The new military occupational specialty for combat medics, the 91W, requires that all medics successfully pass the National Registry of Emergency Medical Technicians examination. The objective of this study was to supplement standard emergency medical technician training with a three-dimensional, computer-based, virtual training simulator and to assess whether scores and pass rates could be increased. Combat medics (N = 167) were selected for training through the usual noncommissioned officer unit selection process and were randomized by cohort to the training simulator. Results showed no significant differences in National Registry of Emergency Medical Technicians examination scores (t = 1.019, df= 153, p = 0.745, one-tailed) or pass rates (χ^sup 2^ = 1.575, df = 1, p = 0.209). The findings, however, were used to construct two models of combat medic characteristics that can be used to assist in initial selection for emergency medical technician courses and subsequent counseling of soldiers on course completion. With further research, these models could be refined for Army-wide use to increase the cost-effectiveness of combat medic recruitment, training, and testing.

Introduction

In October 1999. a major change was set in motion to transform the army "into a strategically responsive force that is dominant across the full spectrum of operations."1 This vision initiated a huge training mission for the Army Medical Department, to "make sure that when the soldier walks on point, he's not alone."2 Medic training needed to be radically revamped to better incorporate skills in trauma management, competence in resuscitating and monitoring casualties without medical supervision over long evacuation distances, and enhanced versatility to support all types of Army operations.

The transition to the new combat medic, designated as the military occupational specialty (MOS) of 9IW health care specialist, officially began October 2001 for all new recruits. However, the combat medics who were currently on active duty had to meet the new training requirements for this new MOS by 2007 (reserves by 2009). This meant that ~44.000 combat medics (9IB medical specialist, 91C licensed practical nurse, and several low-density MOSs) had to be trained before transitioning into the new 9IW MOS, becoming the second largest MOS in the Army.3

One of the major requirements for transitioning medics was to successfully pass the National Registry of Emergency Medical Technicians (NREMT) certification examination after completion of a basic emergency medical technician (EMT) course. Up to this point, basic EMT courses were few in number, either contracted through accredited civilian programs or present in medical facilities only to train medics assigned to ambulance sections. Overall, these programs, with few qualified EMT instructors, were not designed to consistently train large volumes of combat medics.

As the Army Medical Department-wide training structures readjusted to meet the new training mission using limited resources, the average first-time pass rates for transitioning medics fell below the national average (unpublished observation). Just as the Chief of Staff of the Army, at that time, looked to technology as a force multiplier, this study looked to technology as an instruction multiplier. The express purpose was to determine whether technology could be used to augment basic EMT-B training and to validate the use of technology as a training strategy. The hypothesis was that transitioning medics who experienced standard EMT training supplemented with technology would have increases in their NREMT examination scores and pass rates and would be more cost-effective, compared with transitioning medics who did not.

Materials

The technology selected was a computer-based, virtual, EMT training simulation software called STATCare (Simulation Technologies for Advanced Trauma Care) that allowed the user to interact with a three-dimensional virtual patient. Medical Research and Materials Command and Research Triangle Institute developed the software as a dual-funded project4 (Fig. 1).

This software was chosen because it was mobile (personal computer-based), required limited space (no extensive programming), and provided training on military-unique skills required of first-responder medics during combat. Additionally, the high level of interaction, low-risk decision-making, and sensory stimulation made it ideal for selection for training combat medics. These combat medics were also considered the generation of computer game players; therefore, using this mode of instruction was postulated to be advantageous in capturing and holding their attention.

Study Design

This study used a quasi-experimental cohort design in which combat medics were scheduled for a program cohort that was randomized to receive one of two instructional strategies, i.e., a standard EMT-B course or a standard EMT-B course augmented with the STATCare training simulators.

Methods

From July 2002 and May 2003, six EMT-B classes were conducted at the Joint Medical Training Center at Fort Lewis, Washington. Combat medics requiring EMT-B courses to transition to 91W were selected and scheduled for training using the usual noncommissioned officer unit selection process. Because of the multiple threats to internal validity, the technology was randomized to three of the six classes, not to the individual combat medics. Because program certification standards mandated that the EMT-B curriculum could not be altered without registry approval, training simulators were integrated into the skills practice sessions, becoming one of the skills stations through which combat medics rotated. Twenty-five laptop computers with headphones were set up in a private room. Initial instruction was given in how to navigate the.software, access the three modes of instruction, obtain feedback, and treat the simulated casualties. The number of times each combat medic accessed the simulator, the time spent in each episode, selected demographic data, learning style preferences, satisfaction with the technology, and NREMT examination scores were collected.

Approval was obtained from the institutional review board to conduct the study. Special procedures were implemented to address concerns regarding coercion. Combat medics were recruited as a class with an initial informational briefing performed by the study's civilian research program director, without uniformed military personnel or faculty presence. All questions were answered during the briefing, and combat medics who volunteered were asked to witness signatures of other combat medic volunteers.

Subjects

Of the 260 medics scheduled for classes, 223 volunteered for the study; 16 withdrew, 32 represented academic or nonacademic drops from the program, 16 did not take the NREMT examination, and results for 6 combat medics were not obtained (N = 167). As a result, the study had an attrition rate of 25%. Operation Iraqi Freedom occurred during data collection and accounted for the majority of the nonacademic drops.

The average combat medic's age was 27 years (SD, 6.38 years). Seventy-six percent were male. Ethnicity represented the general population of the United States, with a slightly lower Hispanic percentage. Eighty-eight percent of the combat medics were in the rank of E5 or below. In terms of highest education level, 74% had an initial education of a high school diploma or its equivalent, 17% an associate's degree, 8% a bachelor's degree, and 1% a master's degree. Most of the combat medics (59%) were assigned to nonmedical units, having an average of 9.75 h/wk (SD, 15 h/wk) during which they described their work as directly touching a patient. On average, they had been combat medics for 5 years (SD, 4.21 years).

Results

No significant differences in test scores (t = 1.019, df = 153, p = 0.745, one-tailed) or in pass rates (χ^sup 2^ = 1.575, df = 1, p = 0.209) were found between the combat medics who were exposed to the training simulators and those who were not. In addition, there was no relationship between dropout status and group status. Consequently, the cost-benefit relationship for the training simulators could not be established. Nevertheless, the data collected were used to understand the combat medic characteristics most closely related to the NREMT examination scores and the probability of passing the NREMT examination.