Injury and Illness Casualty Distributions Among U.S. Army and Marine Corps Personnel during Operation Iraqi Freedom

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1 Injury and Illness Casualty Distributions Among U.S. and Personnel during Operation Iraqi Freedom J. M. Zouris A. L. Wade C. P. Magno Naval Health Research Center Report -. Approved for public release: distribution is unlimited. Naval Health Research Center Sylvester Road San Diego, California 6

2 MILITARY MEDICINE, 3, 3:, Injury and Illness Casualty Distributions among U.S. and Personnel during Operation Iraqi Freedom James M. Zouris, BS*; Amber L Wade, MPIHt; Cheryl P. Magno, MPHf ABSTRACT The objective of this study was to evaluate the distributions of U.S. and wounded In action (WIA) and disease and nonbattle injury (DNBI) casualties dudng Operation Iraqi Freedom Major Combat Phase (OIF-) and Support and Stability Phase (OIF-). A retrospective review of hospitalization data was conducted. X^ tests were used to assess the Primary International Classification of Diseases, th Revision (ICD-), diagnostic category distributions by phase of operation, casualty type, and gender. Of the, casualties identified for analysis, 3,63 were WIA and, were DNBI. Overall, the proportion of WTA was higher during OIF- (36.6) than OTF- (3.6). Marines had a higher proportion of WIA and nonbattle injuries than soldiers. Although overall DNBI distributions for men and women were statistically different, their distributions of types of nonbattle injuries were similar. Identifying differences in injury and illness distributions by characteristics of the casualty population is necessary for military medical readiness planning. INTRODUCTION Examining and understanding the distribution of combat casualty illnesses and injuries is essential to improving military medical planning. Reliable estimates of casualties and threats to the Health Service Support (HSS) system, such as mass casualty situations, are necessary to forecast medical resource requirements for military operations. Casualty estimates consist of absolute numbers, surges in casualty admissions, evacuation patterns, and the distribution of types of injuries and illnesses. Hospitalization estimates and other support requirements are derived from these data and are then incorporated into HSS planning tools, such as the Medical Analysis Tool (MAT),' Estimating Supplies Program,^ and Tactical Medical Logistics Planning Tool.^ MAT is a joint medical resource planning tool that provides theater-wide medical and clinical decision support during planning, programming, and deployment. MAT also provides medical planners with the level and scope of medical support needed for a joint operation, and the capability of evaluating probable courses of action for a variety of scenarios. The Estimating Supplies Program and the Tactical Medical Logistics Planning Tool are the planning tools used by the Marines and Navy to estimate and configure the autho- *Naval Health Research Center, Catalina Boulevard, San Diego, CA 6-. tscience Applications International Corporation, Inc., 6 Campus Point Drive, San Diego, CA. tsan Diego State University Research Foundation, Campanile Drive, San Diego, CA. The views expressed in this article are those of the authors and do not reflect the official policy or position of the Navy, Department of Defense nor the LJ.S. government. Approved for public release; distribution is unlimited. This research has been conducted in compliance with all applicable federal regulations governing the protection of human subjects. No human subjects were directly involved in this research. This manuscript was received for review in February. The revised manuscript was accepted for publication in November. rized medical allowance lists, provide overall medical system analysis, and assist in risk assessment and capability-based planning. The purpose of the present study was to describe the distribution of evacuated wounded in action (WIA) and disease and nonbattle injury (DNBI) casualties sustained during the Major Combat Phase (OIF-) and the Support and Stability Phase (OIF-) of Operation Iraqi Freedom (OIF) involving the U.S. and Marines. This study uses data from the TRANSCOM Regulating and Command and Control Evacuation System (TRACES) and the Joint Patient Tracking Application (JPTA). TRACES is a World Wide Web-based system that provides documentation on patient regulation and movement for all branches of the U.S. Armed Forces in the theater of operations. The JPTA is a World Wide Web-based patient tracking and management tool that collects, manages, analyzes, and reports data on patient transfers, and provides information about transportation, treatment, and disposition of patients from Operations Iraqi and Enduring Freedom. The data from the JPTA became available after January. Both systems are part of the Theater Medical Information Program Joint (TMIP-J).'' TMIP-J is a family of systems designed to aid deployed medical personnel in all levels of care in theater, including complete clinical care documentation, medical supply and equipment tracking, patient movement visibility, and health surveillance. METHODS A retrospective review of hospitalization ICD- (Primary International Classification of Diseases, th Revision) data from OIF was performed. Data from OIF- (March -April 3, 3) were obtained from TRACES. Data from OIF- (March, -April 3, ) were obtained from JPTA.^ Primary ICD-'' diagnoses, gender, and service were extracted from the respective databases for each patient. Casu- MILITARY MEDICINE, Vol. 3, March

3 alties were categorized as WIA or DNBI and were assigned to an ICD- diagnostic category (or injury subcategory) based on their primary diagnosis on admission. Since the majority of WIA and nonbattle injury causalities were from the injury and poisoning category (ICD- codes -), these diagnoses were classified into the injury and poisoning subcategories (i.e., fractures (-), dislocations (3-3), sprains and strains (-), bums (-), intracranial injury (-), open wounds (-)) based on the casualty trauma description. In addition, "amputations" were included as a unique category to parallel previous studies that examined injury distributions.^"' Furthermore, two ICD- disease categoiies, "tiervous system" and "tnusculoskeletal," were added to the injury distribution to capture: () injuries coded as disease in ICD- (e.g., ICD- code 3., acoustic trauma (explosive) to ear); () injuries miscoded as diseases (e.g., injuries to the eye); and (3) future conditions resulting from injury (e.g., a Marine whose back was injured in combat and continues to seek medical care for back pain). Excluding these situations would eliminate a significant portion of injury-related causalities. WIA casualties were defined as active duty military personnel who were injured during hostile action and required hospitalization. Casualties who were killed in action (i.e., died as a result of hostile action before reaching a medical treatment facility), died of wounds (i.e., died as a result of wounds received during hostile action after reaching a medical treatment facility), or returned to duty were excluded from analysis. Subcategories within the injury ICD- category (e.g., fractures, amputations) were used to compare WIA casualties. DNBI casualties were defined as active duty military personnel who required hospitalization due to disease or injury unrelated to a hostile event. DNBI casualties were compared across ICD- diagnostic groups. X^ tests of independence were used to compare the diagnostic distributions (using the ICD- diagnostic categories) of WIA and DNBI casualties by phase of operation, branch of service, and gender. Statistical analyses were performed using SPSS software version.. (SPSS Inc., Chicago, Illinois); tests were two-tailed and p < was used to determine statistical significance. Adjusted standardized residuals were used to identify cells that had the greatest impact on the ;^ statistic. Critical values for standardized residuals were ±.. RESULTS Of the, casualties identitied for analysis,,36 (.) were from OIF- and,3 (.) were from OIF-. As shown in Table I, the majority of casualties were DNBI (.), were personnel (3.), and were male (). Phase of Operation The overall injury distributions among WIA casualties from OIF- were statistically diiferent from that of OIF- (x'- = 6., df =, p < ). There were a higher proportion of WIA casualties during OIF- than OIF- (36.6 vs. 3.6). TABLE I. Characteristics of U.S. Marine and Soldier Casualties during OIF- and OIF- Characteristic Casualty type DNBI WIA Branch of service Gender Male Female TABLE II. Injury Category Amputations Bums Dislocations Fractures tntracranial Nervous system** Sprains/strains Open wounds' Other 6 3,,36 OIF OIF-,,6,,,,, , 3,63,,,66,3, Distribution of WIA Casualties by Injury Category during OIF- and " ' ' 3' ' OIF ' 63 3" ' * 6," 3,6 OIF " f = 6., df=, p< ]. "Adjusted standardized residual was less than.. ' Adjusted standardized residual was more than --.. '' Hearing and visual impairment. ' Excludes amputations ,3 3, '. As indicated by the adjusted standardized residuals (see Table II), sprains and strains, open wounds, and dislocations were significantly higher dudng OIF-, whereas burns, fractures, and traumatic amputations were higher during OIF-^ As demonstrated in Table III, ICD- category distributions for DNBI casualties also dilfered significantly by phase of operation (x^ =.6, df = 6, p < ). Injuries and mental disorders were notably higher during OIF-. During OIF-, infectious and parasitic diseases and diseases of the musculoskeletal, digestive, and nervous systems were more common. Branch of Service Marines sustained proportionally more WIA injuries than personnel during OIF- ( vs..) and OIF- (. vs..). In addition, distributions of injury categories among WIA casualties diifered significantly between and Marines during OIF- (x^ =, df =,p < ) and during OIF- (x^ =., df ^, p < ) (Table IV). MILITARY MEDICINE, Vol. 3, March

4 TABLE III. Distribution of DNBI Casualties by ICD- Diagnostic Category during OIF- and OIF- ICD- Category Infectious Neoplasms Endocrine Blood Mental disorders Circulatory Respiratory Digestive Genitourinary Pregnancy Skin Congenital Ill-defined Injury Supplementary * 66' 3' " ' ' 6 33' 6 OIF-I ' 6 * 6',' 63 3',6',', OlF 'X^ =.6, J/ = 6,/ <. ' Adjusted standardized residual was less than.. ' Adjusted standardized residual was more than , 6,,33,36 3, The distributions of DNBI ICD- categories by service atid phase of operatioti are shown in Table V. Marines had the highest proportions of nonbattle injuries during OIF- and OIF-, and the lowest proportions of ill-defined conditions, mental disorders, and diseases of the musculoskeletal system. However, x^ tests were not performed on the DNBI distributions by phase and service due to the lack of cell counts in several of the ICD- categories. Gender Disease and nonbattle injury ICD- casualty distributions also differed by gender (;^ =, df =, p < ) (Table VI). The proportion of nonbattle injuries was significantly higher among men than women (. vs. 6.). However, among the ICD- major categories, neoplasms, mental disorders, diseases of the blood and blood-forming organs, respiratory, and genitourinary systems were more common among women than men. As shown in Table VII, the gender distributions within each phase were consistent with the overall findings for gender. Although male and female DNBI distributions were different, similar trends existed among them. Restricting our analysis to just the ICD- injury and poisoning group demonstrated that the distributions of nonbattle injuries among men and women were similar (x^ =.6, df= 6, p =.) (Table VIII). DISCUSSION This study evaluated the diagnostic distributions of WIA and DNBI casualties from the Major Combat and Support and Stability Phases of OIF obtained from the reporting tools of the TMIP-J program. As in previous military operations, DNBI casualties were much more prevalent than WIA casualties overall.'" However, during both phases of OIF, Marines sustained a significantly higher proportion of WIA casualties than the ; approximately one in two Marine casualties was WIA compared with only one in five casualties. This difference may be attributed to the distinct doctrinal missions and capabilities of the Marines Corps and the. The discrepancy in wounding patterns among battle casualties in the present analysis more traumatic amputations, fractures, and bums during OIF- is likely the result of changing weaponry preferences of the enemy. During OIF-, improvised explosive devices emerged as the primary mechanism of injury among WIA casualties." In previous conflicts, including OIF-, however, injuries due to small arms weapons were more common., TABLE IV. Distribution of U.S. and WIA Casualties by Injury Category during OIF- and OIF- OIF^-l» OIF-' Injury Category Amputations Burns Dislocations Fractures Intracranial Sprains/strains Open wounds Other " " 36' ' ' " ' ' 6 ' 6 3', " " 3 3 " " 'X^ =, d/=,p<. 'X^ =., df=,p <. 'Adjusted standardized residual was more than +.. "Adjusted standardized residual was less than.. MILITARY MEDICINE, Vol. 3, March

5 TABLE V. Distribution of DNBI Casualties by ICD- Diagtiostic Category and Branch of Service during OIF- and OIF- OIF-I OIF- ICD- Category Infectious Neoplasms Endocrine Blood Mental disorders Circulatory Respiratory Digestive Genitourinary Pregnancy Skin Congenital Ill-defined Injury Supplementary ,6 3,6, tests were excluded due to insufficient cell counts. TABLE VI. Distribution of DNBI Casualties by Gender and ICD- Diagnostic Category during OIF" ICD- Category Infectious Neoplasms Endocrine Blood Mental disorders Circulatory Respiratory Digestive Genitourinary Skin Congenital defined Injury Supplementary " lm"- lo-^ ' 36 ' 3"^ ' 333-^ 3, ",'' '-, Men IF 3' 3 ' 6* 3c ' "^ ' 3 6' 6^ 3', Women , 3,,33,36 3, ICD- diagnoses associated with childbirth, diseases of the male genital organs, inflammatory disease of female pelvic organs, and other disorders of the female genital tract were excluded. "X^ =, df= \,p <. ' Adjusted standardized residual was more than +.. "Adjusted standardized residual was less than.. DNBI distributions also differed between the phases of OIF. The initial, intense combat experience, as well as the constant movement of convoys, may have contributed to the higher proportion of mental disorders and nonbattle injuries during OIF-. However, diseases of the musculoskeletal system, such as injuries due to overuse and chronic pain, were expectedly more prevalent during OIF-. In fact, musculoskeletal problems accounted for one in five DNBI hospitalizations during this time period. Although this analysis provides important information regarding operational, gender, and service-specific differences in injury and illness distributions, there are limitations. Only hospitalization data were represented in this study, which include casualties who required medical care at a level III treatment facility due to more serious injury or illness. As such, these data may not refiect distributions of sick call or surveillance reporting systems from forward-deployed medical treatment facilities. The reporting tools used in this study (i.e., TRACES and JPTA) are primarily used for tracking casualties and do not provide a denominator or population at risk. Furthermore, the reliability and validity of the diagnostic methodology and characteristics of medical providers in theater is unknown, and determining the accuracy of the ICD- data was outside the scope of this study. However, as the only diagnostic information provided by these reporting tools, ICD- data may serve as the best proxy measure to incorporate into current and future HSS modeling and simulation applications. Despite these limitations, the findings demonstrate that casualty medical care resource planners should evaluate the differences in ICD- distributions for both WIA and DNBI casualties by operational phase, branch of service, and gender. Furthermore, methodologies that estimate scenario-specific patient streams should be modified to account for these distinctions to eliminate medical resource shortfalls such as the number of beds needed or the proper mix of medical specialists to treat the casualties. Together MILITARY MEDICINE, Vol. 3, March

6 TABLE VII. Distribution of DNBI Casualties by Gender and ICD- Diagnostic Category during OIF- and OIF- OIF- OIF- Men Women Men Women ICD- Category Infectious Neoplasms Endocrine Blood Mental disorders Circulatory Respiratory Digestive Genitourinary Pregnancy Skin Congenital Ill-defined Injury Supplementary , 6,, , Note: y tests were excluded due to insufficient cell counts. TABLE VIM. Nonbattle Injury Category Burns Dislocations Fractures Heat Sprains/strains Open wounds Other Distribution of Nonbattle Injuries among DNBI Casualties by Gender during OIF" 3 6 3, Men =.6, df= 6,p = Women , with the estimated counts of casualties, patient streams are the impetus of projecting the resources needed to sustain the HSS. Future research should compare various command elements, which will provide more insight on the differences between ICD- category distributions. Future studies should also attempt to examine the accuracy of the ICD- data from TRACES and JPTA by comparing it with data collected and coded by registries such as the Navy- Combat Trauma Registry.'* The Navy- Combat Trauma Registry, although primarily consisting of Marine casualties and including only patients initially treated at level I and II Navy- facilities, uses professional nurse coders to code injuries and illnesses which allows for the identification of possible systematic biases and assessments of reliability and validity. Diagnostic reporting procedures and guidelines may need to be adopted by TMIP-J to address these issues in their reporting tools. More work is needed to identify wounding patterns associated with specific causative agents and to identify the populations at risk, which are necessary for calculating incidence and prevalence of the disease or injury entities. ACKNOWLEDGMENTS Report - was supported by the Office of Naval Research, Arlington, VA, and the Warfighting Laboratory under Work Unit 636N.M.6,. REFERENCES. Medical Analysis Tool, version.. Technical Reference Manual. McLean, VA, Booz Allen & Hamilton, Inc.,.. Tropeano A: Estimating Supplies Program. Technical Document -D. San Diego, CA, Naval Health Research Center,. 3. Tropeano A, Konoske P, Galarneau M, Mitchell R, Brock J: The Development of the Tactical Medical Logistics Planning Tool (TML+). Technical Document 3-3C. San Diego, CA, Naval Health Research Center, 3.. The Military Health System. Washington, DC, The Pentagon. Available at accessed May,.. Fravell M: Force Health Protection Review: Keeping Track of Injured and Service Members Is All about the Details. Military Medical Technology Online Archives, Vol (),. Available at accessed July, World Health Organization: International Classification of Diseases, th Revision. Geneva, Switzerland, WHO,.. Palinkas LA, Coben P: Combat Casualties among U.S. Personnel in Vietnam: 6-. Technical Report -. San Diego, CA, Naval Health Research Center,. Reister FA: Medical Stadstics in World War II, p. Washington, DC, Department of the, Office of the Surgeon General,. MILITARY MEDICINE, Vol. 3, March

7 . Reister FA: Battle Casualties and Medical Statistics: U.S. Experience in the Korean War, Chap 3. Washington, DC, Department of the, OfBce of the Surgeon General, 3.. Palinkas LA, Coben P: Disease and non-battle injuries among U.S. Marines in Vietnam. Milit Med ; 3: -.. Gondusky JS, Reiter MP: Protecting military convoys in Iraq: an examination of battle injuries sustained by a mechanized battalion during Operation Iraqi Freedom II. Milit Med ; : 6-.. Mabry RL, Holcomb JB, Baker AM, et al: United States Rangers in Somalia: an analysis of combat casualties on an urban battlefield. J Trauma ; : -.. Zouris JM, Walker GJ, Dye J, Galameau M: Wounding patterns of U.S. Marines and Sailors during Operation Iraqi Freedom, major combat phase. Milit Med 6; : 6-.. Galameau MR, Hancock W, Konoske P, et al: U.S. Navy-. combat trauma registry. Milit Med 6; : 6-. MILITARY MEDICINE, Vol. 3, March

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9 REPORT DOCUMENTATION PAGE The public reporting burden for this collection of information is estimated to average hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, Jefferson Davis Highway, Suite, Arlington, VA -3, Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB Control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS.. Report Date (DD MM YY) Report Type Journal publication. TITLE AND SUBTITLE Injury and Illness Casualty Distributions Amopng US and Peronnel during Operation Iraqi Freedom 6. AUTHORS James M. Zouris, Amber L. Wade, Cheryl P. Magno. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Health Research Center P.O. Box San Diego, CA 6-. SPONSORING/MONITORING AGENCY NAMES(S) AND ADDRESS(ES) Commanding Officer Commander Naval Medical Research Center Navy Medical Support Command 3 Robert Grant Ave P.O. Box Silver Spring, MD - Jacksonville, FL DATES COVERED (from - to) July 6 - Nov 6 a. Contract Number: b. Grant Number: c. Program Element: d. Project Number: e. Task Number: f. Work Unit Number: 6. PERFORMING ORGANIZATION REPORT NUMBER Report -. Sponsor/Monitor's Acronyms(s) NMRC/NMSC. Sponsor/Monitor's Report Number(s) DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution is unlimited.. SUPPLEMENTARY NOTES Published in: Military Medicine,, 3(3), -. ABSTRACT (maximum words) The objective of this study was to evaluate the distributions of wounded in action (WIA) and disease and nonbattle injury (DNBI) casualties during the Operation Iraqi Freedom Major Combat Phase (OIF-) and the Support and Stability Phase (OIF-). A retrospective review of hospitalization records was conducted. Chi-square tests were used to assess the distributions of casualties by phase of operation, casualty type, branch of service, gender, and ICD- diagnostic category. Of the, casualties identified for analysis, 3,36 were WIA and,63 were DNBI. Overall, the proportion of WIA was higher during OIF- (3.) than OIF- (.). U.S. Marines had a higher proportion of WIA and nonbattle injuries than all other services. Although overall DNBI distributions for men and women were statistically different, their distributions of types of nonbattle injuries were similar. Identifying differences in injury and illness distributions by characteristics of the casualty population is necessary for military medical readiness planning.. SUBJECT TERMS Operation Iraqi Freedom, wounded in action, disease and nonbattle injury 6. SECURITY CLASSIFICATION OF:. LIMITATION. NUMBER a. NAME OF RESPONSIBLE PERSON a. REPORT b.abstract b. THIS PAGE OF ABSTRACT OF PAGES Commanding Officer UNCL UNCL UNCL UNCL b. TELEPHONE NUMBER (INCLUDING AREA CODE) COMM/DSN: (6) 3- Standard Form (Rev. -) Prescribed by ANSI Std. Z3-