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 [email protected]
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
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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.
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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
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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
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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
[email protected]@ibrinc [email protected]
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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.