Deployed Health SurveillanceDeployed Health SurveillanceMethods and ResultsMethods and Results

Col Kenneth L. CoxCol Kenneth L. CoxDirector, Force Health ReadinessDirector, Force Health Readiness

Deployment Health Support DirectorateDeployment Health Support Directorate

AFEB Meeting

21 September 2004

Slide #2

Overview

• Force Health Protection• Overview of Current Methods/Systems

– Occupational & Environmental Assessments– Disease Surveillance– Injury Surveillance– Mortality– Pre- and Post-deployment Health Surveys

• Future Directions• Summary

Slide #3

Episodic Health AssessmentsAcross the Military Life Cycle

Deployment

Garrison

Deployment

Garrison

Recruits

Recruit Assessment Program

Active Duty, National Guard, Reserve Episodic Health Assessments in Garrison (PHA, “HEAR”)

Pre- and Post-deployment Health Assessments DD 2795/2796

Chronologic Summary of Health Status DD 2766

Deployment

Garrison

Deployment

Separated and/or Retired

DeathMortality Registry

MEPS

BMT

OTS

Acad

PRD-5 Mandates “Cradle to Grave Surveillance…”

Garrison

Slide #4

Force Health ProtectionGoals and Needs

• If we want to:– Detect outbreaks

• Natural disease• Chem-bio attacks

– Maximize readiness & mission effectiveness

– Monitor injury patterns, lost duty time, etc.

– Evaluate exposures vs. health outcomes

• We will need:– Real-time global health &

exposure surveillance

– Accurate, systematic & thorough data collection

• Locations • Exposures

• Health events

– Electronic medical records

– Short- and long-term epidemiological analyses

Near-te rm

to Lon

g-ter m

Slide #5

Existing Systems/Programs

• In-theater Health & Environ Surveillance– Disease and Non-battle Injury Reporting– Occupational & Environmental Reporting

• Aeromedical Evacuation Data• Other (Safety Reports, Trauma Registries)• Casualty Reports (hostile injuries/deaths)

– Personnel Component– Mortality Component (AFIP)

• Pre- and Post-deployment Surveys

Slide #6

Health Risk Reassessment

• Relies on newly collected data from the site– Site observations and industrial shop visits

– Sampling and testing• On-site, e.g., HAPSITE, direct reading sampling tubes

• Off-site via reference labs, e.g., CHPPM, NEHC, AFIOH

– Newly identified sources, e.g., local health department

• Local risk assessment and additional review via reachback resources

• Methodology, qualitative vs. quantitative– Whose standards apply?

Slide #7

Respiratory Disease & Air Quality

0

20

40

60

80

100

120

Week1

Week2

Week3

Week4

Week5

Week6

Week7

Week8

Week9

Week10

Week11

Week12

0

5

10

15

20

25

30

Respiratory Disease (e.g., Asthma) Respirable Particulate Matter

Site X— Fictitious Dataμg/m3/24 hr Cases/1000

EPA Standard=65 μg/m3/24 hr SWA Respiratory Rate=4/1000

Slide #8

• JCS DNBI data

• Weekly

• CENTCOM SSC

• Daily

Med Evac (TRAC2ES)

End Users

• SecDef

• CENTCOM

• SGs

• Field units

Theater Health Event Data Flow Patterns

CHCS2-TSAMSGEMS

Slide #9

Disease Non-battle Injury (DNBI) JCS-Mandated

Categories (Weekly)

DermatologicGI, infectionsGynecologicOphthalmologicPsychiatricCombat stressRespiratoryIntimate diseasesFever, >24 hoursNeurologic (new)All other, med/surg

Injuries, heat/cold

Injuries, sports/recreation

Injuries, motor vehicle

Injuries, work/training

Injuries, other

Problems:Static since inception (1998)Data 10-14 days old when analyzeThis won’t detect WMD attacksSolution?—Special Surveillance

Slide #10

CENTCOM Special DNBI Surveillance Categories (Daily)

Category Definition

Systemic Fever(generic flu-like prodromes, e.g., tularemia)

Unexplained temp > 38C (100.5F) for 24 hours or a history of chills and fever without a clear diagnosis. Includes flu-like illnesses with fever and multiple systemic complaints (such as cough).

Lower Respiratory Illness (anthrax)

Bronchitis, pneumonia, new onset reactive airway disease, pleurisy, or respiratory difficulty of unclear etiology

Infectious GI (ricin) Any infection primarily manifested by vomiting and/or diarrhea.

Dermatologic Unclear Dx (s-pox)

Skin infections, blisters, ulcers, etc.

Unexplained Neuro(botulinum toxin)

Cases of altered levels of consciousness, cranial nerve dysfunction, muscle weakness

Slide #11

Analytical Methods

• Poisson statistics (z-score) for near-term, measures of central tendency for long-term

• Linear regression model using empirically derived baseline covering previous 4-12 weeks of data, replaced by exponentially weighted moving average when poor data fit– Geographic cluster spatial scan analysis

available, but not used with theater data

• Change-point-detection approach

Slide #12

CPEG Chart Process Control Chart

-1 3

320 19

321 19

322 24

323 4

324 21

331 32

Week of: 14-March-2003; As of: 26 Mar 2003 FRI Report

Wee

kly

FR

I Rep

ort f

or s

quad

ron

320

Rat

e pe

r 100

Week Ending 14-March-2003

Weekly FRI Rate 25-Week Average Alarm Threshold Alert Threshold

20-Sep 15-Oct 9-Nov 4-Dec 29-Dec 23-Jan 17-Feb 14-Mar

1.0

2.0

3.0

4.0

Analysis & Interpretation

Slide #13

Recent & Historic DNBI Rates

DNBI CategoryDNBI Rate per 100 (%) Personnel per Week

ODS/S1 OJE1 OJG2

Conflict Phase3 Stabilization Phase4

OEF OIF OEF OIF

Dermatologic 0.93 0.72 0.92 0.66 0.61 0.51 0.44

GI, Infectious 0.87 0.45 0.45 0.72 0.34 0.47 0.34

Respiratory 1.04 1.00 2.09 0.99 1.04 0.62 0.44

Total Injury 1.19 1.95 2.19 1.42 0.96 1.39 1.03

Total DNBI 6.48 7.09 8.12 5.73 5.19 5.14 3.901Sanchez, Craig, Kohlhase, et al. Mil Med 2001;166:470-4.

2McKee, Kortepeter, Ljaamo. Mil Med 1998;163:733-42.

1OIF Conflict Phase (not OEF) 15 March 2003 to 3 May 2003.

44 May 2003 to 13 August 2004.

Data Source: AFIOH analyzed data – on 27 August 2004.

Slide #14

Injury Pyramid Data CaptureGarrison vs. Theater

Source: World Health Organization

In Garrison In Theater

Near Total

Near Total

Near Total

Near Total

Rare

Near Total

Fair

Fair to Poor, combined into one category

Rare

Slide #15

Comparative ResultsInjury Rates (Theater vs. Garrison)

Data Source Time Period Avg Unclass Denominators

*

Avg Cumulative Rate/1000

OIF (TRAC2ES) Mar 03-Jul 04 200,431 13

OEF (TRAC2ES) Mar 03-Jul 04 10,516 27.5

Garrison (Inptnt + Outptnt fx)

Jan 03-Mar 04 2,119,850 22

Garrison (Inptnt only)

Jan 03-Mar 04 2,119,850 3.9

Garrison (Outptnt only)

Jan 03-Mar 04 2,119,850 366

* In-garrison denominator adjusted to account for deployed troops

DSOC Categories—Theater vs. Garrison

NBI Rates/1000 Service MembersCategory OIF

19 Mar 03-31 Jul 04

OEF1 Oct 02-31 Jul 04

Garrison1 Jan 03 -31 May 04

Head/Neck 0.29 1.45 22.81

Shoulder/Arm 1.62 5.77 33.53

Hand/Wrist 1.36 4.77 28.23

Leg 0.32 1.31 8.31

Knee 1.10 2.96 30.71

Ankle/Foot 0.93 3.25 78.92

Torso 2.82 7.73 92.88

Environmental 0.23 0.74 9.44

Unspecified 1.82 6.73 66.03

TotalsAnnualizedAverage/month

10.488.110.66

34.7319.850.95

370.86261.7821.82

1 1 1

2 2

2

3 3

3

4 4

4

5

5

5

Slide #17

Rat

e p

er

1000

Month

Total Injury Injury Rate Average Alarm Level Alert Level

Feb2003 Apr2003 Jun2003 Aug2003 Oct2003 Dec2003Feb2004 Apr2004

0.00

0.50

1.00

1.50

0.64

Total Injuries, OIFDSOC Schema, TRAC2ES Data

Avg monthly total NBI rate = 0.6/1000 Cumulative 17 month rate = 10.5/1000

Slide #18

Top 10 OIF Injury DiagnosesBarell Matrix Pareto

00.10.20.30.40.50.60.70.80.9

1

Uns

pecif

ied

- Fra

ctur

e

Knee

- Disloca

tion

Shoul

der /

Upp

er A

rm D

isloca

tion

Uns

pecif

ied

- Wris

t/Han

d/Fi

nger

s

Wris

t/Han

d/Fi

nger

- Fra

ctur

e

Wris

t/Han

d/Fi

nger

- O

pen

Wou

nd

Wris

t/Han

d/Fi

nger

- Cru

sh

Wris

t/Han

d/Fi

nger

s - A

mpu

tatio

n

Lum

bar V

CI -

Spr

ains

& Stra

ins

Face

- Bur

ns

Foot

/Toe

s - O

pen

Wou

nd

Back/But

tock

- Spr

ains

& S

trains

Inju

ry R

ate

Pe

r 1

00

0 S

erv

ice

me

mb

ers

Chart includes all injuries from TRAC2ES for 19 Mar 03 – 31 Jul 04

Slide #19

Mortality Data & Reports

• Casualty Reporting System– Personnel driven, categories assigned by

personnel

• AFIP Medical Examiner Reports– 100% autopsies on all active duty deaths

– Cause of death info vital to refining protective measures, driving research, etc.

– Gold standard for mortality data. Lag time between for tox results and final report

Slide #20

OIF Causes of Hostile DeathAll Services, 3/19/2003 – 7/31/2004

N=639 (total deaths=913)

*Projectile injuries due to various mechanisms.

0

50

100

150

200

250

300

350

Blast &shrapnelinjuries

Gunshotwound

Blunt forceinjuries

Ballisticinjuries*

Multipleinjuries

Drowning Thermalinjuries

Other

Nu

mb

er o

f Dea

ths

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Cu

mu

lativ

e P

erce

nt

Mortality Surveillance DivisionOffice of the Armed Forces Medical Examiner

Slide #21

OIF Hostile Deaths Lethal Injury Site: Explosives vs. Small Arms Fire

3/19/2003 – 7/31/2004

ExplosivesN=450

Small ArmsN=160

Extremities4%

Head/Neck44%

Multiple15%

NA1%

Torso36%

Extremities5%

Head/Neck33%

Multiple45%

Torso17%

Mortality Surveillance DivisionOffice of the Armed Forces Medical Examiner

Slide #22

Post-deployment SurveyDD Form 2796

• Self-assessment of individual health at end of deployment

• Ensure those who develop illnesses (or concerns) while deployed receive appropriate follow-up

• Monitor trends in concerns, sites with reported exposures, identify cohorts for additional study, identify risk commun-ication topics

Slide #23

Post-deployment SurveyResults, Partial Summary

Service Member Responses since 01 Jan 03, % Affirmative Active Duty with Reserve Compnent Value in Parentheses

General Health (fair or poor)

Medical/Dental

Problems

Mental Health

Concerns

Exposure Concerns

Health Concerns

Referral Indicated

Med Visit After

Referral

Army 9 (11) 28 (40) 5 (6) 17 (22) 15 (22) 26 (26) 95 (82)

Navy 5 (5) 12 (34) 2 (2) 5 (18) 6 (18) 6 (15) 70 (87)

AF 2 (3) 11 (17) 1 (1) 6 (9) 5 (9) 10 (13) 88 (64)

Marine 6 (10) 18 (36) 2 (3) 12 (24) 8 (24) 11 (24) 61 (56)

Total 7 (9) 21 (37) 3 (5) 12 (21) 10 (20) 18 (33) 84 (78)

Sour

ce:

Def

ense

Med

ical

Sur

veil

lanc

e S

yste

m

Slide #24

Deployment SurveillanceFuture Directions

• Fill critical data gaps (e.g., environmental exposure data, in-theater hospitalization/surgery data, reproductive health outcomes, cancer events, etc.)

• Automate data collection as much as possible• Validate and refine syndromic categories, threshold

determination, risk assessment methodologies, etc.• Integrate diverse data streams (e.g., lab results,

personnel data, geospatial data, etc.)

• Monitor cohorts (unusual exposures, risk groups, etc.)• Evaluate new technologies (e.g., biomarkers,

microarrays) and analytical approaches

Slide #25

Summary

• Health surveillance is a valuable tool to:– Detect, confirm, and/or characterize outbreaks

(diseases, injuries, etc.)– A way to monitor the effectiveness of public health and

preventive medicine programs

• Health surveillance will benefit from validation of best methods, standardization, user-friendly electronic systems, & improved reporting

• Greatest value is to forward units. High-level reports useful for answering questions from media & national leaders, but virtually no public health benefit due to dilution effect of aggregating data across wide geographic area and diverse environs

Questions and Discussion

Slide #27

Common Exposure Categories Identified in EOHWED

Environmental• Airborne dust

• Air emissions from industry• Endemic diseases• Drinking water• Hazardous waste sites• NBC weapon exposure

• Hazardous animals/insects• Agricultural emissions• Depleted uranium• Lead-based paint & asbestos

Occupational• Noise

• Heat stress• Airborne chemical exposure• Contact chemical exposure• Ionizing radiation• Non-ionizing radiation

• Ergonomics• Bloodborne pathogens

Slide #28

Distribution of Injury & Disease DataICD-9 Diagnostic Groups, TRAC2ES vs. Garrison

Category OIF*Mar 03-Jul 04

OEF*Mar 03-Jul 04

Garrison*Jan 03-May 04

Non-battle Injuries

12.78 27.46 370.35

Infections 2.47 1.82 Not Available

Mental 2.82 8.85 Not Available

Nervous 3.25 6.20 Not Available

Digestive 5.56 10.16 Not Available

Respiratory 1.40 3.57 Not Available

Musculoskeletal 7.94 20.48 Not Available

Ill-defined 5.20 15.12 Not Available

Other 25.31 53.03 Not Available

Totals 51.48 117.40

* Injury Rate Per 1,000 Service Members

Slide #29

OIF TRAC2ES DataPrincipal ICD-9 Diagnostic Groups

19%

4%

4%

5%

8%

2%12%

8%

38%

Non-battle InjuriesInfectionsMentalNervousDigestiveRespiratoryMusculoskeletalIll-definedOther

Compares favorably with Marine hospitalization data from Vietnam

Slide #30

Disease, Non-battle InjuryWeekly DNBI

Findings/Actions/Results•Documented natural disease outbreaks that were already recognized by field

–Thanksgiving “food poisoning”–Norovirus on aircraft carrier

•Outbreaks found by other means–Severe penumonias (AEP)–Leishmaniasis–Malaria

Future Directions•Facilitate better compliance and improved accuracy via TMIP, e.g., CHCS2-T•Add inpatient electronic data collection•Evaluate value of other category definitions and more frequent DNBI data collection, e.g., daily syndromic surveillance

JCS broad-based disease categories, e.g., Respiratory, GI, Derm, Injuries (4 types), etc.

Data Characteristics: compliance highly variable. Last week’s data analyzed by Wed/Thu of following week. Accuracy also varies due to multiple data collection systems, some manually assigned, others based on ICD-9 codes as entered by field medical staff, most who don’t have training in coding. Outpatient data only.

Slide #31

Aeromedical EvacuationsTRAC2ES

Findings/Actions/Results•Used primarily to answer questions about injury patterns. Provides some insight about requisite in-theater resource levels (equipment, specialty mix, etc.)

Future Directions

Aeromedical evacuation tracking data serves as a surrogate for in-theater inpatient disease and injury rates.

Data Characteristics: severity biased. Preliminary, often unconfirmed diagnoses subject to change during and after evacuation. Web-enabled data entry with immediate transmission to central database facilitates real-time analysis.

Slide #32

Safety ReportsIn-theater Investigations

Findings/Actions/Results•Helicopter crashes•Motor vehicle crashes, in-theater steps taken to reverse trend•Sports and recreation injuries, periodic efforts to address, as in CONUS

Future Directions

Description: Data Characteristics: