Evidence Based Fatigue Risk gManagement as a Continuous

Performance Improvement ProcessPerformance Improvement Process

Steven R. Hursh, PhDPresident, Institutes for Behavior Resources

Professor, Johns Hopkins University School of Medicinep yshursh@ibrinc.org

Fatigue Risk Management SystemContinuous Improvement Process

MeasureDefine the situationSchedule evaluationActigraph recordings

Model & AnalyzeMonitorInvolves all stakeholdersat each stage:

management, labor, aided by science

Model & AnalyzeModel the fatigue problem

Analyze sources and Fatigue factors

o toAssess operational indicators

Individual self-evaluationFeedback to process

aided by science

EnablersEmployee trainingMedical screening

ManageCollaborate for solutionsObtain commitment to

Modify/MitigateShared Responsibility

• Operating practicesEconomic analysis

Technology aidssolve problem• Labor agreements

• Individual “life style”

Major Fatigue Factors● Time of Day: between midnight and 0600 hrs.● Recent Sleep: less than eight hours in last 24 ● Recent Sleep: less than eight hours in last 24

hrs. ● Continuous Hours Awake: more than 17 hours ● Continuous Hours Awake: more than 17 hours

since last major sleep period.C l i Sl D b h i h h ● Cumulative Sleep Debt: more than eight hours accumulation since last full night of sleep (i l d di d l )(includes disrupted sleep).

● Time on Task/Work Load: continuous work time without a break or intensity of work demands.

Symptoms versus Root Causes

Symptoms Operational Consequences● Measurable Changes in Root Cause Analysis● Measurable Changes in

Performance● Lapses in attention and vigilance● Delayed reactions

Root Cause Analysis Fatigue is one

potential root cause.y● Impaired logical reasoning and

decision-making● Reduced “situational awareness”

L ti ti t f

No direct measure, physiological marker, or “blood test” for● Low motivation to perform

“optional” activities● Poor assessment of risk or failure

to appreciate consequences of

or blood test for fatigue.

action● Operator inefficiencies

4

People are not good at judging h i l itheir own sleepiness

20

s

4.0 4 hr sleep6 hr sleep8 h lca

le

Actual Sleepiness Self-Rated Sleepiness

10

15

e La

pses

2.0

3.0 8 hr sleep

eepi

ness

Sc

0

5

Vigi

lanc

0.0

1.0

Sta

nfor

d S

le

-5BL 2 4 6 8 10 12 14

Days of Sleep Restriction

-1.0BL 2 4 6 8 10 12 14

S

Days of Sleep Restriction

Van Dongen, Maislin, Mullington, & Dinges (2003). The cumulative cost of additional wakefulness: dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. . SleepSleep, 26, 117, 26, 117--126.126.

Modeling Provides an Objective Metric for Fatigue

● The conditions that lead to fatig e are ell ● The conditions that lead to fatigue are well known.

● A fatigue model simulates the specific conditions and determines if fatigue could be present.

● The model can estimate the level of degradation in performance and provide an estimate of schedule induced fatigue risk.

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ALERTNESS & COGNITIVE PERFORMANCE

Time of Day Sleep History and Time on Duty

CIRCADIAN CUMULATIVE RHYTHM SLEEP DEBT

Daily Variations in Effectiveness

ALERTNESS & COGNITIVE

a y a at o s ect e ess

7

PERFORMANCE

SAFTE/FAST

●The Sleep, Activity, Fatigue, and T k Eff ti (SAFTE) M d lTask Effectiveness (SAFTE) Model.

●Based on 17 years of fatigue modeling experience.

●Validated against laboratory and Validated against laboratory and simulator measures of fatigue.

●Validated and calibrated to predict ●Validated and calibrated to predict accident risk by the Department of TransportationTransportation.

8

Human Factors Accident Risk is Significant Function of Decreasing Predicted Effectiveness (400 Railroad Accidents, Correlation = -0.93, p < 0.01)

80%

(400 Railroad Accidents, Correlation 0.93, p 0.01)

65%

40%

60%

22%20%

40%

Ris

k

10%6%7%

16%

0%

Random

-16%

r 2 = 0.86

-40%

-20%Human Factors Accidents

b l 5060 5070 6080 7090 80+100 90

Correlation Coefficient = -0.93, p < 0.01

9

35455565758595

Model Effectiveness Scorebelow 5060-5070-6080-7090-80+100-90

No Fatigue High FatigueHursh, 2008

Average Accident Property Cost by Major CausesAll accidents below 77 are more costly than averageAll accidents below 77 are more costly than average

$750 000

Average Accident Damage Costs by Effectiveness BandFive Rail Roads ‐ Crew harmonic effectiveness scores

$600,000

$750,000

Cost

Fatigue Type Cause Code

All Human Factors Causes

All Non Human Factors Accidents

4.8 x77

$450,000

dent Dam

age C

2 5

$300,000

Average Accid

Average cost of all accidents =

$277,575

2.5 x

$664,594$209,532$284,598 $343,343$201,996$137,442 $333,049$266,103$271,375$0

$150,000

A

10

$0

Below 7790 to 77Above 90

Effectiveness ScoreNo Fatigue Fatigue

Casualty CostsCasualty Costs● Fatality valued at $5,800,000● Injury Costs as a fraction of a fatality:

For employees, MAIS level determined by lost daysFor non-employees, MAIS level was moderate.

MAIS level 0 1 2 3 4 5 6

Severity None Minor Moderate Serious Severe Critical Fataly

Fraction of VSL 0 0.002 0.0155 0.0575 0.1875 0.7625 1

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Average Railroad Accident Cost by Major CausesAll accidents below 77 are more costly (property and casualties)

$1,200,000

ies) Human Factors Causes

$1,057,671

$1,000,000

and Ca

sualti

NonHuman Factors Causes

x 4

$600,000

$800,000

t (Prop

erty a

$419,590

$262,035

$400,488

$276,937$299,355

$400,000

cciden

t Cost

Average cost of all accidents =

$407,134

$0

$200,000

Average Ac

$

Less than or equal to 77 90 to 77Greater than 90

Estimated EffectivenessLow Fatigue Fatigue

12

Property Damage and Casualties$1,200,000

HumanFactors AverageCost w/ Casualties$1,057,671

$800,000

$1,000,000

Cost 

Human Factors Average Cost w/ Casualties

Human Factors Average Damage Cost

$600,000

$ ,

e Acciden

t C

$419,590

$262 035$355,022

$200 000

$400,000

Average

Average cost of all accidents =

$407,134

$262,035

$200,201

$136,335

$0

$200,000

Less thanor equal to 7790 to77Greater than90

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Less than or equal to 77 90 to 77Greater than 90

Estimated Effectiveness

Damage Risk and EffectivenessDamage Risk = Accident Risk x Relative Cost of Accident

454%4.50

5.00

Damage Risk (Property and Casualties)

g

308%

3.50

4.00

Damage Risk (Property Only)

Accident Risk

308%

2.50

3.00

ive Risk

145%

101%1 00

1.50

2.00

Relati

(-31%)

1.0 = Unchanged relative risk (100%)

(-77%) (-39%)(-67%) (-21%)

61%

23%

79%

33%

69%

0.00

0.50

1.00

Less than or equal to 77 90 to 77Greater than 90

Crew Effectiveness ScoreNo Fatigue Fatigue

Fatigue Risk Pyramid: Modeling and BarriersFatigue Risk Pyramid: Modeling and Barriers

AccidentsAccidentsIncidents

S bj ti A

Fatigue RelatedErrors

Job Performance ChangesSubjective Awareness

Second Line of DefenseSecond Line of DefenseEmployee sleep habits & conditions

First line of Defense

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Work demands, schedules, and sleep opportunities

Based on James Reason, “Managing the Risks of Organizational Accidents”, Figure 1.6, Stages in the development and investigation of an organizational accident.

First Line of Defense: Design Better SchedulesSoftware for Fatigue Assessment and ManagementSoftware for Fatigue Assessment and Management

● Fatigue Avoidance Scheduling Tool (FAST)g g ( )

● FAST is a fatigue assessment tool using the SAFTE model

● Developed for the US Air Force and the US Army.

● DOT/FRA sponsored work has lead to enhancements for transportation applications.

Sleep estimation algorithm

Schedule grid data entry tool

Wizards and dashboard Wizards and dashboard

Standard data file format

● DOT validated and calibrated.

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FAST Roster Fatigue Assessment Process

Organization Specific Schedule Database XML format

Same as Standard FAST

30‐Day Schedules except schedule is created by FAST AviationModeler

FAST RosterModeler

FAST Roster Manager

FAST Schedule Analyzer

• Specialized AutoSleep• SAFTE Model

O t t lt t f ld

• Sorts by Criterion• Displays results

Li k t A l

• Examine schedules• Effectiveness

Graph• Fatigue Factors• Output results to folder

• Links to Manager• Links to Analyzer• Fleet level reports

Fatigue Factors• “What-If” Drills• Individual reports

Modular Process for Speed and Flexibility

FAST Roster Manager

FAST Graphical Screen Options

Effectiveness

Adjustable Criterion LineAdjustable Criterion Line

Lower Percentile (e.g. 20%)

Work Periods in RedSleep Periods in Blue

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Work Periods in Red

Second Line of Defense: Get Better SleepNext Generation Actigraph Watch

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AMI MotionLogger ActigraphAMI MotionLogger Actigraph● Off-the-shelf accelerometer● Full-function sports watch● Event marker● Off-wrist detection● Temperature sensor● Temperature sensor● Onboard PVT● Onboard rating scale● Ports to fatigue modelg

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FS Actigraph Data ProcessingPersonnel wear the actigraph

Wrist movements are recorded 24/7 and downloaded over the internet

Individual fatigue risk levels are amalgamated into a group report

Personnel wear the actigraph that measures wrist movements

Downloaded data are converted toSAFTE evaluates the fatigue risk Downloaded data are converted to daily sleep/wake/work timesDaily sleep/wake/work times are

fed into the SAFTE risk evaluation model

SAFTE evaluates the fatigue risk and effectiveness of each individualdriver

Tools: FatigueScience.com

Fatigue Risk Management SystemContinuous Improvement Process

MeasureDefine the situationSchedule evaluation

13.0%

13.0%

20.5%

41.0%

42.0%

88.0%

OutcomeM Actigraph recordings

Model & AnalyzeMonitor

6.0%

6.4%

8.0%

9.8%

12.0%

0% 25% 50% 75% 100%

Measures& Modeling

Involves all stakeholdersat each stage:

management, labor, aided by science

Model & AnalyzeModel the fatigue problem

Analyze sources and Fatigue factors

o toAssess operational indicators

Individual self-evaluationFeedback to process

Mitigations are Proportional to the RiskEvolutionary, Incremental ImprovementResponsive to Changing Circumstancesaided by scienceResponsive to Changing Circumstances

EnablersEmployee trainingMedical screening

ManageCollaborate for solutionsObtain commitment to

Modify/MitigateShared Responsibility

• Operating practicesEconomic analysis

Technology aidssolve problem• Labor agreements

• Individual “life style”

Fatigue Risk Management Services

If you would like help,

g g

If you would like help, call……

Steve Hursh or Melissa MallisSteve Hursh or Melissa Mallis410-752-6080

shursh@ibrinc.orgmmallis@ibrinc orgmmallis@ibrinc.org

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Government and Commercial Users● Two major aviation carriers planning to filter all schedules through ● Two major aviation carriers planning to filter all schedules through

SAFTE/FAST. Other companies in negotiation.

● FAA Ultra-long Range City Pairs, Other schedules

● The Federal Railroad Administration (FRA) – accident wizard

● NTSB – accident investigation

● Air Force and Navy aviation safety centers – accidents● Air Force and Navy aviation safety centers accidents

● All AF flight surgeons trained on FAST● The 201st Airlift Squadron - Andrew AFB - VIP flights

● Army unit level fatigue tool

● NASA medical risk model

● The Canadian Defense Aviation Establishment ● The Canadian Defense Aviation Establishment

● Sixteen government regulators world-wide

● 93 military users

● Fourteen major aviation carriers

Railroad Illustration: Railroad Illustration: Reduce All Duty Periods to 6 hrs or less → Increased Fatigue and Potential RiskReduce All Duty Periods to 6 hrs or less → Increased Fatigue and Potential Risk

5% < 751 7% < 701.7% < 70

Standard Duty Periods Up to 10 hrs plus

11% < 755% < 70

Li it d D t P i d U t 6 h

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Limited Duty Periods Up to 6 hrs

BAC ScaleBAC ScaleThe effects of fatigue may be compared to the effects

of blood alcohol to calibrate the severity of fatigueContinuous

Hours of Wakefulness

Reaction Speedor

Effectiveness

Blood Alcohol Concentration

of blood alcohol to calibrate the severity of fatigue

Wakefulness Effectiveness (% Baseline)

18.5 77 0.0521 70 0.08

Arnedt, J.T., Wilde, G.J., Munt, P.W., MacLean, A.W. “How do prolonged wakefulness and alcohol compare in the decrements they produce on a simulated driving task?” Accid Anal Prev 2001

However, fatigue and the effects of alcohol are not identical.

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compare in the decrements they produce on a simulated driving task? Accid Anal Prev., 2001 May;33(3):337-44.

Dawson, D., Reid, K., 1997. “Fatigue, alcohol and performance impairment.” Nature 388, 23.