University of Manchester
Title: What is the inter-rater agreement of injury classification using the WHO minimum data set for emergency medical teams?Author names:Dr. Anisa J. N. Jafar, MBChB(e) MPH PhD(Corresponding author)HCRI Ellen Wilkinson Building, University of Manchester, Devas Street, Manchester M13 9PTTel: +44 (0)161 275 0245Fax: anisa.jafar@manchester.ac.ukDr Jamie C Sergeant, MSci, DPhilCentre for Biostatistics, University of Manchester, Manchester Academic Health Science Centre, Manchester, UKArthritis Research UK Centre for Epidemiology, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, UKjamie.sergeant@manchester.ac.ukProf. Fiona Lecky, PhDCentre for Urgent and Emergency Care Research (CURE) Group, ScHARR, University of Sheffield Regent’s Court, Regent Street, Sheffield S1 4DA f.e.lecky@manchester.ac.uk AJNJ undertook this study as part of a PhD funded by the Royal College of Emergency Medicine & Hong Kong Jockey Club Charities Trust however JCS and FL have no funding sources to declare.AJNJ provided consultancy to the UK EMT & contributed to the WHO EMT MDS working group however JCS and FL have no conflicts of interests to declare.Word count: 3236Number of tables: 4Number of figures: 2Keywords: disaster planning and response; data management; global healthAbstract BackgroundIn 2017 the WHO produced its first minimum data set (MDS) for emergency medical team (EMT) daily reporting during sudden onset disasters (SODs), following expert consensus. The MDS was deliberately designed to be simple in order to improve the rate of data capture however it is new and untested. This study assesses the inter-rater agreement between practitioners when performing the injury aspect of coding within the WHO EMT MDS. Methods25 clinical case vignettes were developed, reflecting potential injuries encountered in a SOD. These were presented online from April to July 2018 to practitioners who have experience of/training in managing patients in SODs The practitioners were from UK-Med’s members, AUSMAT’s Northern Territory members and NZMAT members. Practitioners were asked to code injuries according to the WHO EMT MDS case classifications. Randolph’s kappa statistic for free-marginal multi-rater data was calculated for the whole data-set as well as subgroups to ascertain inter-rater agreementResults86 practitioners responded (20.6% response rate), giving >2000 individual case responses. Overall agreement was moderate at 67.9% with a kappa of 0.59 [CI 0.49,0.69]. Despite subgroups of paramedics (kappa 0.63 [CI 0.53,0.72]), doctors (kappa 0.61 [CI 0.52, 0.69]) and those with disaster experience (kappa 0.62 [CI 0.52, 0.71]) suggesting slightly higher agreement, their CIs (and those of other subgroups) suggest overall similar and moderate levels of practitioner agreement in classifying injuries according to the MDS categories.ConclusionsAn inter-rater agreement of 0.59 is moderate, at best, however it gives MoHs some sense of how tightly they may interpret injury data derived from daily reports using the WHO EMT MDS. Furthermore, this kappa is similar to established but more complex (thus more contextually impractial) injury scores. Similar studies, with weighting for injury likelihood using sample data from SODs would further refine the level of expected inter-rater agreement. What this paper addsWhat is already known on this subjectThe WHO emergency minimum data set for daily reporting includes a simple injury score designed to allow for resource allocation during disastersWhat this study addsThis study tests inter-rater agreement of this injury score and finds a moderate level of agreementThe inter-rater agreement within this score is not dissimilar to more widely used and detailed injury scoresThe evidence from this study will help ministries of health and the WHO to interpret disaster injury data and translate it into more accurate resource managementBackgroundThe year 2013 saw the publication of minimum standards for medical teams working internationally in response to disasters ADDIN EN.CITE <EndNote><Cite><Author>GHC</Author><Year>2013</Year><RecNum>4366</RecNum><DisplayText>(1)</DisplayText><record><rec-number>4366</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1494952472" guid="d7376889-97ea-46de-bb7a-df5b3ba23676">4366</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>GHC</author></authors></contributors><titles><title>Classification and minimum standards for foreign medical teams in sudden onset disasters</title></titles><dates><year>2013</year></dates><pub-location>;(1). This “blue-book” as it is informally known, has been a true game-changer and pivot point for emergency medical team (EMT) practice worldwide and has set in motion a process of World Health Organisation (WHO) verification. The WHO standards and verification seek to ensure that EMTs are working to a minimum acceptable standard and when called upon to assist a foreign government with a disaster, can perform as required ADDIN EN.CITE <EndNote><Cite><Author>WHO</Author><Year>2017</Year><RecNum>4723</RecNum><DisplayText>(2)</DisplayText><record><rec-number>4723</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1501798745" guid="c399cd8f-f5ba-4d9d-ba95-9027fe4b62c7">4723</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>WHO</author></authors></contributors><titles><title>Emergency Medical Teams Initiative</title></titles><volume>2017</volume><number>31st July</number><dates><year>2017</year></dates><urls><related-urls><url>;(2). Within this process it was recognised that in order for EMTs to develop to this standard, certain guidelines for best practice would be needed. One area which warranted its own working group was the minimum data set (MDS) for EMT daily reporting ADDIN EN.CITE <EndNote><Cite><Author>Kubo</Author><Year>2016</Year><RecNum>4635</RecNum><DisplayText>(3)</DisplayText><record><rec-number>4635</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1494952504" guid="45edbc70-9d6e-4842-95bf-4aec77db8491">4635</key></foreign-keys><ref-type name="Conference Proceedings">10</ref-type><contributors><authors><author>Kubo, Tatsuhiko</author></authors></contributors><titles><title>The EMT Minimum Data Set Recommendation by the WG</title><secondary-title>The WHO EMT Global Meeting</secondary-title></titles><dates><year>2016</year></dates><pub-location>Hong Kong</pub-location><urls></urls></record></Cite></EndNote>(3). The purpose of the MDS was to identify a minimum level of information which could be expected to be provided by each EMT to the ministry of health (MoH)/EMT co-ordinating cell (EMTCC) on a daily basis. The group recognised the balance which was required between too much information (which would make the task impossible for each EMT) and enough information (to allow the MoH/EMTCC to coordinate an effective response). Led by representatives from the WHO EMT Secretariat, the Japan International Cooperation Agency (JICA) and Israel’s Agency for International Development Cooperation (MASHAV) the final components of the MDS were deliberated over by an expert consensus group from different EMTs worldwide, alongside an epidemiologist and one country’s MoH representative. Prior to this there had been an initial meeting followed by a wider online consultation with a total of 59 organisations spanning 28 countries ADDIN EN.CITE <EndNote><Cite><Author>WHO</Author><Year>2018</Year><RecNum>4724</RecNum><DisplayText>(4)</DisplayText><record><rec-number>4724</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1501798746" guid="623c3d1c-bb71-4da9-b2a7-492e55fc1258">4724</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>WHO</author></authors></contributors><titles><title>EMT-MDS Daily Reporting Form</title></titles><dates><year>2018</year></dates><urls><related-urls><url>;(4). 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ADDIN EN.CITE.DATA (5-7). The subsequent challenge includes understanding the utility of the data to resource-manage an acute response. The MDS is split into 6 main sections: team information, summary data, demographic information, diagnosis, intervention and outcome (see figure 1 for the latest iteration of the MDS) Within “diagnosis” there is included some injury coding (see table 1). Compared to the MDS illness coding, the injury coding has the most potential for individual interpretation because it involves an element of severity coding. Within this study, for that reason, the focus is solely upon injury coding. However this does not intend to detract from the high number of illness presentations to EMTs alongside injuries.Injury coding optionsCoding guideMajor head / spine injuryAny major trauma to the scalp, skull, brain and spinal cord requiring hospitalisation and/or general anaesthesia.Major torso injuryAny major trauma involving the chest and abdomen requiring hospitalisation and/or general anaesthesia.?Major extremity injuryAny upper and lower extremity injures requiring hospitalisation and/or spinal or general anaesthesia.Moderate injuryInjury that can be treated as an outpatient requiring conscious sedation or regional anaesthesia excluding spinal anaesthesia.Minor injuryInjury that requires first aid and light dressing care with/without local anaesthesia.Other diagnpsis, not specified aboveAny injury which does not fit into the above categories Table 1: WHO minimum data set emergency medical team classification options for injuries alongside coding guide The coding itself is very simple and does have an associated guideline description as to which injuries ought to be coded as such (see table 1) ADDIN EN.CITE <EndNote><Cite><Author>Kubo</Author><Year>2016</Year><RecNum>4635</RecNum><DisplayText>(3)</DisplayText><record><rec-number>4635</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1494952504" guid="45edbc70-9d6e-4842-95bf-4aec77db8491">4635</key></foreign-keys><ref-type name="Conference Proceedings">10</ref-type><contributors><authors><author>Kubo, Tatsuhiko</author></authors></contributors><titles><title>The EMT Minimum Data Set Recommendation by the WG</title><secondary-title>The WHO EMT Global Meeting</secondary-title></titles><dates><year>2016</year></dates><pub-location>Hong Kong</pub-location><urls></urls></record></Cite></EndNote>(3). This guideline was developed to be deliberately broad, with the intention that the information collected on injuries (as well as other components) would be simple and quick to complete whilst able to guide resource management at an MoH/EMTCC level. If such quick, evolving, healthcare data is reliably available on a daily basis, then the MoH/EMTCC will have the information they need to allocate surgical and rehabilitation (as well as medical and maternal health) resource in the short term. Furthermore, projections of longer term disability and rehabilitation requirements may be possible at the early stages which would permit the MoH to make informed decisions when financing its own in-country resources, as well as ensuring any external assistance is precisely what is required. It is well established that international assistance can potentially do more harm than good ADDIN EN.CITE <EndNote><Cite><Author>Sommers-Flanagan</Author><Year>2007</Year><RecNum>4845</RecNum><DisplayText>(8)</DisplayText><record><rec-number>4845</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1572737496" guid="7da51daf-a358-4308-b360-b9450b5ba44d">4845</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Sommers-Flanagan, Rita</author></authors></contributors><titles><title>Ethical Considerations in Crisis and Humanitarian Interventions</title><secondary-title> Dec 2007</date></pub-dates></dates><publisher>Taylor & Francis Group</publisher><work-type>research-article</work-type><urls><related-urls><url> & BEHAVIOR, Vol. 17, No. 2, 2007: pp. 187–202</electronic-resource-num><language>en</language></record></Cite></EndNote>(8) unless it is carefully targeted where required. Such acute data may help safeguard against inadvertently detrimental humanitarian assistance.Other injury coding systems do exist such as the Abbreviated Injury Scale (AIS) which informs calculation of the Injury Severity Score (ISS) and the New Injury Severity Score (NISS), there is also the ICD classification of injury: all are widely used in clinical practice globallyPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYWtlcjwvQXV0aG9yPjxZZWFyPjE5NzQ8L1llYXI+PFJl
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ADDIN EN.CITE.DATA (13-16). Inter-rater agreement (or reliability) demonstrates how much agreement there is between different raters who are scoring or rating the same case. This concept is important to consider if we are using an injury score for the purposes of resource allocation: if there is poor inter-rater agreement, then the relationship between data produced and the subsequent indicated resource required will be heavily dependent on who is doing the rating. Considering that the purpose of the MDS is to help guide and effectively resource manage a disaster, it is essential to understand to what degree the injury coding is reproducible. The commonly used scores such as ISS, NISS and AIS have varying levels of inter-rater agreementPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SZWFkLUFsbHNvcHA8L0F1dGhvcj48WWVhcj4yMDA0PC9Z
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ADDIN EN.CITE.DATA (13-17) depending on the context of testing, however they differ from the MDS injury codes because there is considered to be a tighter definition of the “right” way to code. The MDS coding guide (shown in table 1) is broad and heavily reliant on clinical interpretation therefore it perhaps matters less whether injuries are coded “correctly” and more that they are coded consistently between practitioners. Currently we have no data as to whether this injury coding system is coded consistently between practitioners. Given that it has been already rolled out within the WHO MDS and thus has the potential to have real influence on resource allocation during disasters, it is essential that we develop an understanding of how the MoH/EMTCC can interpret the results. If there is tight inter-rater agreement, then extrapolating precise injury resource allocation to any data produced may be prudent. If there is very weak inter-rater agreement then resource allocation needs to be much more cautious in response to the daily data.This study aims to demonstrate the level of inter-rater agreement of injury scoring by EMT practitioners using the WHO EMT MDS.MethodsStudy design25 case vignettes were developed initially by one of the researchers who has an emergency medicine background as well as knowledge of disaster medicine. The cases were created using: the relevant syllabus areas of the UK curricula followed by emergency medicine and surgical trainees ADDIN EN.CITE <EndNote><Cite><Author>ISCP</Author><RecNum>4808</RecNum><DisplayText>(18, 19)</DisplayText><record><rec-number>4808</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1537195006" guid="39594e97-3612-4b8b-84b0-dd2eabf9d293">4808</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>ISCP</author></authors></contributors><titles><title>The syllabus</title><secondary-title>Intercollegiate Surgical Curriculum Programme</secondary-title></titles><volume>2018</volume><number>17th September</number><dates></dates><urls><related-urls><url> app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1537195007" guid="441298ce-baee-4f8f-baa1-25bdfaaa48ce">4809</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>RCEM</author></authors></contributors><titles><title>Curriculum - 2015 Curriculum</title></titles><volume>17th September</volume><number>2018</number><keywords><keyword>Emergency Medicine</keyword><keyword>Training</keyword><keyword>curriculum</keyword><keyword>2015 curriculum</keyword><keyword>2010 curriculum</keyword><keyword>WPBA</keyword><keyword>Workplace Based Assessment</keyword><keyword>Assessment</keyword><keyword>Life Support Courses</keyword></keywords><dates><year>2016</year></dates><urls><related-urls><url>;(18, 19); alignment with material from an ongoing study of disaster resource management (whose preliminary findings have been presented at conference proceedings ADDIN EN.CITE <EndNote><Cite><Author>Bartolucci</Author><Year>2018</Year><RecNum>4810</RecNum><DisplayText>(20)</DisplayText><record><rec-number>4810</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1537369582" guid="61087543-eb66-4b9f-88f9-da46c0a3f3e4">4810</key></foreign-keys><ref-type name="Electronic Article">43</ref-type><contributors><authors><author>Bartolucci, Andrea</author></authors></contributors><titles><title>Decision Support Framework for the Deployment of Emergency
Response Relief Teams after Sudden Onset Disasters (SODs)</title></titles><dates><year>2018</year></dates><pub-location>IPRED? Abstract E-book</pub-location><urls><related-urls><url>;(20)); feedback from colleagues with extensive field experience; and feedback from a pilot test of cases with from 14 practitioners who commonly contribute to the management of injured patients (emergency physicians, general practitioners, anaesthetists and surgeons). The final wording of the vignettes was approved by a second researcher who has an emergency medicine background and extensive experience in trauma research. The case vignettes are shown in table 2. Between April and July 2018 participants were asked to categorise these vignettes using the available options from the WHO MDS for EMTs as shown in table 1.Table 2: Case vignettes provided to participants Case numberCase vignette132 year old man, injury to face following a fall onto concrete: fracture on radiograph involving lateral orbital wall and zygomatic arch. No displacement or deformity, no ocular/facial symptoms other than pain.221 year old female, exposed to flying debris during earthquake. Multiple penetrating debris injury to chest and abdomen, stable, no organ involvement clinically, wound management is the limit of surgical requirement. Clinically stable.314 year old male, open wound to genitalia, likely right testicle involvement (cause: sharp floating debris following severe flooding). Clinically stable.446 year old male, loss of distal half of terminal phalanx middle finger of non-dominant hand due to guillotine-like injury.580 year old male, penetrating chest injury following tsunami, large left sided haemo-pneumothorax666 year old female, fall from 3 steps due to after-shock. Anterior wedge fracture of L4. No neurological deficit.710 year old male caught in landslide impact on home, head injury, initial loss of consciousness for a few seconds, large scalp haematoma, no evidence clinically of cerebral oedema, GCS 15817 year old female large, open depressed skull fracture with GCS 9. Unknown mechanism.934 year old male 30% mostly full thickness burns to chest and abdomen following house fire.1050 year old female inversion injury to ankle, when running out of damaged building. Swollen, no fracture on radiograph, likely sprain, unable to weight-bear1127 year old male, fall after ground tremors. Closed right Colles fracture on radiograph, no neurovascular deficit, in good alignment.1278 year old male exposed to scalding liquid during earthquake. 35% burns to limbs some superficial and some deep dermal.1358 year old female, right intracapsular neck of femur fracture following fall escaping flood-waters.1433 year old female hit by falling tree, complex open mid-shaft tibial and fibular fracture left side on radiograph.1518 year old male, shielding sister from falling debris, clavicle fracture on radiograph, middle third, non-displaced.1665 year old male, fall down flight of stairs during aftershock, odontoid peg fracture on radiograph, no neurological deficit.1713 year old female >50 shrapnel wounds to both lower limbs following earthquake-triggered explosion, no compartment syndrome, clinically and radiologically no foreign bodies requiring removal, no tendon, neurovascular, significant muscular damage. Full motor and sensory function intact.1879 year old male, escaping at haste from volcanic eruption nearby left, extracapsular neck of femur fracture on radiograph.1943 year old male, exposed to forest fire, 6% superficial dermal non-circumferential burns to thigh2031 year old male, injured during flood, superficial 6cm laceration to forearm requiring stitches no tendon or neurovascular involvement. Full motor and sensory function intact.2125 year old female, hit to face by falling debris, bilateral orbital blow-out fractures on radiograph, reduced visual acuity.2211 year old female, eye injury (small debris flew into face) – evidence of subconjunctival haemorrhage, bruising to eyelid, no pupillary or corneal involvement, non-painful full range of ocular movements and normal visual acuity.2322 year old male, helping mother out of building. Penetrating injury of 2cm nail into sole of left foot.2447 year old female 3% epidermal burn to left lower flank from falling onto domestic heater.2538 year old male, blunt injury to left abdomen as parts of building fell onto him, high clinical suspicion of splenic rupture.These cases were entered into an online survey platform (Google Forms? Google LLC, Mountainview, CA) within a password protected account created specifically for this study. Informed consent was integrated within the survey (see Appendix 1 for a copy of the full survey content) along with links to further details of the study. Study setting & participantsThe pool of participants was a convenience sample, limited by response rate, derived from three sources: UK-Med’s register members, the Australian Medical Assistance Team (AUSMAT)’s Northern Territory members and the New Zealand Medical Assistance Team (NZMAT) members. UK-Med is a registered charity which, amongst other health-related international activities hosts and trains National Health Service (NHS) medical staff for the UK Emergency Medical Team (UK EMT). Both AUSMAT and NZMAT have a register of practitioners engaged in disaster response. The healthcare professionals in these three WHO verified teams deploy overseas, when invited, to provide clinical care following disasters. The participant pool inclusion criteria was restricted to trained EMT members who encounter injured patients in their clinical practice by virtue of their speciality. These teams were approached (as well as other teams who did not respond) owing to their primary practice language (and first language) being English. Thus their use of clinical terminology is similar. This meant that the whole study population was more likely to have a similar response to the case vignettes, not one materially influenced by their language of practice. To broaden the study would require more in-depth language modification and piloting which would significantly delay the study. In view that the MDS is already in use, it was deemed important to acknowledge the study limitations yet remain pragmatic in delivering timely answers to this important research question.The teams initially were approached via email to identify a gatekeeper who had administrative access to contacting the team’s registered members individually. Sometimes it took a chain of emails to identify the individuals who could agree to the team members being contacted and ultimately the gatekeeper who could do the contacting. These gatekeepers then sent an email (written by the research team) to trained register members, inviting them to participate, providing details of the study and providing a link to the participant information sheet and the survey itself. No more than 3 requests to participate were sent to the participant pool over the study period. Data was collected on participant clinical role, speciality, length of time in clinical practice and experience of working in disasters.OutcomesThe primary outcome is the level of agreement of classification of injuries between multiple clinical raters using the WHO EMT MDS. Secondary outcome measures include sub-group analysis of level of agreement depending on:clinical roledisaster experiencespecialitynumber of years of clinical experienceAnalysisThe data was transferred into a Microsoft? Excel? for Mac 2011 version 14.7.6 (170621) ? 2010 document, coded and then input into an online calculator of Randolph’s kappa statistic for free marginal data. ADDIN EN.CITE <EndNote><Cite><Author>Randolph</Author><Year>2008</Year><RecNum>4806</RecNum><DisplayText>(21)</DisplayText><record><rec-number>4806</rec-number><foreign-keys><key app="EN" db-id="z2etvptxjpt29qesvw8vp9aue2p2esapzt05" timestamp="1533220752" guid="065c9c09-5d1d-4ce4-af59-119091372d42">4806</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>Randolph, J. J.</author></authors></contributors><titles><title>Online Kappa Calculator [Computer software]</title></titles><dates><year>2008</year></dates><urls><related-urls><url>;(21) The kappa statistic quantifies agreement between raters, accounting for agreement that may occur by chance. Free marginal data denotes that there was not a known number of cases to assign to each category.EthicsThe University of Manchester ethical review manager granted approval for this low risk study on 22nd January 2018 with reference 2018-3577-4808.Patient and public involvementNo patient involved.ResultsOf the 417 individuals invited, 86 (20.6%) completed the exercise. Table 3 shows a breakdown of those invited and those who participated. Slightly higher numbers of paramedics responded than would have been expected proportionate to those invited, whilst proportionately slightly lower numbers of allied health professionals responded. In general this appears to be a broadly representative sample of the participant pool. Appendix 2 and figure 2 may be cross-referenced to table 1 to see the breakdown of categorisation for each case vignette. Some cases such as 1, 2, 3, 4, 6, 7, 13, 15, 17, 18 appeared to show wider disagreement than others. This included all cases in which the subject was under 17 years of age and both cases with neck of femur fractures. Figure 2 shows the percentage distribution of categories assigned to each case.Table 3: those invited as compared to those who participatedRoleinvited (% total)participated (% total)Doctor161 (39)37 (43)Nurse163 (39)29 (34)Paramedic56 (13)18 (21)Allied health professional* ?37 (9)2 (2)Total41786*including operating department practitioners and physiotherapistsFull data analysis showed a kappa statistic of 0.59 with a 95% confidence interval (0.50, 0.68) (table 4). Of the sub-groups, the specialities of being a doctor or paramedic showed a small increase in inter-rater agreement, whilst having disaster experience showed a similar incremental increase. However, these differences are small and accompanied by overlapping confidence intervals, hence there is little evidence of difference in agreement between the subgroups.Table 4: All participants & subgroup Randolph's kappa statistic?% overall agreementfree-marginal kappa95% confidence intervalAll participants65.710.59(0.50, 0.68)??Paramedics68.890.63(0.53, 0.72)Nurses63.370.56(0.46, 0.66)Doctors67.210.61(0.52, 0.69)??No disaster experience64.880.58(0.48, 0.67)Disaster experience67.930.62(0.52, 0.71)??Emergency medicine65.790.59(0.49, 0.69)Non-emergency medicine66.430.6(0.50, 0.69)??<20 years clinical experience65.240.58(0.48, 068)20+ years clinical experience66.340.6(0.51, 0.69)Commonly the medical literature uses one of two systems to assign the description of agreement level of kappa resultsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MYW5kaXM8L0F1dGhvcj48WWVhcj4xOTc3PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (22, 23). These systems place the WHO MDS injury scoring inter-rater agreement from this study as “moderate” with confidence intervals spanning up into “good/substantial”.DiscussionThis study took the WHO EMT MDS injury categories and tested their inter-rater agreement using 86 practitioners scoring a set of 25 case vignettes. The study found similar levels of inter-rater agreement across all subgroups and an overall inter-rater agreement of 0.59 (0.5, 0.68). It is challenging to compare the inter-rater agreement of this injury coding system with other coding systems such as the ICD, AIS, ISS or NISS because there are considerably more elements to their calculation. When these more established scoring systems are taken at face-value however there is an interpretable level of agreement which has been found to range from “fair” to “substantial/good”PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NYWNLZW56aWU8L0F1dGhvcj48WWVhcj4xOTg1PC9ZZWFy
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AG==
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AG==
ADDIN EN.CITE.DATA (13, 15). What this suggests is that the WHO EMT MDS injury codes are comparable in this study with the inter-rater agreement found for more established injury scores. The study was not able to (and was not primarily designed or powered to) robustly identify whether certain features such as speciality background or previous disaster experience conferred a truly higher inter-rater agreement. Although this may be a feature of the study numbers and choice of case vignettes, it is interesting that the kappa statistic and associated confidence intervals were so similar between the subgroups. Assessing formally whether subgroup differences exist would require further study. Understanding in addition to merely identifying any differences would be likely to require a qualitative element to the study.With a kappa statistic of 0.59 (0.50, 0.68) overall, the results lie at the upper limits of the “moderate” level of inter-rater agreement and confidence intervals span the “moderate” and “good/substantial” strengths of agreementPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MYW5kaXM8L0F1dGhvcj48WWVhcj4xOTc3PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (22, 23). If this result is replicated in real deployments then the EMTCC/MoH are able to have some concept of how tightly resource allocation should be assigned depending on information provided by the WHO EMT MDS. It is difficult to be precise with the exact margin of error likely to be produced by resource allocating according to data which has “moderate” agreement; thus it would be important that those allocating resource have an understanding of such limitations. That said, moderate agreement will mean that data is more consistent than if this study had found lower levels of inter-rater agreement which is not unusual within clinical scoring systems. Furthermore, over time an understanding of how to interpret and use the reporting data for resource planning and allocation - when based on analysing the MDS injury data – will be developed. Post incident analyses can then compare whether or not MDS usage improves the accuracy of resource provision compared to historical incident analyses. Subsequent deployments may benefit from algorithms whereby more accurate resource provision can be implemented with more confidence as to lower and upper limits of resource required based on interpreting the WHO EMT MDS information. Healthcare resources are often a scarce commodity, even at baseline, in the regions of the world most affected by SODs. Thus, acute and accurate data is essential during a SOD, in order to make best use of the available healthcare resources and thus provide targeted and tailored care where it is most needed. The first challenge faced is collection and collation of regular data from EMTs: the MDS has been deliberately developed to be simple enough to achieve this. The second challenge is then knowing how to translate this data into useful information to direct resource allocation such as surgical, medical and rehabilitation teams. This study has demonstrated “moderate” inter-rater agreement of very simple injury scoring, which, if replicated in larger and wider studies, provides a level of confidence with which to interpret the injury data and thus allocate relevant resource. Avoiding the use of more complex injury scoring systems reduces the burden on EMTs, especially given that injury is only one part of the workload that EMTs manage. For the injury scoring to be more useful a better inter-rater agreement would be of benefit, thus training of EMTs in coding uniformity may achieve this. LimitationsIt is clear that case vignettes coded as an online survey are not reflective of the holistic process of managing a live patient in a field hospital and then completing coding. However to achieve a reproducible test of coding for all participants, it is necessary to generate an artificial scenario. To enhance realism, an alternative may have been to present images and/or video footage however this would be resource intensive with no guarantee of having a truly better reflection of real life. Furthermore, if this study is to be validated in a larger and wider population, bandwidth and/or download speeds may have an impact upon which groups are most able to respond. Thinking a step further ahead, the cases used in this and subsequent larger studies could be adapted into a training package with an aim to improve inter-rater agreement (such that the majority category selected for each case would allow the cases in turn to serve as examples of each category). Therefore any such training package would need to be resource light and therefore ideally avoid images and video. Of note, we have no way of knowing whether each participant completed the survey entirely independently as it was completed online. It is unlikely, given the sheer geographical spread of the participants that there was significant, if any, conferring between participants and certainly there would be no incentive to do so. More possible could be conferring with another person (perhaps a domestic partner with healthcare background or a work colleague). The latter possibility may lend some reality to the study as in field hospitals we rarely work in isolation, and conferring with a colleague over coding would not be unusual. Another point of debate is the equal weighting of the cases. It is certain that some of the cases will be much less often seen than others, therefore it could be argued that a weighting ought to be applied to the more common cases as it is their inter-rater agreement which ought to contribute more to the overall figure. That said, we do not have enough granular data available in the wider literature from EMTs to be clear how this weighting should accurately be assigned and this may generate an unrepresentative result. The 20% survey response rate is low, and thus we do not have more detailed characteristics of those who did respond other than their profession. Moreover, the groups who completed the scoring represented a narrow coverage of global EMT practitioners. Wider coverage could be achieved by repeating the same study across EMT practitioners from other geographical locations with appropriate language modification of the cases to ensure equivalent meaning was portrayed. It may also prove useful to provide plain definitions of any anatomical terms to reduce the chance of any misinterpretation. Finally, this paper focusses purely on the injury aspect of the diagnostic scoring because this is the easiest to model using case vignettes and the most open to clinician interpretation.ConclusionThis study has demonstrated that by using case vignettes, the WHO EMT MDS is able to generate a moderate level of inter-rater agreement according to the commonly understood assignment of kappa readings between 0.41 and 0.6.PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MYW5kaXM8L0F1dGhvcj48WWVhcj4xOTc3PC9ZZWFyPjxS
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ADDIN EN.CITE.DATA (22, 23) Thus the WHO EMT MDS, which is already expected to be used, can be understood with some level of confidence as to how tightly to interpret the data it is likely to generate for resource management in the context of injury. If higher levels of agreement are required to inform more accurate resource allocation then additional standardised training and/or guidance for EMT practitioners may achieve this. Ultimately, improving appropriate resource allocation to those requiring healthcare in SODs is highly likely to improve patient care in contexts where need is at its greatest.Figure 1. Latest iteration of WHO EMT MDS Figure 2. Percentage distribution of categories assigned to each caseAcknowledgementsThe authors would like to thank Anna Baldwin of UK-Med, Emma Lawrey of NZMAT and Kathleen McDermott of AUSMAT for facilitating access to a participant pool.FundingThis work was supported by the Royal College of Emergency Medicine & Hong Kong Jockey Club Charities Trust who supported the first author’s PhD which generated this study. ADDIN EN.REFLIST References1.GHC. Classification and minimum standards for foreign medical teams in sudden onset disasters. : WHO, 2013.2.WHO. Emergency Medical Teams Initiative 2017 [cited 2017 31st July]. Available from: T, editor The EMT Minimum Data Set Recommendation by the WG. The WHO EMT Global Meeting; 2016; Hong Kong.4.WHO. EMT-MDS Daily Reporting Form. 2018.5.Jafar AJ, Norton I, Lecky F, Redmond AD. A literature review of medical record keeping by foreign medical teams in sudden onset disasters. Prehosp Disaster Med. 2015;30(2):216-22. doi: 10.1017/S1049023X15000102. PubMed PMID: 25659602.6.Jafar AJN, Fletcher RJ, Lecky F, Redmond AD. A Pilot of a UK Emergency Medical Team (EMT) Medical Record During a Deployment Training Course. Prehosp Disaster Med. 2018:1-7. Epub 2018/07/02. doi: 10.1017/S1049023X18000468. PubMed PMID: 29962356.7.Kubo T, editor EMT MDS Daily Reporting. WHO EMT Meeting; 2019; Bangkok.8.Sommers-Flanagan R. Ethical Considerations in Crisis and Humanitarian Interventions. . 2007;17(2):187-202. doi: ETHICS & BEHAVIOR, Vol. 17, No. 2, 2007: pp. 187–202.9.Baker SP, O'Neill B, Haddon W, Long WB. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma. 1974;14(3):187-96. PubMed PMID: 4814394.10.Osler T, Baker SP, Long W. A modification of the injury severity score that both improves accuracy and simplifies scoring. J Trauma. 1997;43(6):922-5; discussion 5-6. Epub 1998/01/07. PubMed PMID: 9420106.11.AAAM. The Abbreviated Injury Scale Dictionary – 2015 version. Des Plaines, Chicago, USA2015.12.WHO. International Classification of Diseases 11th Edition. 2018.13.Ringdal KG, Skaga NO, Hestnes M, Steen PA, R?islien J, Rehn M, et al. Abbreviated Injury Scale: not a reliable basis for summation of injury severity in trauma facilities? Injury. 2013;44(5):691-9. Epub 2012/07/24. doi: 10.1016/j.injury.2012.06.032. PubMed PMID: 22831922.14.Smith IM, Naumann DN, Guyver P, Bishop J, Davies S, Lundy JB, et al. Interobserver Variability in Injury Severity Scoring After Combat Trauma: Different Perspectives, Different Values? J Spec Oper Med. 2015;15(2):86-93. PubMed PMID: 26125170.15.MacKenzie EJ, Shapiro S, Eastham JN. The Abbreviated Injury Scale and Injury Severity Score. Levels of inter- and intrarater reliability. Med Care. 1985;23(6):823-35. PubMed PMID: 3925257.16.Read-Allsopp C. Establishing inter-rater reliability scoring in a state trauma system. J Trauma Nurs. 2004;11(1):35-9. PubMed PMID: 16515155.17.Fleischman RJ, Mann NC, Dai M, Holmes JF, Wang NE, Haukoos J, et al. Validating the Use of ICD-9 Code Mapping to Generate Injury Severity Scores. J Trauma Nurs. 2017;24(1):4-14. doi: 10.1097/JTN.0000000000000255. PubMed PMID: 28033134; PubMed Central PMCID: PMCPMC5323458.18.ISCP. The syllabus [cited 2018 17th September]. Available from: . Curriculum - 2015 Curriculum 2016 [cited 17th September 2018]. Available from: A. Decision Support Framework for the Deployment of EmergencyResponse Relief Teams after Sudden Onset Disasters (SODs)2018. Available from: JJ. Online Kappa Calculator [Computer software] 2008. Available from: JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159-74. PubMed PMID: 843571.23.Altman DG. Practical statistics for medical research1991. ................
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