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Naval Health Research Center

Injury and Illness Casualty Distributions Among U.S. Army and

Marine Corps Personnel during Operation Iraqi Freedom

J. M. Zouris A. L. Wade

C. P. Magno

Report No. 07-01

. Approved for public release: distribution is unlimited.

Naval Health Research Center 140 Sylvester Road

San Diego, California 92106

MILITARY MEDICINE, 173, 3:247, 2008

Injury and Illness Casualty Distributions among U.S. Armyand Marine Corps 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. Marine Corps and Army woundedIn action (WIA) and disease and nonbattle injury (DNBI) casualties dudng Operation Iraqi Freedom Major CombatPhase (OIF-1) and Support and Stability Phase (OIF-2). A retrospective review of hospitalization data was conducted.X^ tests were used to assess the Primary International Classification of Diseases, 9th Revision (ICD-9), diagnosticcategory distributions by phase of operation, casualty type, and gender. Of the 13,071 casualties identified for analysis,3,263 were WIA and 9,808 were DNBI. Overall, the proportion of WTA was higher during OIF-1 (36.6%) than OTF-2(23.6%). Marines had a higher proportion of WIA and nonbattle injuries than soldiers. Although overall DNBIdistributions for men and women were statistically different, their distributions of types of nonbattle injuries weresimilar. Identifying differences in injury and illness distributions by characteristics of the casualty population isnecessary for military medical readiness planning.

INTRODUCTIONExamining and understanding the distribution of combat ca-sualty illnesses and injuries is essential to improving militarymedical planning. Reliable estimates of casualties and threatsto the Health Service Support (HSS) system, such as masscasualty situations, are necessary to forecast medical resourcerequirements for military operations. Casualty estimates con-sist of absolute numbers, surges in casualty admissions, evac-uation patterns, and the distribution of types of injuries andillnesses. Hospitalization estimates and other support require-ments are derived from these data and are then incorporatedinto HSS planning tools, such as the Medical Analysis Tool(MAT),' Estimating Supplies Program,^ and Tactical MedicalLogistics Planning Tool.^

MAT is a joint medical resource planning tool that pro-vides theater-wide medical and clinical decision support dur-ing planning, programming, and deployment. MAT also pro-vides medical planners with the level and scope of medicalsupport needed for a joint operation, and the capability ofevaluating probable courses of action for a variety of scenar-ios. The Estimating Supplies Program and the Tactical Med-ical Logistics Planning Tool are the planning tools used bythe Marines and Navy to estimate and configure the autho-

*Naval Health Research Center, 271 Catalina Boulevard, San Diego, CA92186-5122.

tScience Applications International Corporation, Inc., 10260 CampusPoint Drive, San Diego, CA 92121.

tSan Diego State University Research Foundation, 5250 CampanileDrive, San Diego, CA 92182.

The views expressed in this article are those of the authors and do notreflect the official policy or position of the Navy, Department of Defense northe LJ.S. government. Approved for public release; distribution is unlimited.This research has been conducted in compliance with all applicable federalregulations governing the protection of human subjects. No human subjectswere directly involved in this research.

This manuscript was received for review in February 2007. The revisedmanuscript was accepted for publication in November 2007.

rized medical allowance lists, provide overall medical systemanalysis, and assist in risk assessment and capability-basedplanning.

The purpose of the present study was to describe thedistribution of evacuated wounded in action (WIA) and dis-ease and nonbattle injury (DNBI) casualties sustained duringthe Major Combat Phase (OIF-1) and the Support and Sta-bility Phase (OIF-2) of Operation Iraqi Freedom (OIF) in-volving the U.S. Army and Marines.

This study uses data from the TRANSCOM Regulating andCommand and Control Evacuation System (TRAC2ES) and theJoint Patient Tracking Application (JPTA). TRAC2ES is aWorld Wide Web-based system that provides documentationon patient regulation and movement for all branches of theU.S. Armed Forces in the theater of operations. The JPTA isa World Wide Web-based patient tracking and managementtool that collects, manages, analyzes, and reports data onpatient transfers, and provides information about transporta-tion, treatment, and disposition of patients from OperationsIraqi and Enduring Freedom. The data from the JPTA becameavailable after January 2004.

Both systems are part of the Theater Medical InformationProgram—Joint (TMIP-J).'' TMIP-J is a family of systemsdesigned to aid deployed medical personnel in all levels ofcare in theater, including complete clinical care documenta-tion, medical supply and equipment tracking, patient move-ment visibility, and health surveillance.

METHODSA retrospective review of hospitalization ICD-9 (PrimaryInternational Classification of Diseases, 9th Revision) datafrom OIF was performed. Data from OIF-1 (March 21-April30, 2003) were obtained from TRAC2ES. Data from OIF-2(March 1, 2004-April 30, 2005) were obtained from JPTA.^

Primary ICD-9'' diagnoses, gender, and service were ex-tracted from the respective databases for each patient. Casu-

MILITARY MEDICINE, Vol. 173, March 2008 247

Army and Marine Corps Casualty Distributions during OIF

alties were categorized as WIA or DNBI and were assigned toan ICD-9 diagnostic category (or injury subcategory) basedon their primary diagnosis on admission. Since the majorityof WIA and nonbattle injury causalities were from the injuryand poisoning category (ICD-9 codes 800-999), these diag-noses were classified into the injury and poisoning subcate-gories (i.e., fractures (800-829), dislocations (830-839),sprains and strains (840-849), bums (840-849), intracranialinjury (850-854), open wounds (870-879)) based on thecasualty trauma description. In addition, "amputations" wereincluded as a unique category to parallel previous studies thatexamined injury distributions.^"' Furthermore, two ICD-9 dis-ease categoiies, "tiervous system" and "tnusculoskeletal," wereadded to the injury distribution to capture: (1) injuries coded asdisease in ICD-9 (e.g., ICD-9 code 388.11, acoustic trauma(explosive) to ear); (2) injuries miscoded as diseases (e.g.,injuries to the eye); and (3) future conditions resulting frominjury (e.g., a Marine whose back was injured in combat andcontinues to seek medical care for back pain). Excludingthese situations would eliminate a significant portion of in-jury-related causalities.

WIA casualties were defined as active duty military per-sonnel who were injured during hostile action and requiredhospitalization. Casualties who were killed in action (i.e.,died as a result of hostile action before reaching a medicaltreatment facility), died of wounds (i.e., died as a result ofwounds received during hostile action after reaching a med-ical treatment facility), or returned to duty were excludedfrom analysis. Subcategories within the injury ICD-9 cate-gory (e.g., fractures, amputations) were used to compare WIAcasualties. DNBI casualties were defined as active duty mil-itary personnel who required hospitalization due to disease orinjury unrelated to a hostile event. DNBI casualties werecompared across 17 ICD-9 diagnostic groups.

X^ tests of independence were used to compare the diag-nostic distributions (using the ICD-9 diagnostic categories) ofWIA and DNBI casualties by phase of operation, branch ofservice, and gender. Statistical analyses were performed usingSPSS software version 12.0.2 (SPSS Inc., Chicago, Illinois);tests were two-tailed and p < 0.05 was used to determinestatistical significance. Adjusted standardized residuals wereused to identify cells that had the greatest impact on the ;^statistic. Critical values for standardized residuals were ± 2.0.

RESULTSOf the 13,071 casualties identitied for analysis, 1,368 (10.5%)were from OIF-1 and 11,703 (89.5%) were from OIF-2. Asshown in Table I, the majority of casualties were DNBI (75.0%),were Army personnel (83.5%), and were male (90.0%).

Phase of OperationThe overall injury distributions among WIA casualties fromOIF-1 were statistically diiferent from that of OIF-2 (x'- =60.77, df = 9, p < 0.001). There were a higher proportion ofWIA casualties during OIF-1 than OIF-2 (36.6% vs. 23.6%).

TABLE I. Characteristics of U.S. Marine and SoldierCasualties during OIF-1 and OIF-2

Characteristic

Casualty typeDNBIWIA

Branch of serviceArmyMarine Corps

GenderMaleFemale

Total

OIF-1

No.

867501

915453

1,255113

1,368

%

63.436.6

66.933.1

91.78.3

100.0

OIF-2

No.

8,9412,762

9,9981,705

10,5111,192

11,703

%

76.423.6

85.414.6

89.810.2

100.0

Total

No.

9,8083,263

10,9132,158

11,7661,305

13,071

%

75.025.0

83.516.5

90.010.0

100.0

TABLE II. Distribution of WIA Casualties by Injury Categoryduring OIF-1 and

Injury Category

AmputationsBumsDislocationsFracturestntracranialNervous

system**Sprains/strainsMusculoskeletalOpen wounds'OtherTotal

OIF-1

No.

12"2011'

111'7

13

23'20

240'44

501

%

2.44.02.2

22.21.42.6

4.64.0

47.98.8

100.0

OIF-2

No.

132'16323"

845'7295

42*69

1,087"234

2,762

%

4.85.90.8

30.62.63.4

1.52.5

39.48.5

100.0

Total

No.

14418334

95679

108

6589

1,327278

3,263

%

4.45.61.0

29.32.43.3

2.02.7

40.7' 8.5100.0

" f = 60.77, df= 9, p< 0.00]."Adjusted standardized residual was less than —2.0.' Adjusted standardized residual was more than -1-2.0.'' Hearing and visual impairment.' Excludes amputations.

As indicated by the adjusted standardized residuals (see TableII), sprains and strains, open wounds, and dislocations weresignificantly higher dudng OIF-1, whereas burns, fractures,and traumatic amputations were higher during OIF-2^

As demonstrated in Table III, ICD-9 category distributionsfor DNBI casualties also dilFered significantly by phase ofoperation (x^ = 187.86, df = 16, p < 0.001). Injuries andmental disorders were notably higher during OIF-1. DuringOIF-2, infectious and parasitic diseases and diseases of themusculoskeletal, digestive, and nervous systems were morecommon.

Branch of ServiceMarines sustained proportionally more WIA injuries thanArmy personnel during OIF-1 (51.9% vs. 29.1%) and OIF-2(54.1% vs. 18.4%). In addition, distributions of injury cat-egories among WIA casualties diifered significantly be-tween Army and Marines during OIF-1 (x^ = 27.87, df =9,p < 0.01) and during OIF-2 (x^ = 27.28, df ^ 9, p <0.01) (Table IV).

248 MILITARY MEDICINE, Vol. 173, March 2008


TABLE III. Distribution of DNBI Casualties by ICD-9Diagnostic Category during OIF-1 and OIF-2°

ICD-9 Category

InfectiousNeoplasmsEndocrineBloodMental disordersNervous systemCirculatoryRespiratoryDigestiveGenitourinaryPregnancySkinMusculoskeletalCongenitalIll-definedInjurySupplementaryTotal

OIF-I

No.

7*7

102

66'38'323466"5213'2089'6

75338'

12867

%

0.91.51.30.27.94.34.03.77.15.81.52.3

10.80.89.2

37.41.4

100.0

OlF-2

No.

175'141165

13501*556'409250

1,005'563

38'251

1,716'51

9581,978'

1718,941

%

1.91.61.80.25.66.24.62.8

11.26.30.42.8

19.20.6

10.722.1

1.9100.0

Total

No.

18214817515

567594441284

1,071615

51271

1,80557

1,0332,316

1839,808

%

1.91.51.80.25.86.14.52.9

10.96.30.52.8

18.40.6

10.523.6

1.9100.0

'X^ = 187.86, J / = 16,/7 < 0.001.' Adjusted standardized residual was less than —2.0.' Adjusted standardized residual was more than -1-2.0.

The distributions of DNBI ICD-9 categories by serviceatid phase of operatioti are shown in Table V. Marines had thehighest proportions of nonbattle injuries during OIF-1 andOIF-2, 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 distribu-tions by phase and service due to the lack of cell counts inseveral of the ICD-9 categories.

GenderDisease and nonbattle injury ICD-9 casualty distributionsalso differed by gender (;^ = 201.90, df = 15, p < 0.001)

(Table VI). The proportion of nonbattle injuries was signifi-cantly higher among men than women (25.2% vs. 16.4%).However, among the ICD-9 major categories, neoplasms,mental disorders, diseases of the blood and blood-formingorgans, respiratory, and genitourinary systems were morecommon among women than men. As shown in Table VII,the gender distributions within each phase were consistentwith the overall findings for gender.

Although male and female DNBI distributions were dif-ferent, similar trends existed among them. Restricting ouranalysis to just the ICD-9 injury and poisoning group dem-onstrated that the distributions of nonbattle injuries amongmen and women were similar (x^ = 5.62, df= 6, p = 0.47)(Table VIII).

DISCUSSIONThis study evaluated the diagnostic distributions of WIA andDNBI casualties from the Major Combat and Support andStability Phases of OIF obtained from the reporting tools ofthe TMIP-J program. As in previous military operations,DNBI casualties were much more prevalent than WIA casualtiesoverall.'" However, during both phases of OIF, Marines sus-tained a significantly higher proportion of WIA casualties thanthe Army; approximately one in two Marine casualties was WIAcompared with only one in five Army casualties. This differencemay be attributed to the distinct doctrinal missions and capabil-ities of the Marines Corps and the Army.

The discrepancy in wounding patterns among battle casu-alties in the present analysis—more traumatic amputations,fractures, and bums during OIF-2—is likely the result ofchanging weaponry preferences of the enemy. During OIF-2,improvised explosive devices emerged as the primary mech-anism of injury among WIA casualties." In previous con-flicts, including OIF-1, however, injuries due to small armsweapons were more common.12,13

TABLE IV. Distribution of U.S. Army and Marine Corps WIA Casualties by Injury Category during OIF-1 and OIF-2

Injury Category

AmputationsBurnsDislocationsFracturesIntracranialNervous systemSprains/strainsMusculoskeletalOpen woundsOtherTotal

No.

4135

591"9

1412

113"36'

266

OIF

Army

%

1.54.91.9

22.20.43.45.34.5

42.513.5

100.0

^-l»

Marine

No.

876

526'498

127'8"

235

Corps

%

3.43.02.6

22.12.61.73.83.4

54.03.4

100.0

No.

99'121'

165404274'2647

701173'

1,839

OIF-2'

Army

%

5.46.60.9

29.42.34.01.42.6

38.19.4

100.0

Marine

No.

33"42"

7305

3021"1622

38661"

923

Corps

%

3.64.60.8

33.03.32.31.72.4

41.86.6

100.0

'X^ = 2 7 . 8 7 , d / = 9,p< 0 . 0 1 .'X^ = 21.2%, df= 9,p < 0 . 0 1 .'Adjusted standardized residual was more than +2.0."Adjusted standardized residual was less than —2.0.



TABLE V.

ICD-9 Category


Distribution

No.

6752

583124304139111376

563

22612

649

of DNBI Casualties by

OIF-I

Army

%

0.91.10.80.38.94.83.74.66.36.01.72.0

11.70.89.7

34.81.8

100.0

ICD-9 Diagtiostic Category

Marine Corps

No.

10508784

251327

131

12112

0218

%

0.50.02.30.03.73.23.71.8

• 11.56.00.93.26.00.55.5

51.40.0

100.0

and Branch of

Army

No.

162132155

13457496392237929527

37222

1,61948

8931,682

1588,159

Service during

OIF-2

%

2.01.61.90.25.66.14.82.9

11.46.50.52.7

19.80.6

10.920.6

1.9100.0

OIF-1 and

Marine

No.

139

100

446017137636

12997

365

29613

782

OIF-2

Corps

%

1.71.21.30.05.67.72.21.79.74.60.13.7

12.40.48.3

37.91.7

100.0

tests were excluded due to insufficient cell counts.

TABLE VI. Distribution of DNBI Casualties by Gender andICD-9 Diagnostic Category during OIF"

ICD-9 Category

Infectious

Neoplasms

Endocrine

Blood

Mental disorders

Nervous system

Circulatory

Respiratory

Digestive

Genitourinary

Skin

Musculoskeletal

Congenital

111 defined

Injury

Supplementary

Total

Men

No.

171"

lM"-

152lO-̂

471 '

536404 '

237"̂

997 '

333-^

2391,597

48877"

2,140''

148'-

8,474

%

2.01.41.80.25.76.34.82.8

11.6

3.92.8

18.8

0.510.5

25.2

1.7100.0

Women

No.

I F34'235'

96*5837c47'74"̂

1 0 1 '32

2089

156'176^35'

1,102

%

1.12.92.00.69.05.23.54.56.69.02.9

18.30.7

14.416.43.0

100.0

Total

No.

18214817515

567594441284

1,071434271

1,80557

1,0332,316

1839,576

%

1.91.51.80.25.96.24.63.0

11.24.52.8

18.80.6

10.824.2

1.7100.0

ICD-9 diagnoses associated with childbirth, diseases of the male genitalorgans, inflammatory disease of female pelvic organs, and other disordersof the female genital tract were excluded."X^ = 201.90, df= \5,p < 0.001.' Adjusted standardized residual was more than +2.0."Adjusted standardized residual was less than —2.0.

DNBI distributions also differed between the phases ofOIF. The initial, intense combat experience, as well as theconstant movement of convoys, may have contributed to thehigher proportion of mental disorders and nonbattle injuriesduring OIF-1. However, diseases of the musculoskeletal sys-tem, such as injuries due to overuse and chronic pain, were

expectedly more prevalent during OIF-2. In fact, musculo-skeletal problems accounted for one in five DNBI hospital-izations during this time period.

Although this analysis provides important information re-garding operational, gender, and service-specific differencesin injury and illness distributions, there are limitations. Onlyhospitalization data were represented in this study, whichinclude casualties who required medical care at a level IIItreatment facility due to more serious injury or illness. Assuch, these data may not refiect distributions of sick call orsurveillance reporting systems from forward-deployed med-ical treatment facilities. The reporting tools used in this study(i.e., TRAC2ES and JPTA) are primarily used for trackingcasualties and do not provide a denominator or population atrisk. Furthermore, the reliability and validity of the diagnosticmethodology and characteristics of medical providers in the-ater is unknown, and determining the accuracy of the ICD-9data was outside the scope of this study. However, as the onlydiagnostic information provided by these reporting tools,ICD-9 data may serve as the best proxy measure to incorpo-rate into current and future HSS modeling and simulationapplications.

Despite these limitations, the findings demonstrate thatcasualty medical care resource planners should evaluatethe differences in ICD-9 distributions for both WIA andDNBI casualties by operational phase, branch of service,and gender. Furthermore, methodologies that estimate sce-nario-specific patient streams should be modified to ac-count for these distinctions to eliminate medical resourceshortfalls such as the number of beds needed or the propermix of medical specialists to treat the casualties. Together



TABLE VII. Distribution of DNBI Casualties by Gender and ICD-9 Diagnostic Category during OIF-1 and OIF-2

ICD-9 Category


No.

7381

543330296440

020828

61312

8758

OIF-1

Men

%

0.90.41.10.17.14.44.03.88.45.30.02.6

10.80.88.0

41.21.1

100.0

No.

0421

125252

1213070

14264

109

Women

%

0.03.71.80.9

11.04.61.84.61.8

11.011.90.06.40.0

12.823.9

3.7100.0

Men

No.

164111144

9417503374208933379

• 0219

1,51542

8161,828

1407,802

OIF-2

%

2.11.41.80.15.36.44.82.7 .

12.04.90.02.8

19.40.5

10.523.4

1.8100.0

Women

No.

1130214

8453354272

1843832

2019

14215031

1,139

%

1.02.61.80.47.44.73.13.76.3

16.23.32.8

17.60.8

12.513.22.7

100.0

Note: y tests were excluded due to insufficient cell counts.

TABLE VIM. Distribution of Nonbattle Injuries among DNBICasualties by Gender during OIF"

Nonbattle InjuryCategory

BurnsDislocationsFracturesHeatSprains/strainsOpen woundsOtherTotal

Men

No.

74178721

37649304177

2,140

%

5.15.0

16.61.8

18.010.510.2

100.0

Women

No.

91754

5482320

176

%

3.54.2

17.91.1

19.811.67.6

100.0

Total

No.

8319577542

697327197

2,316

%

3.64.3

17.81.2

19.711.57.8

100.0

= 5.62, df= 6,p = 0.47.

with the estimated counts of casualties, patient streams arethe impetus of projecting the resources needed to sustainthe HSS.

Future research should compare various command ele-ments, which will provide more insight on the differencesbetween ICD-9 category distributions. Future studies shouldalso attempt to examine the accuracy of the ICD-9 data fromTRAC2ES and JPTA by comparing it with data collectedand coded by registries such as the Navy-Marine CorpsCombat Trauma Registry.'* The Navy-Marine Corps Com-bat Trauma Registry, although primarily consisting of Ma-rine casualties and including only patients initially treatedat level I and II Navy-Marine Corps facilities, uses pro-fessional nurse coders to code injuries and illnesses whichallows for the identification of possible systematic biasesand assessments of reliability and validity. Diagnosticreporting procedures and guidelines may need to be

adopted by TMIP-J to address these issues in their report-ing tools. More work is needed to identify wounding pat-terns associated with specific causative agents and to iden-tify the populations at risk, which are necessary forcalculating incidence and prevalence of the disease orinjury entities.

ACKNOWLEDGMENTSReport No. 07-01 was supported by the Office of Naval Research, Arlington,VA, and the Marine Corps Warfighting Laboratory under Work Unit No.63706N.M0095.60,511.

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James M. Zouris, Amber L. Wade, Cheryl P. Magno

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13. SUPPLEMENTARY NOTES Published in: Military Medicine, 2008, 173(3), 247-252

14. ABSTRACT (maximum 200 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-1) and the Support and

Stability Phase (OIF-2). 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-9

diagnostic category. Of the 13,988 casualties identified for analysis, 3,356 were WIA and 10,632 were DNBI. Overall,

the proportion of WIA was higher during OIF-1 (32.7%) than OIF-2 (22.9%). 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.

15. SUBJECT TERMS Operation Iraqi Freedom, wounded in action, disease and nonbattle injury 16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON

Commanding Officer a. REPORT UNCL

b.ABSTRACT UNCL

b. THIS PAGE UNCL

17. LIMITATION OF ABSTRACT

UNCL

18. NUMBER OF PAGES

7 19b. TELEPHONE NUMBER (INCLUDING AREA CODE) COMM/DSN: (619) 553-8429

Standard Form 298 (Rev. 8-98)Prescribed by ANSI Std. Z39-18

injury and illness casualty distributions among u.s. · pdf fileinjury and illness casualty...

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