Healthcare and Medicine Reference
In-Depth Information
a causal factor in catastrophic accidents. 26,52,53 At the popu-
lation level, a case-control study has estimated that motor
vehicle crashes resulting in injury could be reduced by
19% on a metropolitan road network if drivers did not
drive when they felt sleepy, when they had slept 5 hours or
less in the last 24 hours, or between 2:00 AM and 5:00 AM. 54
A fatigue-related incident or accident can be viewed as
the final point in a causal chain of events or hazard trajec-
tory that penetrates all the defenses present in the system
to control that hazard. 55 A series of defensive layers can be
implemented to limit the likelihood of a fatigue-related
incident or accident (a defenses-in-depth approach),
• providing adequate opportunities for sleep (level 1
defense, partially addressed by traditional hours-of-ser-
vice regulations);
• processes for confirming that adequate sleep is obtained
(level 2 defense);
• processes to detect behavioral symptoms of fatigue (level
3 defense);
• processes for detecting fatigue-related errors (level 4
defense); and
• processes for investigating fatigue-related incidents
(level 5 defense).
No single level of defenses is impenetrable. However, in a
system with four levels of defense, even if each level has
only 50% sensitivity for detecting fatigue, only about 6%
of cases will remain undetected.
The concept of defenses in depth is central to fatigue
risk management systems. Sleep science is not yet able to
reliably predict the level of fatigue-related impairment of
an individual at a given point in time. Estimating the risk
of a fatigue-related accident at a given point in time is even
more complex and depends on the context in which the
fatigued person is working (see Chapter 67, this volume).
However, in a defenses-in-depth approach, additional
defensive layers can be implemented to compensate for
scientific uncertainty. As scientific understanding improves,
the effectiveness of the overall system for reducing fatigue
risk also improves.
modern onboard technologies that continuously record a
vast array of light data. These data are already being
assessed on a routine basis to proactively correct shortcom-
ings in light operations before safety issues arise. The
challenge for FRMS is to link crew fatigue to identified
incidents of exceeding established light safety parameters.
Proactive analysis occurs whenever a significant change
is introduced. For example, appropriately validated bio-
mathematical models can be used to estimate likely fatigue
levels on a new route or as a result of a significant schedule
change. In a system with multiple layers of defense, models
do not have to be perfect to be useful, so long as other
defenses are adequate to detect and manage where model
predictions are unreliable. As model predictive capability
improves, the effectiveness of the overall system for reduc-
ing fatigue risk improves.
Once a register of hazards has been established, risk
management aims at minimizing the safety impact of those
hazards. In its guidance material, ICAO identifies three
levels of safety management. First is suppression of risk,
for example in FRMS by eliminating schedules that are
associated with high levels of fatigue. Second is mitigation
of the risk of fatigue, for example by providing education
on personal strategies to improve sleep, or in long-haul
aviation providing additional crew members and the
opportunity for in-flight sleep, or ensuring that schedules
include layovers that permit sufficient time for recovery
sleep. Third is strategies to maintain operational safety
when crewmembers are fatigued, for example through the
use of automation or task rotation. This level is critical
because fatigue risk cannot be eliminated by the first two
levels, particularly fatigue caused by nonwork factors.
Consistent with these considerations, we here define an
FRMS as a scientifically based and flexible alternative to
rigid work time limitations that provides a layered system
of defenses to minimize, as far as is reasonably practicable,
the adverse effects of fatigue on workforce alertness and
performance and the safety risk that this represents.
A strength of this approach is that it does not rely on a
priori decisions about the factors most likely to be causing
fatigue, in contrast to the traditional prescriptive hours-of-
service limits, which focus on duration of work and rest.
Instead, the FRMS is data driven, monitoring where
fatigue risk occurs and where safety may be jeopardized
and generating new scheduling solutions or other strate-
gies to mitigate measured fatigue risk. At the same time,
the FRMS provides operators with flexibility to seek the
most efficient safe crewing solutions to meet operational
Fatigue risk management systems are not envisaged as a
one-size-fits-all approach. They differ according to the
regulatory framework under which an organization oper-
ates; the complexity, scale, and nature of its operations; the
operational reliability required; and the particular demo-
graphics of its workforce. A detailed example of a compre-
hensive FRMS for aviation operations has been published
by the Flight Safety Foundation. 57
Safety Management Systems
Ideally, fatigue risk management systems are one compo-
nent in a broader safety management system that addresses
the full range of hazards in a given work environment.
Safety management systems are becoming more formal-
ized across a range of industries. For example, standards
for safety management systems in the aviation industry are
specified in a manual published by the International Civil
Aviation Organization (ICAO). 56 To identify hazards,
ICAO identifies three types of tools: reactive analysis,
normal activity analysis, and proactive analysis.
Reactive analysis is based on reporting systems. For
example, a voluntary reporting system ensures that crew-
members can report possible fatigue-related incidents
without fear of retribution, in addition to the mandatory
reporting required for more serious safety incidents.
Normal activity analysis uses questionnaires or routine
observations. This provides data for the analysis of trends
in fatigue risk and does not rely on fatigue levels reaching
a threshold where accidents or reportable safety events
occur. For FRMS, it is possible to take advantage of
The Role of Regulation
Concerns about the risk that fatigued people pose to others
are particularly acute in sectors such as health care and
public transportation, where consumers must trust that
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