesthesia and Critical Care Research Group, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway
(3)
Field of Pre-hospital Critical Care, Network of Medical Sciences, University of Stavanger, Stavanger, Norway
(4)
Department of Anesthesiology and Intensive Care, Akershus University Hospital, Lørenskog, Norway
(5)
School of Clinical Sciences, University of Bristol, Bristol, UK
(6)
London’s Air Ambulance, The Helipad, Royal London Hospital, Whitechapel, London, UK
(7)
Department of Anaesthesiology and Intensive Care, Hammerfest Hospital, Finnmark Health Trust, Hammerfest, Norway
(8)
Norwegian Trauma Competency Service, Oslo University Hospital, Oslo, Norway

References

  1. International Societies of the Red Cross and Crescent: World Disaster Report 2011. 2011, GenevaGoogle Scholar
  2. Guha-Sapir DVF, Below R, Ponserre S: Annual Disaster Statistical Review 2011: the numbers and trends. 2012, CRED: BrusselsGoogle Scholar
  3. World Health Organization: Global status on Road Safety 2013. Supporting a decade of action. 2013, GenevaGoogle Scholar
  4. Bogen KT, Jones ED: Risks of mortality and morbidity from worldwide terrorism: 1968–2004. Risk Anal. 2006, 26: 45-59. 10.1111/j.1539-6924.2006.00706.x.View ArticlePubMedGoogle Scholar
  5. World Bank: World Development Report 2011: conflict, security and development. 2011, Washington DCView ArticleGoogle Scholar
  6. Dara SI, Ashton RW, Farmer JC, Carlton PK: Worldwide disaster medical response: an historical perspective. Crit Care Med. 2005, 33 (Suppl 1): S2-S6.View ArticlePubMedGoogle Scholar
  7. Bradt DA, Aitken P: Disaster medicine reporting: the need for new guidelines and the CONFIDE statement. Emerg Med Australas. 2010, 22: 483-487. 10.1111/j.1742-6723.2010.01342.x.View ArticlePubMedGoogle Scholar
  8. Stratton SJ: Use of structured observational methods in disaster research: “Recurrent medical response problems in five recent disasters in the Netherlands”. Prehosp Disaster Med. 2010, 25: 137-138. 10.1017/S1049023X0000786X.View ArticlePubMedGoogle Scholar
  9. Stratton SJ: The Utstein-style Template for uniform data reporting of acute medical response in disasters. Prehosp Disaster Med. 2012, 27: 219-10.1017/S1049023X12000817.View ArticlePubMedGoogle Scholar
  10. Castren M, Hubloue I, Debacker M: Improving the science and evidence for the medical management of disasters: Utstein style. Eur J Emerg Med. 2012, 19: 275-276. 10.1097/MEJ.0b013e3283571743.View ArticlePubMedGoogle Scholar
  11. Lockey DJ: The shootings in Oslo and Utoya island July 22, 2011: lessons for the International EMS community. Scand J Trauma Resusc Emerg Med. 2012, 20: 4-10.1186/1757-7241-20-4.PubMed CentralView ArticlePubMedGoogle Scholar
  12. Fattah S, Rehn M, Reierth E, Wisborg T: Systematic literature review of templates for reporting prehospital major incident medical management. BMJ Open. 2013, 3: e002658-PubMed CentralView ArticlePubMedGoogle Scholar
  13. Juffermans J, Bierens JJ: Recurrent medical response problems during five recent disasters in the Netherlands. Prehosp Disaster Med. 2010, 25: 127-136. 10.1017/S1049023X00007858.View ArticlePubMedGoogle Scholar
  14. Simon R, Teperman S: The World Trade Center attack. Lessons for disaster management. Crit Care. 2001, 5: 318-320. 10.1186/cc1060.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Romundstad L, Sundnes KO, Pillgram-Larsen J, Roste GK, Gilbert M: Challenges of major incident management when excess resources are allocated: experiences from a mass casualty incident after roof collapse of a military command center. Prehosp Disaster Med. 2004, 19: 179-184.PubMedGoogle Scholar
  16. Carresi AL: The 2004 Madrid train bombings: an analysis of pre-hospital management. Disasters. 2008, 32: 41-65. 10.1111/j.1467-7717.2007.01026.x.View ArticlePubMedGoogle Scholar
  17. Aylwin CJ, Konig TC, Brennan NW, Shirley PJ, Davies G, Walsh MS, Brohi K: Reduction in critical mortality in urban mass casualty incidents: analysis of triage, surge, and resource use after the London bombings on July 7, 2005. Lancet. 2006, 368: 2219-2225. 10.1016/S0140-6736(06)69896-6.View ArticlePubMedGoogle Scholar
  18. Rodoplu U, Arnold JL, Tokyay R, Ersoy G, Cetiner S, Yucel T: Mass-casualty terrorist bombings in Istanbul, Turkey, November 2003: report of the events and the prehospital emergency response. Prehosp Disaster Med. 2004, 19: 133-145.PubMedGoogle Scholar
  19. Van de Ven AH, Delbecq AL: The nominal group as a research instrument for exploratory health studies. Am J Public Health. 1972, 62: 337-342. 10.2105/AJPH.62.3.337.PubMed CentralView ArticlePubMedGoogle Scholar
  20. Fevang E, Lockey D, Thompson J, Lossius HM: The top five research priorities in physician-provided pre-hospital critical care: a consensus report from a European research collaboration. Scand J Trauma Resusc Emerg Med. 2011, 19: 57-10.1186/1757-7241-19-57.PubMed CentralView ArticlePubMedGoogle Scholar
  21. Kruger AJ, Lockey D, Kurola J, Di Bartolomeo S, Castren M, Mikkelsen S, Lossius HM: A consensus-based template for documenting and reporting in physician-staffed pre-hospital services. Scand J Trauma Resusc Emerg Med. 2011, 19: 71-10.1186/1757-7241-19-71.PubMed CentralView ArticlePubMedGoogle Scholar
  22. Ringdal KG, Coats TJ, Lefering R, Bartolomeo S, Steen PA, Røise O, Handolin L, Lossius HM, Utstein TCD expert panel: The Utstein template for uniform reporting of data following major trauma: a joint revision by SCANTEM, TARN. DGU-TR and RITG. Scand J Trauma Resusc Emerg Med. 2008, 16: 7-10.1186/1757-7241-16-7.PubMed CentralView ArticlePubMedGoogle Scholar
  23. Sollid SJ, Lockey D, Lossius HM: A consensus-based template for uniform reporting of data from pre-hospital advanced airway management. Scand J Trauma Resusc Emerg Med. 2009, 17: 58-10.1186/1757-7241-17-58.PubMed CentralView ArticlePubMedGoogle Scholar
  24. Lossius HM, Krüger AJ, Ringdal KG, Sollid SJM, Lockey DJ: Developing templates for uniform data documentation and reporting in critical care using a modified nominal group technique. Scand J Trauma Resusc Emerg Med. 2013, 21: 80-10.1186/1757-7241-21-80.PubMed CentralView ArticlePubMedGoogle Scholar
  25. Debacker M, Hubloue I, Dhondt E, Rockenschaub G, Ruter A, Codreanu T, Koenig KL, Schultz C, Peleg K, Halpern P, Stratton S, Della Corte F, Delooz H, Ingrassia PL, Colombo D, Castrèn M: Utstein-style template for uniform data reporting of acute medical response in disasters. PLoS Current. 2012, 4: e4f6cf3e8df15a-Google Scholar
  26. Leiba A, Schwartz D, Eran T, Blumenfeld A, Laor D, Goldberg A, Weiss G, Zalzman E, Ashkenazi I, Levi Y, Bar-Dayan Y: DISAST-CIR: Disastrous incidents systematic analysis through components, interactions and results: application to a large-scale train accident. J Emerg Med. 2009, 37: 46-50. 10.1016/j.jemermed.2007.09.025.View ArticlePubMedGoogle Scholar
  27. World Health Organization: WHO Position Paper: Pediatric Age Categories to be Used in Differentiating Between Listing on Model Essential Medicines List for Children.http://archives.who.int/eml/expcom/children/Items/PositionPaperAgeGroups.pdf,
  28. Spaite DW: Outcome analysis in EMS systems. Ann Emerg Med. 1993, 22: 1310-1311. 10.1016/S0196-0644(05)80113-1.View ArticlePubMedGoogle Scholar
  29. Brice JH, Garrison HG, Evans AT: Study design and outcomes in out-of-hospital emergency medicine research: a ten-year analysis. Prehosp Emerg Care. 2000, 4 (2): 144-150. 10.1080/10903120090941416.View ArticlePubMedGoogle Scholar
  30. Sleat GK, Ardolino AM, Willett KM: Outcome measures in major trauma care: a review of current international trauma registry practice. Emerg Med J. 2011, 28: 1008-1012. 10.1136/emermed-2011-200326.View ArticlePubMedGoogle Scholar
  31. Skaga NO, Eken T, Jones JM, Steen PA: Different definitions of patient outcome: consequences for performance analysis in trauma. Injury. 2008, 39: 612-622. 10.1016/j.injury.2007.11.426.View ArticlePubMedGoogle Scholar
  32. Nocera A: Australian major incident nomenclature: it may be a ‘disaster’ but in an ‘emergency’ it is just a mess. ANZ J Surg. 2001, 71: 162-166. 10.1046/j.1440-1622.2001.02056.x.View ArticlePubMedGoogle Scholar
  33. National Library of Medicine.http://sis.nlm.nih.gov/dimrc/glossaries.html,
  34. UNISDR Disaster Terminology.http://www.unisdr.org/we/inform/terminology,
  35. Sundnes KO: Health disaster management: guidelines for evaluation and research in the Utstein style: executive summary. Task Force on Quality Control of Disaster Management. Prehosp Disaster Med. 1999, 14: 43-52.PubMedGoogle Scholar
  36. Advanced Life Support Group: Major Incident Medical Management and Support, the Practical Approach at the scene. 2002, Plymouth: BMJ Publishing GroupGoogle Scholar
  37. Radestad M, Jirwe M, Castren M, Svensson L, Gryth D, Ruter A: Essential key indicators for disaster medical response suggested to be included in a national uniform protocol for documentation of major incidents: a Delphi study. Scand J Trauma Resusc Emerg Med. 2013, 21: 68-10.1186/1757-7241-21-68.PubMed CentralView ArticlePubMedGoogle Scholar

Copyright

© Fattah et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Advertisement

Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine

ISSN: 1757-7241