The SDMPH 10-year anniversary conference created an opportunity for a researcher to present at a professional association conference to advance their research by seeking consensus of statements using Delphi methodology.

Conference attendees and SDMPH members who did not attend the conference were identified as Delphi experts. Experts rated their agreement of each statement on a 7- point linear numeric scale. Consensus amongst experts was defined as a standard deviation < = 1. Presenters submitted statements relevant to advancing their research to the authors to edit to fit Delphi statement formatting.

Statements attaining consensus were included in the final report after the first round. Those not attaining consensus moved to the second round in which experts were shown the mean response of the expert panel and their own response for opportunity to reconsider their rating for that round. If reconsideration attained consensus, these statements were included in the final report. This process repeated in a third and final round.

37 Experts agreed to participate in the first round; 35 completed the second round, and 34 completed the third round; 35 statements attained consensus; 3 statements did not attain consensus.

A Delphi technique was used to establish expert consensus of statements submitted by the SDMPH conference presenters to guide their future education, research, and training.

Medical professionals can use mass-casualty triage systems to assist them in prioritizing patients from mass-casualty incidents (MCIs). Correct triaging of victims will increase their chances of survival. Determining the triage system that has the best performance has proven to be a difficult question to answer. The Advanced Prehospital Triage Model (Modelo Extrahospitalario de Triaje Avanzado; META) and Sort, Assess, Lifesaving Interventions, Treatment/Transport (SALT) algorithms are the most recent triage techniques to be published. The present study aimed to evaluate the META and SALT algorithms’ performance and statistical agreement with various standards. The secondary objective was to determine whether these two MCI triage systems predicted patient outcomes, such as mortality, length-of-stay, and intensive care unit (ICU) admission.

This retrospective study used patient data from the trauma registry of an American College of Surgeons Level 1 trauma center, from January 1, 2018 through December 31, 2020. The sensitivity, specificity, and statistical agreement of the META and SALT triage systems to various standards (Revised Trauma Score [RTS]/Sort Triage, Injury Severity Score [ISS], and Lerner criteria) when applied using trauma patients. Statistical analysis was used to assess the relationship between each triage category and the secondary outcomes.

A total of 3,097 cases were included in the study. Using Sort triage as the standard, SALT and META showed much higher sensitivity and specificity in the Immediate category than for Delayed (Immediate sensitivity META 91.5%, SALT 94.9%; specificity 60.8%, 72.7% versus Delayed sensitivity 28.9%, 1.3%; specificity 42.4%, 28.9%). With the Lerner criteria, in the Immediate category, META had higher sensitivity (77.1%, SALT 68.6%) but lower specificity (61.1%) than SALT (71.8%). For the Delayed category, SALT showed higher sensitivity (META 61.4%, SALT 72.2%), but lower specificity (META 75.1%, SALT 67.2%). Both systems showed a positive, though modest, correlation with ISS. For SALT and META, triaged Immediate patients tended to have higher mortality and longer ICU and hospital lengths-of-stay.

Both META and SALT triage appear to be more accurate with Immediate category patients, as opposed to Delayed category patients. With both systems, patients triaged as Immediate have higher mortality and longer lengths-of-stay when compared to Delayed patients. Further research can help refine MCI triage systems and improve accuracy.

This study investigates the impact of primary care utilisation of a symptom-based head and neck cancer risk calculator (Head and Neck Cancer Risk Calculator version 2) in the post-coronavirus disease 2019 period on the number of primary care referrals and cancer diagnoses.

The number of referrals from April 2019 to August 2019 and from April 2020 to July 2020 (pre-calculator) was compared with the number from the period January 2021 to August 2022 (post-calculator) using the chi-square test. The patients’ characteristics, referral urgency, triage outcome, Head and Neck Cancer Risk Calculator version 2 score and cancer diagnosis were recorded.

In total, 1110 referrals from the pre-calculator period were compared with 1559 from the post-calculator period. Patient characteristics were comparable for both cohorts. More patients were referred on the cancer pathway in the post-calculator cohort (pre-calculator patients 51.1 per cent vs post-calculator 64.0 per cent). The cancer diagnosis rate increased from 2.7 per cent in the pre-calculator cohort to 3.3 per cent in the post-calculator cohort. A lower rate of cancer diagnosis in the non-cancer pathway occurred in the cohort managed using the Head and Neck Cancer Risk Calculator version 2 (10 per cent vs 23 per cent, p = 0.10).

Head and Neck Cancer Risk Calculator version 2 demonstrated high sensitivity in cancer diagnosis. Further studies are required to improve the predictive strength of the calculator.

Critically injured patients have experienced delays in being transported to hospitals during Mass Casualty Incidents (MCIs). Extended pre-hospital times (PHTs) are associated with increased mortality. It is not clear which factors affect overall PHT during an MCI. This systematic review aimed to investigate PHTs in trauma-related MCIs and identify factors associated with delays for triaged patients at incident scenes.

This systematic review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Web of Science, CINAHL, MEDLINE, and EMBASE were searched between January and February 2022 for evidence. Research studies of any methodology, and grey literature in English, were eligible for inclusion. Studies were narratively synthesized according to Cochrane guidance.

Of the 2025 publications identified from the initial search, 12 papers met the inclusion criteria. 6 observational cohort studies and 6 case reports described a diverse range of MCIs. PHTs were reported variably across incidents, from a median of 35 minutes to 8 hours, 8 minutes. Factors associated with prolonged PHT included: challenging incident locations, concerns about scene safety, and adverse decision-making in MCI triage responses. Casualty numbers did not consistently influence PHTs. Study quality was rated moderate to high.

PHT delays of more than 2 hours were common. Future MCI planning should consider responses within challenging environments and enhanced timely triage decision-making.

Primary care referrals received by secondary care services are vetted or triaged to pathways best suited for patients’ needs. If knowledge-based triaging is used by vetting clinicians, accuracy is required to avoid incorrect decisions being made. With limited evidence to support best practice, we aimed to evaluate consistency across vetting clinicians’ decisions and their agreement with a criterion decision.

Twenty-nine trained vetting clinicians (18 female) representative of pay grades independently triaged five musculoskeletal physiotherapy referral cases into one of 10 decisions using an internally developed triage tool. Agreement across clinicians’ decisions between and within cases was assessed using Fleiss’s kappa overall and within pay grade. Proportions of triage decisions consistent with criterion decisions were assessed using Cochran’s Q test.

Clinician agreement was fair for all cases (κ = 0.385) irrespective of pay grade but varied within clinical cases (κ = −0.014–0.786). Proportions of correct triage decisions were significantly different across cases [Q(4) = 33.80, P < 0.001] ranging from 17% to 83%.

Agreement and consistency in decisions were variable using the tool. Ensuring referrer information is accurate is vital, as is developing, automating and auditing standards for certain referrals with clear pathways. But we argue that variable vetting outcomes might represent healthy pathway abundance and should not simply be automated in response to perceived inefficiencies.

To describe the epidemiological profile of multiple casualty incidents (MCI) and contribute to the better understanding of their impacts in Northern Spain.

Retrospective, population-based observational study of MCI between 2014 and 2020 in 5 autonomous communities (Aragón, Castilla y León, Galicia, the Basque Country and Principado de Asturias) that participated in the MCI Database of Northern Spain. Inclusion criteria was any incident with 4 or more patients needing ambulance mobilization. A total of 54 variables were collected. This study presents the most relevant results.

There were 253 MCI. Of these, 79.8% were road traffic accidents, 12.3% fires or explosions, 2.0% poisonings and 5.9% defined as others. Monthly average was 2.9 (SD = 0.35; EEM = 15.90), average of victims by MCI was 6.8 (CI95% 6.16 - 7.60). There were significantly (P < 0.05) more victims in 3 types of MCI (fires, poisonings, and others). We saw 37.7% of MCI involved 4 victims, 18.8% 5 victims, and 37.9% more than 5. Mean response time was 30.8 minutes (95% CI 28.6 - 33.1), longer in maritime incidents. A total of 67% (95% CI 64.5 - 69.5) of victims were mild.

Road traffic accidents are the most frequent MCI and minor injuries predominate. More than 50% of the MCI have 5 or fewer patients. Fires had significantly more mild patients and significantly more resources deployed. Maritime incidents had a significantly longer response time.

For the pediatric population, there is no consensus on which triage system to use for mass-casualty incidents (MCI). A scoping review was conducted to identify the most accurate triage system for pediatric patients in MCIs.

MEDLINE (NLM, Bethesda, MA, USA), Embase (Elsevier Inc., Amsterdam, Netherlands), CINAHL (EBSCO Information Services, Ipswitch, MA, USA), and The Cochrane CENTRAL Register of Controlled Trials (John Wiley & Sons, Hoboken, NJ, USA), as well as Scopus (Elsevier Inc., Amsterdam, Netherlands), Global Health (Centre for Agriculture and Bioscience International, Wallingford, UK), Global Health Archive (Centre for Agriculture and Bioscience International, Wallingford, UK), and Global Index Medicus (World Health Organization, Geneva, Switzerland) were searched for relevant studies that were divided into 3 categories: accuracy of a single system, comparison of 2 or more primary triage system and comparison of secondary triage systems. Grey literature was also searched.

996 studies were identified from which 18 studies were included. Systems studied were found to have poor inter-rater reliability, had a low level of agreement between providers, had missed critically ill patients or were not externally validated. 11 studies compared pediatric MCI triage algorithms using different strategies and the most accurate algorithm was not identified. A recently developed secondary triage system, specifically for pediatric patients, was found to perform better than the comparison triage system.

Although some algorithms performed better than others, no primary triage algorithm was accurate enough for the pediatric population. However, only 1 secondary triage algorithm was found to be superior to the others.

To describe experience using general practitioners (GPs), with an extended role (GPwER) in spinal medicine, to expedite assessment, triage, and management of patients referred from primary care for specialist spinal surgical opinion.

Low back and neck pain are common conditions in primary care. Indiscriminate or inappropriate referral to a spinal surgeon contributes to long waiting times. Previous attempts at triaging patients who really require a surgical opinion have used practice nurses, physiotherapists, clinical algorithms, and interdisciplinary screening clinics.

Within the setting of an independent spinal care centre, we have used GPs specially trained in spinal practice to expedite the assessment and triage of new referrals between 2015 and 2021. We reviewed feedback from a Patient Satisfaction Questionnaire and the postgraduate backgrounds, training, practice with regard to triage of new referrals, and experiences of the GPs who were recruited

Six GPwER had a mean of 26 years of postgraduate experience before appointment (range 10–44 years). The first four GPwER, appointed between 2015 and 2018, underwent an ad hoc in-house, interdisciplinary training programme and saw 2994 new patients between 2016 and 2020. After GPwER, assessment in only 18.9% (range 12.6 to 22.7%) of these patients was a spinal surgical opinion deemed necessary. Waiting times to see the spinal surgeon remained at 6–8 weeks despite a three-fold annual increase (from 340 to 1058) in new referrals. A Patient Satisfaction Questionnaire revealed high levels of satisfaction with the performances of the GPwER across seven dimensions. A dedicated training programme was designed in 2020, and the last two appointees underwent 20 h of clinical teaching prior to practice. Initial experience using GPwER, here termed ‘Spinal Clinicians’, suggests they are efficient at screening for patients needing spinal surgical referral. Establishing a recognised training programme, assessment, and certification for these practitioners are the next challenges.

This study aimed to investigate the use of the head and neck cancer risk calculator version 2 in a primary care setting and to evaluate the impact of the risk calculator on the number of referrals stratified by urgency and cancer yield.

Referrals between April 2019 and August 2019, April 2020 and July 2020 (pre-risk calculator) and August 2020 and July 2021 (post-risk calculator) were analysed. Referral urgency, head and neck cancer risk calculator version 2 score, cancer diagnosis, cancer type and further investigations were recorded.

The 2023 patient encounters were analysed; there were 1110 (55 per cent) referrals before head and neck cancer risk calculator version 2 use and 913 (45 per cent) after head and neck cancer risk calculator version 2 use. A higher proportion of older (p < 0.001) and male (p < 0.013) patients were seen post-head and neck cancer risk calculator version 2 use. All cancer cases were seen on the urgent suspicion of cancer pathway post-head and neck cancer risk calculator version 2 use; however, a higher proportion of patients were seen as urgent suspicion of cancer (51.1 vs 83.5 per cent; p < 0.001). Overall, the cancer diagnosis rate increased from 2.7 to 4.1 per cent.

The head and neck cancer risk calculator version 2 had high sensitivity in cancer diagnosis. More studies are required to optimise the predicted versus actual cancer probability gap.

The coronavirus disease 2019 (COVID-19) pandemic challenged health care systems in an unprecedented way. Due to the enormous amount of hospital ward and intensive care unit (ICU) admissions, regular care came to a standstill, thereby overcrowding ICUs and endangering (regular and COVID-19-related) critical care. Acute care coordination centers were set up to safely manage the influx of COVID-19 patients. Furthermore, treatments requiring ICU surveillance were postponed leading to increased waiting lists.

A coordination center organizing patient transfers and admissions could reduce overcrowding and optimize in-hospital capacity.

The acute lack of hospital capacity urged the region West-Netherlands to form a new regional system for patient triage and transfer: the Regional Capacity and Patient Transfer Service (RCPS). By combining hospital capacity data and a new method of triage and transfer, the RCPS was able to effectively select patients for transfer to other hospitals within the region or, in close collaboration with the National Capacity and Patient Transfer Service (LCPS), transfer patients to hospitals in other regions within the Netherlands.

From March 2020 through December 2021 (22 months), the RCPS West-Netherlands was requested to transfer 2,434 COVID-19 patients. After adequate triage, 1,720 patients with a mean age of 62 (SD = 13) years were transferred with the help of the RCPS West-Netherlands. This concerned 1,166 ward patients (68%) and 554 ICU patients (32%). Overcrowded hospitals were relieved by transferring these patients to hospitals with higher capacity.

The health care system in the region West-Netherlands benefitted from the RCPS for both ward and ICU occupation. Due to the coordination by the RCPS, regional ICU occupation never exceeded the maximal ICU capacity, and therefore patients in need for acute direct care could always be admitted at the ICU. The presented method can be useful in reducing the waiting lists caused by the delayed care and for coordination and transfer of patients with new variants or other infectious diseases in the future.

Triage is a tool used to determine patients’ severity of illness or injury within minutes of arrival. This study aims to assess the reliability and validity of a new computer-based triage decision support tool, ANKUTRIAGE, prospectively.

ANKUTRIAGE, a 5-level triage tool was established considering 2 major factors, patient’s vital signs and characteristics of the admission complaint. Adult patients admitted to the ED between July and October, 2019 were consecutively and independently double triaged by 2 assessors using ANKUTRIAGE system. To measure inter-rater reliability, quadratic-weighted kappa coefficients (Kw) were calculated. For the validity, associations among urgency levels, resource use, and clinical outcomes were evaluated.

The inter-rater reliability between users of ANKUTRIAGE was excellent with an agreement coefficient (Kw) greater than 0.8 in all compared groups. In the validity phase, hospitalization rate, intensive care unit admission and mortality rate decreased from level 1 to 5. Likewise, according to the urgency levels, resource use decreased significantly as the triage level decreased (P < 0.05).

ANKUTRIAGE proved to be a valid and reliable tool in the emergency department. The results showed that displaying the key discriminator for each complaint to assist decision leads to a high inter-rater agreement with good correlation between urgency levels and clinical outcomes, as well as between urgency levels and resource consumptions.

In recent years, the use of drones in health emergencies has increased. Among their main benefits are avoiding endangering rescuers, travelling long distances in a short time, or contacting victims in risky situations; but despite their multiple advantages, their use has not been fully demonstrated.

This study aims to identify the available evidence on the use of drones in emergency health care compared to traditional health care.

Systematic review of the literature was conducted. Search protocols were developed to locate studies that met the established selection criteria. Six experimental or quasi-experimental studies with high methodological quality published from the beginning of indexing until 2020 were included.

Drones covered a significantly larger area than other traditional tracking methods and were very useful for performing preliminary triage, determining needs, and knowing the scene prior to the arrival of rescuers. In addition, drones reduced the time required to locate the victim.

Drones are an element to be taken into account when attending health emergencies as they significantly improve the distance travelled to locate accident victims, have the possibility of performing triage prior to the arrival of the health care units, and improve the time and quality of the care provided.

Many triage algorithms exist for use in mass-casualty incidents (MCIs) involving pediatric patients. Most of these algorithms have not been validated for reliability across users.

Investigators sought to compare inter-rater reliability (IRR) and agreement among five MCI algorithms used in the pediatric population.

A dataset of 253 pediatric (<14 years of age) trauma activations from a Level I trauma center was used to obtain prehospital information and demographics. Three raters were trained on five MCI triage algorithms: Simple Triage and Rapid Treatment (START) and JumpSTART, as appropriate for age (combined as J-START); Sort Assess Life-Saving Intervention Treatment (SALT); Pediatric Triage Tape (PTT); CareFlight (CF); and Sacco Triage Method (STM). Patient outcomes were collected but not available to raters. Each rater triaged the full set of patients into Green, Yellow, Red, or Black categories with each of the five MCI algorithms. The IRR was reported as weighted kappa scores with 95% confidence intervals (CI). Descriptive statistics were used to describe inter-rater and inter-MCI algorithm agreement.

Of the 253 patients, 247 had complete triage assignments among the five algorithms and were included in the study. The IRR was excellent for a majority of the algorithms; however, J-START and CF had the highest reliability with a kappa 0.94 or higher (0.9-1.0, 95% CI for overall weighted kappa). The greatest variability was in SALT among Green and Yellow patients. Overall, J-START and CF had the highest inter-rater and inter-MCI algorithm agreements.

The IRR was excellent for a majority of the algorithms. The SALT algorithm, which contains subjective components, had the lowest IRR when applied to this dataset of pediatric trauma patients. Both J-START and CF demonstrated the best overall reliability and agreement.