It was around one o’clock in the morning on the turnpike in Mercer County, New Jersey when the driver of the tractor-trailer failed to observe slow-moving traffic ahead. At the last minute, the driver swerved to try to avoid the Mercedes limo bus but struck it from behind, forcing the limo to rotate and overturn. The result was one person killed and four others taken to the hospital including comedian Tracey Morgan.
A report issued by the National Transportation Safety Board stated that the driver of the rig that slammed into the van was speeding after working for more than 13 consecutive hours and driving for more than 9 hours and 37 minutes continuously leading up to the crash. Additionally, it is suspected that the driver had been awake for more than 24 consecutive hours, driving some 7 hours to the assigned pick up area for the rig where he began the trip. There seems to be a great deal of familiarity with this story. One has to ask, what was the role of the Fatigue Risk Management System (FRMS) in this tragic accident?
Before I get to deep into the subject, let us identify for those who are not familiar with fatigue risk management and safety systems, just what an FRMS is.
In short, FRMS takes its roots from something know as Safety Management Systems (SMS). This involves a systematic approach to operational risk management. Historically, SMS has been a largely reactive process. This means that incidents have been investigated and findings communicated together with appropriate controls to prevent reoccurrence - kind of like someone slapping you on the hand and saying don’t do that, it’s dangerous. Additionally, SMS has incorporated the identification of risks involved in the processes of the job. Traditionally, if the risk is too high then the plan gets changed to reduce the risk. In other words, you are working to avoid, trap or mitigate the errors brought on by the exposure to risk. This concept was greatly embraced in the field of aviation when James Reason published his book Human Error and continues to be embraced to this day.
FRMS has taken a similar approach but with a twist. In the field of FRMS, they have added predictive modeling to the mix. FMS's claim to fame is that it is science-based and supported by peer-reviewed science. Proponents of FRMS like their data in the system for what is called objective analysis. They also use system-wide tools built into corporate safety and health management systems. An active FRMS is supposed to be under constant monitoring for ways to reduce risk using feedback, evaluation, and modification of the system. Most companies that have an FRMS system will have a safety policy, a risk reporting system, perform incident investigations for more data, a training and education system, and perform audits on the FRMS system itself. An active FRMS system may look like the following:
- An active fatigue risk management information collection system such as questionnaires, surveys, a risk chart, and reports
- A fatigue reporting system for the employee
- Fatigue incident investigation system
- Sleep disorder management
- Fatigue education and training department/system
For all of this to work, there must be buy-in from the employees and supported in the form of a top-down approach by company ownership and management. Otherwise, FRMS becomes a policy that sets on the shelf and becomes a reactive program to accidents or incidents.
Many of us involved in high-risk occupations have been exposed to the systems approach to fighting fatigue. I have always been a proponent of the systems approach for a couple of very straightforward reasons. First, it’s better than not having any approach at all. Second, it allows us to collect data and learn from it. My only thought that diminishes it from being the “end all - be all,” is that it is based on the presumption, in the words of Forest Gump, “shit happens”. The presumption that sometimes things just happen and there is nothing we can do about it, except record the data and identify risks, just doesn’t sit well with me!
Looking at each component of the system it looks as though FRMS cannot fail. But how does it happen that fatigue-related accidents occur on a daily basis? I think my old friend Tony Kern struck gold with his assumption that the battle against error is a personal battle. This includes the battle against fatigue. If you haven’t had a chance to read any of Tony’s writings, I highly recommend his book Blue Threat – To Error is Inhuman, Pygmy Book, Monument Colorado, 2009. In a very eloquent manner, he describes many personal reliability issues and countermeasures that may not be addressed in many SMS or FRMS. Now in getting back to where I was going, I think there are a couple of weaknesses in FRMS.
First, if FRMS is not fully supported by management, it is doomed to fail. If the ownership of the FRMS is from topside management, then topside management must wave the flag and be active in all the processes, not just give lip service because FRMS may be required to conduct business. Second, I feel that the systems approach has placed too much emphasis on the system of data collection and not enough on personal accountability. The system begins and ends with what the individual does and does not do, and therefore an acceptable level of responsibility and accountability must be present. Third and lastly, FRMS offers only limited intervention in real-time and that intervention in its present form can be circumnavigated! Remember the Tracy Morgan story at the beginning of this article; all of these shortcomings were present and contributed to the accident.
So what’s this missing link in FRMS that I’ve been hinting at throughout this article? I believe it to be a real-time intervention. I truly believe that no predictive model is ever going to actively intervene when someone is about to fall asleep at his or her post, job or behind the wheel. What is needed is active monitoring, alerting and real-time data collection for the support of the FRMS.
The closest I’ve personally come to finding a fatigue monitoring device/system for real-time intervention comes from a company that I have done consulting and training work with – KOSTechnology.
KOSTechnology has developed a new fatigue risk worn bio-medical monitoring device that uses a measure of heart rate as a key indicator of the onset of fatigue-related unwanted sleep events. Let’s take a look at the science behind the invention and how the device and system works.
As we approach sleep onset a couple of things begin to happen within our bodies. First of all, you don’t normally fall asleep all at once. Unless you have been sleep deprived for a prolonged period of time. You actually enter into sleep in stages. Remember our discussion on sleep cycles? We described the early stages of sleep as preparatory stages, your brain actually starts to downshift from wakefulness to alpha wave to theta and so on and so on. Your physical body actually starts to downshift as well as you start to relax. Your body temperature will decrease slightly, your eyes may dilate, and your heart rate will decrease by as much as 5-8% of its normal resting state. This holds true for sudden onset sleep as well (even micro sleep), the heart rate drop is always present. This heart rate drop is a key indicator of your body’s propensity to fall asleep. KOSTechnology’s sensor uses this drop in heart rate and provides a warning to the wearer that unwanted sleep is about to occur.
The KOS Wearable device is very robust and performs multiple functions. The device automatically tracks the individual via GPS and can report independently. When a warning of unwanted sleep occurs there is a warning given to the wearer and simultaneously, a message is sent to a third-party such as a dispatcher, notifying them that a fatigue warning has occurred and to contact the wearer of the device. The third-party individual will know the exact location of the individual and can contact them with information, fatigue countermeasures and intervention, such as telling them to stop and take a break.
When coupled with the software suite that comes with the fatigue alerting device, a company can integrate the movement of the individual and heart rate data, as well as warning information into their company’s FRMS data collection portal. The company can then examine real-time historical data of events for future planning. They will be able to determine if a certain time period, event or route is a risk danger zone to their employee or operation, and actually be equipped to do something about it in real-time.
KOSTechnology has also incorporated another aspect of what I consider to be a vital part of the risk equation and that is user training. They offer as a service of general fatigue and fatigue risk management training coupled with their bio-medical measuring device. I think that KOSTechnology has truly found the missing link in the FRMS equation – real-time monitoring and intervention coupled with focused training for the individual to bolster his or her role in the risk management system. No system is complete without the incorporation of the human element into the scheme of things.
