Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment

Transcription

1 MILITARY MEDICINE, 174, 2:109, 2009 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment LTC Robert von Tersch, USA MS * ; Harry Birch, MS ; COL Raj Gupta, USA MS (Ret.) ; COL C. F. Tyner, USA MC (Ret.) ABSTRACT Military personnel deployed to Iraq and Afghanistan witnessed decreased numbers of soldiers killed in action and increased numbers of soldiers wounded in action. Medical personnel attribute these changes to use of improved body armor, rapid evacuation to medical treatment facilities, and use of medical technology. In recent years, medical technologist performed extensive research to identify and develop better field tourniquets and bandages to support wounded soldiers. Determining the benefit of these technologies to save a wounded soldier s life poses numerous challenges for medical personnel and commanders tasked to determine these benefits and make buy or no-buy decisions. This study uses modeling and simulation (M&S) to produce combat casualties, incorporate the projected benefits of field tourniquets and bandages, and examine their effects on wounded soldiers in a realistic simulated combat setting. The results show the positive benefit of using M&S to support analysis of medical technology and to inform medical research decisions. INTRODUCTION This paper is one example of the work being accomplished to examine changes in technology, systems, and force structure. Currently, Training and Doctrine Command (TRADOC) and the Army Medical Department (AMEDD) Center for AMEDD Strategic Studies (CASS) use modeling and simulation (M&S) to support decision making. Hence, the authors decided to use M&S to determine its usefulness as a means to evaluate the impact of proposed medical technology for a future force. Specifically, the authors used M&S to analyze wounded soldiers, combat medics (CMs), and medical technology in simulated combat. By using the capabilities of the M&S tool to incorporate the benefits of the medical technology, the authors had the means to examine the impact that these selected technologies could have on prolonging the life of wounded soldiers in a simulated combat setting. This research was undertaken to study the following issues: The impact of the one-handed tourniquet, smart tourniquet, and hemostatic dressing on wounded soldiers in terms of prolonging life. The impact these technologies had on medical personnel in terms of reducing time to treat. * JRO-CBRN Defense, Joint Staff, Pentagon, Washington, DC SAIC, Odyssey Dr. NW, Huntsville, AL Strategic Analysis, 4075 Wilson Blvd., Suite 200, Arlington, VA The Field School, 2301 Foxhall Rd. NW, Washington, DC The opinions or assertions contained herein are the private views of the authors and are not to be construed as official or as reflecting true views of the Department of the Army or the Department of Defense. This manuscript was received for review in April The revised manuscript was accepted for publication in October The impact that these technologies could have on other areas of medical support, such as surgical units. MATERIALS AND METHODS The authors leveraged previous work by the TRADOC Future Warfare Division and the AMEDD CASS where a common scenario and a government-owned M&S tool were used to support the early analysis of the Army s future force. Scenario The scenario used for this early analysis was developed and approved by warfighters from TRADOC. The scenario included 317 friendly blue soldiers and 942 enemy red soldiers engaged in combat operations, which resulted in casualties. Modeling and Simulation Tool The M&S tool used, Interactive Distributed Engineering, Evaluation, and Analysis Simulation (IDEEAS), was developed by computer scientists and engineers from Quality Research, now part of SAIC, Inc., and is owned and operated by U.S. Army Aviation and Missile Research Development and Engineering Command for various studies. IDEEAS is a constructive modeling simulation tool that runs under both Windows and LINUX. It is coded in JAVA and uses Monte Carlo techniques to determine outcome. Each IDEEAS run is identical with the exception of having a different run seed selected by a random number generator. Thirty runsets are optimal; however, fewer can be performed if the parameters are well defined. IDEEAS is verified, validated, and accredited for supporting studies and analyses of combat operations and provides the means to model wounded soldiers, medical technologies, battlefield conditions, and time and distance factors. 1 MILITARY MEDICINE, Vol. 174, February

2 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment TABLE I. Tourniquet Applicable PC Codes PC Code Prob of Injury % Medical Parameters Time to Treat (min) Prob of Death (%) Time to Death Before Treatment (min) Priority of Treatment Assigning Deployable Medical System Patient Condition Codes to Blue Casualties The Deployable Medical System (DEPMEDS) Patient Condition (PC) codes are a listing of 350 injury types, such as those that occur during combat operations, ranging from snake bites (PC 335) to hearing impairments (PC 23), to more serious injuries. 2 For this study, 184 possible PC codes were selected by medical subject matter experts (SMEs) as a basis for determining wounded soldiers injury types. A subset is listed in Table I. To randomly select a PC code from 184 possibilities for each simulated injury event, the probability of occurrence of each PC code was converted by modelers to a cumulative probability whose maximum value is 1.0. The default cumulative distribution is shown in Figure 1. The random selection of a particular PC code is done by drawing a random number from a uniform distribution Ambulatory Probability (%) Description Wound upper arm open penetrating lacerated without fracture severe, with nerve and/or vascular injury Wound upper arm open with fractures and nerve and vascular injury arm nonsalvageable Wound upper arm open with fractures and nerve injury no vascular injury arm salvageable Crush injury upper extremity severe, limb not salvageable Crush injury upper extremity moderate, limb salvageable Amputation hand traumatic complete all cases Amputation forearm traumatic complete all cases Amputation full arm traumatic complete all cases Wound thigh open lacerated penetrating perforating with fracture and nerve/vascular injury limb not salvageable Wound thigh open lacerated penetrating perforating with fracture and nerve and/or vascular injury limb salvageable Wound lower leg open lacerated penetrating perforating with fracture and nerve/vascular injury limb not salvageable Wound ankle foot toes open penetrating perforating with fractures and nerve/vascular injury limb not salvageable Amputation foot traumatic complete all cases Amputation below knee traumatic complete all cases Amputation traumatic complete requiring hip disarticulation Amputation above knee traumatic complete Miw brain and lower limbs requiring bilateral above knee amputations Miw chest with pneumohemothorax and limbs with fracture and vascular injury Miw abdomen pelvis limbs without fracture or neurovascular injury and penetrating perforating wound bladder bounded by 0 and 1 and then selecting the PC code on the basis of the curve in Figure 1. All soldiers wounded in action (WIA) were individually assigned a DEPMEDS PC code on the basis of a uniformly random draw from the list of 184 possibilities. This data set constitutes the default model input for basic CM treatment of casualties. On the basis of the PC Code, the WIA was also assigned a probability of death ( P d ). When the P d was >0, the WIA was assigned an initial time to death from the P d and the no-treatment curve shown in Figure 2. Figure 2 is hypothetical data generated by the SME, Wally Walters, and other medical SMEs during a study titled Combat Health Support for the Objective Force. Casualty Time to Treat Profiles On the basis of a review of treatment briefs for each DEPMEDS PC, a P d was assigned. As is evident from Figure 2, all 110 MILITARY MEDICINE, Vol. 174, February 2009

3 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment Cumulative Probability Distribution for Default Input Probability of Occurrence. FIGURE 2. Time to Death Algorithm. casualties with a nonzero Pd will die at the point of injury without the start of treatment by a CM within 1 hour of injury. Care received at that level automatically puts the patient on a different time to death curve. The reduction in mortality is proportional to the capability at each echelon of care.3 Blue Medical Support Entities Blue medical support entities developed within the M&S tool included the CM and the future combat system evacuation (FCS-E) vehicle. For this study, the M&S tool models CM care MILITARY MEDICINE, Vol. 174, February 2009 only. CM care includes basic treatment, loading of casualties on the medical evacuation vehicle, and transportation to the next level of care. For the evaluation of the new technologies, buddy aid and self-treatment capabilities were added. Buddy aid is defined as crew member aid provided to the casualty starting at the time and point of initial injury. Self-treatment is defined as the casualty having the ability to assist in treatment of his/her injury at the time and point of initial injury. Buddy aid and self-treatment assumes that medical supplies are carried aboard the combat vehicle and are not destroyed when the vehicle is hit. 111 FIGURE 1.

4 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment Medical Echelons of Care There are five echelons, or levels, of care defined in the reference, each progressively more advanced. 4 Echelon I care, provided in this study, provides immediate first aid at the front line. At this echelon, medical care encompasses self-aid, buddy aid, combat lifesaver, CMs, and a treatment squad. Combat Health Support Plan Only CM treatment is considered for this study. Following treatment, casualties are transported to the ambulance exchange point (AXP), and the medical evacuation team returns to continue treating and retrieving casualties or returns to a point behind the company to await orders to move to new sites of injury. Modeling Parameters and Algorithms Representative modeling parameters for IDEEAS have been published elsewhere and parameters for these studies can be provided upon request. Five examples of studies supported by IDEEAS include: 1. Joint aviation missile unmanned system (JAMUS) studies to assess rapid battle space deconfliction. 2. Close-in active protection system (CIAPS) study to assess CIAPS performance in a relevant battlefield and environment context. 3. On-the-move radar analysis to assess conceptual onthe-move radar operational missions in a tactically valid battlefield context study. 4. Extended area protection system (EAPS) study to evaluate candidate acquisition, fire control sensors, and shooter technologies in an operational context. 5. High-velocity outer tier defense missile (HOT-D) study to assess operational mission in a tactically valid battlefield context. Approach Three medical technologies were evaluated using M&S: One-handed tourniquet Smart tourniquet Chitosan bandage In addition, a time delay of 3 hours was incorporated to examine the capabilities of the M&S tool to model time delays as a means to further analyze the benefit of the medical technology. The time delay was a result of enemy activity and caused wounded soldiers to wait 3 hours or longer before the CM arrived and provided assistance for the application of the smart tourniquet (see below). Tourniquets There were 19 tourniquet-applicable PC codes selected. Two types of tourniquet were modeled in this study. One-Handed Tourniquet The application of the one-handed tourniquet requires no assistance. The wounded soldier can apply this tourniquet by himself/herself. The following points were considered in the modeling when using the one-handed tourniquet: 1. The casualty can apply the one-handed tourniquet alone via self-help. 2. The one-handed tourniquet is applied at the point of injury. 3. A litter is required to load the soldier onto the FCS-E. 4. The priority of treatment is echelon II. 5. The P d is 0 meaning that the patient did not die before receiving treatment at the AXP. 6. Time to treat is 1 minute. The clock starts at the time of injury. Smart Tourniquet The application of the smart tourniquet requires two uninjured people to apply. If there are not two uninjured personnel available, then the application must wait for the CMs to arrive. Therefore, the algorithm for tourniquet application is divided between two types of events: 1. At least two uninjured personnel are within the vicinity of the injured. In this study, a 100-meter radius was assumed. 2. The event in which there are not two uninjured personnel within the vicinity. The casualty is counted as one of the two available if he/ she is ambulatory. If not, then the casualty is not counted and two entirely different healthy personnel are required to apply the smart tourniquet. The second event described in the preceding paragraph requires the CMs for application of the smart tourniquet, so treatment cannot begin until the medical evacuation vehicle arrives. All medical input parameters remain the same, with the exception of time to treat. Also, following treatment by the CMs, the P d goes to zero. The following points were considered in the modeling when using the smart tourniquet: 1. The smart tourniquet requires two people to apply it: the casualty plus one additional person. 2. The smart tourniquet is applied at the point of injury, if at least one uninjured person is nearby. 3. A litter is required to load the soldier onto the FCS-E. 4. If no additional help is available, the smart tourniquet was not applied until the CMs arrived. 5. The P d is zero meaning that the patient did not die before treatment at the AXP. 6. Time to treat equals 9 minutes. The clock starts at time of injury, unless CM support is required. 7. Priority of treatment is echelon II. 112 MILITARY MEDICINE, Vol. 174, February 2009

5 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment Chitosan Bandage There were 34 chitosan bandage-applicable PC codes selected. The chitosan bandage PC codes and their medical input parameter values were selected by the authors on the basis of injury descriptions for each PC code and are not officially sanctioned by the medical community, because no data were available. This information is currently being observed and captured from cases treated during Operation Iraqi Freedom and Operation Enduring Freedom. The fact that the CM can apply the chitosan bandage was used during the modeling. Modified PC Code Discussion As previously discussed, there were 19 tourniquet and 34 chitosan bandage PC codes selected out of the 184 possible PC codes. If the probability of occurrence of all PC codes were equal, then the probability of selecting a tourniquet PC code would be 19/184 or 10.3% and the probability of selecting a chitosan bandage PC code would be 34/184 or 18.5%. However, the probability of occurrence of each PC code is not equal. In fact, as part of the provided code data a unique probability of injury is specified for each individual PC code. An example of this is shown in the second column in Table I. Consequently, when the probability of injury is factored in for each PC code, the probability of occurrence of a tourniquet PC code is actually 21% and the probability of occurrence of a chitosan bandage PC code is actually 11%. To parametrically evaluate and compare these different technologies, the selection of PC codes was modified to allow control of the probability of occurrence of the set of PC codes applicable to the particular technology. For the purpose of comparing the one-handed tourniquet, smart tourniquet, and chitosan bandage, the probability of occurrence of each was modeled to be 50%. This modification meant there was a 50% chance of an injury occurring that requires either a smart or one-handed tourniquet or a chitosan bandage. This modification increased the number of injuries needing tourniquets or chitosan bandages, meaning that their effects would have a significant statistical battlefield impact. Figure 3 illustrates the cumulative probability used for both tourniquet types, since the PC codes impacted by these two technologies are the same. The line labeled Baseline PC Codes is the same as that shown in Figure 1. The line labeled Tourniquet Applicable PC codes Only shows the cumulative distribution when only the tourniquet PC codes are considered. The line labeled Baseline with Tourniquet Applicable PC codes removed shows the cumulative distribution minus the tourniquet-applicable PC codes. Figure 4 illustrates the cumulative probability used for the chitosan bandage. The line labeled Baseline PC codes is the same as that shown in Figure 1. The lined labeled Chitosan Applicable PC codes Only shows the cumulative distribution when only the chitosan bandage PC codes are considered. The line labeled Baseline with Chitosan Applicable PC codes Removed shows the cumulative distribution minus the chitosan bandage-applicable PC codes. RESULTS AND ANALYSIS The damage categories of WIA, killed in action (KIA), and uninjured personnel at the initial time of weapon impact on the vehicle or dismounted are shown in Figure 5. The number of casualties expected to die immediately following weapon impact is shown in Figure 6 for the baseline CM treatment. These is the WIA that are expected to die (died of wounds [DOW]) based upon a P d > 0 or based upon the time-to-die clock winding down to zero ( Fig. 2 ). For the baseline CM treatment case all of the expected to die will die, given that no echelon I through echelon III treatment is performed starting at the AXP and becoming more FIGURE 3. Cumulative Probability Distribution with a 50% Occurrence of the One Handed or Smart Tourniquet Applicable PC codes. MILITARY MEDICINE, Vol. 174, February

6 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment Cumulative Probability Distribution with a 50% Occurrence of the Chitosan Bandage Applicable PC codes. FIGURE 5. Blue Force Damage Categories at Initial Weapon Impact. FIGURE 7. FIGURE 6. Total Number of Casualties Expected to Die (WIA to DOW). advanced. In the case of this study, echelons II and III are not modeled. The significantly larger number of those expected to die in the chitosan bandage portion of the graph is because the chitosan injuries are more serious and life threatening than those injuries applicable to the use of a tourniquet. 114 Treatment Completions Timeline. Figure 7 shows a comparison of the two tourniquet technologies to the baseline case. This chart shows the treatment completion time as a function of initial injury time. The chart is a scatterplot of all 10 runs in each runset. A straight line trend line was computed for each of the scatterplots to illustrate the difference in average time that the casualty treatment was completed. The purpose of this chart is to show the overall shorter timeline from self or buddy aid for the new technologies as a result of the shorter treatment time. The chart shows that treatment times for the two technologies were about 30 minutes shorter than the baseline. This is because results of the study showed that on average it took the CM 30 minutes to arrive to the wounded soldier from time of notification. There is no significant difference in the average treatment times between the smart tourniquet and the one-handed tourniquet. Figure 8 is a bar chart comparison of the WIA, those delivered to the AXP where additional care will occur, and those dying of wounds. The total number of DOW was reduced by about 1.5 casualties, when comparing the two technologies to the baseline. A reduction in the number of DOW before treatment was realized as well as a reduction in the number MILITARY MEDICINE, Vol. 174, February 2009 FIGURE 4.

7 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment FIGURE 8. FIGURE 9. Tourniquet. Comparisons of Smart and One Handed Tourniquet to Baseline When Considering Total Applicable Casualties. Expected to DOW and Actual DOW - One Handed of casualties not cleared from the battlefield. There is a slight reduction in DOW when comparing the one-handed tourniquet to the smart tourniquet. This slight reduction is a result of the requirement for self plus one uninjured person to apply the smart tourniquet. There were a few instances in which there was no one available to assist the casualty, so treatment did not occur until the CMs arrived. Analysis revealed that only 18% of the injuries can be treated with these two tourniquets and chitosan bandage. The overall effect is not as significant as it would be if a higher percentage of injuries were amenable to these technologies. Another important point is that only five of the PC codes have a probability of death >0, and of these five only two have an occurrence >0. Therefore, application of these two technologies in this scenario will not show a significant decrease in casualties dying of wounds; 7.2 and 7.5 DOW, respectively, compared to 8.7 DOW for the baseline. Expected to Die and Actual Deaths Figure 9 compares expected to die with the actual DOW for the one-handed tourniquet. The number expected to die is 13 out of 45 (28%). As can be seen when no treatment is provided or when only CMs are used, all that are expected to die will die. In the case of the baseline CM, combat medic treatment does not alter the fact that the casualty will die. The time to death changes because with treatment the casualty moves from the no treatment portion of the curve shown in Figure 2 to the CM treatment portion of the curve. This is true whether or not there is a delay before the CMs can start treating the casualties. The 3-hour delay and the with and without buddy aid/self-treatment show no change for the following reasons. The one-handed tourniquet is selftreatment. Self-treatment starts immediately following initial time of injury. It assumes that the casualty always has the capability to self-treat. Figure 10 shows expected to die and actual DOW for the smart tourniquet. As can be seen, the expected to die is the same as that of the one-handed tourniquet. However, actual DOW varies from the one-handed tourniquet as well as varying when there is a delay in treatment and with/ without buddy aid. This is because it requires two healthy or ambulatory personnel to apply the tourniquet. If the casualty is ambulatory, the casualty can assist a healthy soldier to apply the tourniquet. If the casualty is not ambulatory, then it takes two healthy soldiers. The healthy soldiers must be within 100 meters of the casualty to assist in the application of the tourniquet. In the case of the 3-hour delay in treatment, the actual DOW is the same with and without buddy aid. This implies, but was not confirmed by researching the output data (which was beyond the scope of the proof of principle effort), that in the instances when buddy aid was used, the casualty was in no danger of dying. Figure 11 shows expected to die and actual DOW for the chitosan bandage. As stated earlier, a greater number are expected to die when 50% of the PC codes are chitosan bandage-applicable as compared to tourniquet-applicable PC codes. However, the reduction in the number of actual deaths MILITARY MEDICINE, Vol. 174, February

8 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment FIGURE 10. Expected to DOW and Actual DOW - Smart Tourniquet. FIGURE 11. Expected to DOW and Actual DOW - Chitosan Bandage. is significantly reduced as can be seen in Figure 11. Also, shown in Figure 11, a slight increase in actual DOW occurs with a delay in treatment as well as when buddy aid is not available. However, the results are the same when comparing with and without buddy aid for a delay in treatment by CMs. Since this study was a proof of principle, the output data have not been researched to determine an explanation. Length of Time Tourniquets Have Been in Place Figures 12 and 13 are histograms of the length of time that the tourniquets have been in place for both the one-handed and the smart tourniquets, respectively. The significance of this information is that appendages will be lost if the tourniquets remain in place for extended periods of time. That critical length of time was not available when this document was generated, so the information is presented for information only and no conclusions will be drawn with regard to the loss of limbs. For both tourniquets, the length of time is generally <1 hour for the case in which no delay in treatment occurs. However, in the case of a 3-hour delay in treatment, the delays become significant. The times in this case are longer because the application of the tourniquet generally starts immediately following the time of initial injury. This is precisely true for the one-handed tourniquet, but is only generally true for the smart tourniquet since its application does not necessarily always take place immediately following the time of initial injury. 116 FIGURE 13. Length of Time Tourniquet is in Place One Handed Length of Time Tourniquet is in Place Smart Tourniquet. Chitosan Golden Hour Figure 14 presents the time of arrival of the medical evacuation vehicle at the injury site relative to the golden hour or arrival within 1 hour relative to the initial time of injury, presented in percentage of those vehicles arriving. As illustrated in the chart, when using buddy aid and no delay in movement of the medical evacuation vehicles to the injury sites, more than 80% of the arrivals occur within 1 hour. In the case of a 3-hour delay, there are no arrivals before the golden hour. In the no delay no buddy aid runsets, the number of medical evacuation arrivals before the end of the golden hour is just over 70%. The lower value compared to the 80% case is caused by the longer time to treat when no buddy aid takes place. The longer time to treat translates to later times of arrival at follow-on injury sites. SUMMARY AND CONCLUSION Summary Figure 15 shows the benefit of the two overall technologies (tourniquet and bandage) and shows the differences in the two tourniquet technologies for the best case scenario: buddy aid and no delay in treatment. The ordinate axis is the reduction in the number of casualties dying relative to their baseline cases. In the case of the tourniquets, the percentage improvements are for runsets 3 (one-handed) and 7 (smart) relative to the MILITARY MEDICINE, Vol. 174, February 2009 FIGURE 12. Tourniquet.

9 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment FIGURE 14. Chitosan Bandage - Medic Evac Arrival at the Injury Site Relative to the Golden Hour. Reduction in DOW - Smart Tourniquet. FIGURE 18. Reduction in DOW - Chitosan Bandage. Reduction in DOW when using Buddy Aid and No Delay Finally our analysis reveals that the medical technology presented in this article can save the lives of seriously wounded soldiers. These seriously wounded soldiers, who might otherwise expire, receive surgery to recover and, depending on the seriousness of the injury, return to duty. The increased surgical load would impact the level of medical resources and medical planning. However, analyzing medical and combat resourcing requirements for the battlefield is beyond the scope of this article and may be a topic for additional study. FIGURE 16. Reduction in DOW - One Handed Tourniquet. baseline case, runset 2. For the chitosan bandage, runset 13 is compared to the baseline case, runset 12. Figures 16 through 18 show the change in DOW for all permutations looked at in this study. All four runsets of the onehanded tourniquet shown in Figure 16 display the same level of reduction in DOW. This is an artifact of the ground rules for the one-handed tourniquet stating that each casualty requiring a tourniquet can apply the tourniquet. Use of the smart tourniquet shows some variation in the reduction, Figure 17, with the worst case showing 14%. The chitosan bandage also shows a variation in reduction, with the worst case being 63%, shown in Figure 18. MILITARY MEDICINE, Vol. 174, February 2009 Conclusion M&S tools capable of incorporating medial parameters and data combined with medical SMEs can provide the means for medical personnel to examine combat casualty care technologies applicable to battlefield settings. The results of this initial effort show how M&S can be used to support analysis of medical technology and to inform decisions on medical research. The authors are confident that, as the capabilities of M&S tools increase and as more field or civilian medical data become available, the M&S tools of the future can be used to support analysis and decisions in medical technology and research. However, this improvement can only be accomplished if medical personnel stay engaged with the M&S developers to ensure that medical entities, medical parameters, and data are incorporated accurately. 117 FIGURE 15. in Treatment. FIGURE 17.

10 Examining Technologies to Control Hemorrhage by Using Modeling and Simulation to Simulate Casualties and Treatment ACKNOWLEDGMENTS This work was supported by Research Plans and Programs, Medical Research and Materiel Command. REFERENCES 1. Ingram MC, Keeley TJ, Finken PJ : Objective Force Concept Explo ration: A Notional Combat Battalion Engagement. TRADOC Analysis Center, Report number TRAC-F-TD Fort Leavenworth, KS, August 15, Defense Medical Standardization Board : Deployable Medical System (DEPMEDS) PC codes. Available at 3. Hassell LH, Devore RB Jr, Lee A, Birch HK : Combat Health Support to the Objective Force, paper 03S-SIW-067, presented at the Simulation Interoperability Workshop (SIW), for Simulation Interoperability. 4. Headquarters Department of the Army : FM Medical Evacuation in a Theater of Operations: Tactics, Techniques, and Procedures, pp Washington DC, April 14, MILITARY MEDICINE, Vol. 174, February 2009