This study intended to create symptom-based triage algorithms for the initial encounter with terror-attack victims. The goals of the triage algorithms include: (1) early recognition; (2) avoiding contamination; (3) early use of antidotes; (4) appropriate handling of unstable, contaminated victims; and (5) provisions of force protection. The algorithms also address industrial accidents and emerging infections, which have similar clinical presentations and risks for contamination as weapons of mass destruction (WMD).
The algorithms were developed using references from military and civilian sources. They were tested and adjusted using a series of theoretical patients from a CD-ROM chemical, biological, radiological/nuclear, and explosive victim simulator. Then, the algorithms were placed into a card format and sent to experts in relevant fields for academic review.
Six inter-connected algorithms were created, described, and presented in figure form. The "attack" algorithm, for example, begins by differentiating between overt and covert attack victims (A covert attack is defined by epidemiological criteria adapted from the Centers for Disease Control and Prevention (CDC) recommendations). The attack algorithm then categorizes patients either as stable or unstable. Unstable patients flow to the "Dirty Resuscitation" algorithm, whereas, stable patients flow to the "Chemical Agent" and "Biological Agent" algorithms. The two remaining algorithms include the "Suicide Bomb/Blast/Explosion" and the "Radiation Dispersal Device" algorithms, which are inter-connected through the overt pathway in the "Attack" algorithm.
A civilian, symptom-based, algorithmic approach to the initial encounter with victims of terrorist attacks, industrial accidents, or emerging infections was created. Future studies will address the usability of the algorithms with theoretical cases and utility in prospective, announced and unannounced, field drills. Additionally, future studies will assess the effectiveness of teaching modalities used to reinforce the algorithmic approach.
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[Show abstract][Hide abstract] ABSTRACT: A set of symptom-based, all-hazards, decision-making algorithms was designed to aid the first-contact provider during early patient presentations after a terrorist incident.
The primary objective was to assess the usability of these algorithms. A secondary objective was to assess the psychometric properties of the testing scenarios.
This was a written, usability assessment of the algorithms employing a convenience sample of hospital-based, healthcare providers who had not taken any specific training in the use of the algorithms. A series of 26 paragraph-length, moderately difficult scenarios was created to reflect possible agents, means of attack, and types of patients. Each of the 26 scenarios requires that one make a triage choice on the "attack" algorithm (the trunk algorithm), then proceed to one of four other branch algorithms (dirty resuscitation, chemical agents, biological agents, bomb/blast/radiation dispersal device) to make a final triage choice. Conditional scores based on getting both the attack and final card correct were calculated for each algorithm.
Nineteen attending physicians, 50 emergency medicine residents, and 41 nurses took the assessment. The total score was 45% correct for all participants. The score on the attack algorithm was 66% correct. Dirty resuscitation, biological, chemical, and bomb/blast scores were 46%, 54%, 46%, and 51% respectively. The probability of guessing the correct answer on the attack algorithm was 1/7 or 14%. The conditional probability of guessing both the attack algorithm and the final card correct ranged from 4.7% for the biological, chemical, and bomb/blast algorithms to 2.4% for the dirty resuscitation algorithm. Item discrimination, item difficulty, and Cronbach's alpha were acceptable for the overall test. Certain individual items had item difficulty levels suggesting they were too difficult and should be replaced in future versions of the test.
Performance on the test suggests that participants did substantially better than would have been expected by chance alone. Future efforts will revise the algorithms with the goal of simplification. Revision of the testing instrument and testing algorithm use after instruction also are needed.
Prehospital and disaster medicine: the official journal of the National Association of EMS Physicians and the World Association for Emergency and Disaster Medicine in association with the Acute Care Foundation 23(3):234-41.
[Show abstract][Hide abstract] ABSTRACT: Chemical, biological, radiological, nuclear, and explosive (CBRNE) incidents are low frequency, high impact events that require specialized training outside of usual clinical practice. Educational modalities must recreate these clinical scenarios in order to provide realistic first responder/receiver training.
High fidelity, mannequin-based (HFMB) simulation and video clinical vignettes were used to create a simulation-based CBRNE course directed at the recognition, triage, and resuscitation of contaminated victims. The course participants, who consisted of first responders and receivers, were evaluated using a 43-question pre- and post-test that employed 12 video clinical vignettes as scenarios for the test questions. The results of the pre-test were analyzed according to the various medical training backgrounds of the participants to identify differences in baseline performance. A Scheffe post-hoc test and an ANOVA were used to determine differences between the medical training backgrounds of the participants. For those participants who completed both the pre-course and post-course test, the results were compared using a paired Student's t-test.
A total of 54 first responders/receivers including physicians, nurses, and paramedics completed the course. Pre-course and post-course test results are listed by learner category. For all participants who took the pre-course test (n = 67), the mean value of the test scores was 53.5 +/- 12.7%. For all participants who took the post-course test (n = 54), the mean value of the test scores was 78.3 +/-10.9%. The change in score for those who took both the pre- and post-test (n = 54) achieved statistical significance at all levels of learner.
The results suggest that video clinical vignettes and HFMB simulation are effective methods of CBRNE training and evaluation. Future studies should be conducted to determine the educational and cost-effectiveness of the use of these modalities.
Prehospital and disaster medicine: the official journal of the National Association of EMS Physicians and the World Association for Emergency and Disaster Medicine in association with the Acute Care Foundation 08/2006; 21(4):272-5. DOI:10.1017/S1049023X00003824
[Show abstract][Hide abstract] ABSTRACT: Incidents of significant consequence that create surge may require special research methods to provide reliable, generalizable results. This report was constructed through a process of literature review, expert panel discussion at the journal's consensus conference, and iterative development. Traditional clinical research methods that are well accepted in medicine are exceptionally difficult to use for surge incidents because the incidents are very difficult to reliably predict, the consequences vary widely, human behaviors are heterogeneous in response to incidents, and temporal conditions prioritize limited resources to response, rather than data collection. Current literature on surge research methods has found some degree of reliability and generalizability in case-control, postincident survey methods, and ethnographical designs. Novel methods that show promise for studying surge include carefully validated simulation experiments and survey methods that produce validated results from representative populations. Methodologists and research scientists should consider quasi-experimental designs and case-control studies in areas with recurrent high-consequence incidents (e.g., earthquakes and hurricanes). Specialists that need to be well represented in areas of research include emergency physicians and critical care physicians, simulation engineers, cost economists, sociobehavioral methodologists, and others.