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FATIGUE MANAGEMENT DISCUSSION POINTS The following discussion points and recommendations arise as a consequence of reviewing the following documents: a. Procedures for Validation and Calibration of Human Fatigue Models: The Fatigue Audit InterDyne Tool. US Department of Transport Federal Railroad Administration. Final Report, November 2010. b. Transport and Main Roads: Rail Safety Regulation Safety Alert. Notice to Accredited Rail Transport Operators. 01/11 – Use of bio-mathematical models of human fatigue. 18/1/2011. c. Transport and Main Roads: Rail Safety Regulation Safety Alert. Notice to Accredited Rail Transport Operators. 04/10 – Use of bio-mathematical models managing risks of human fatigue in the workplace. 30/7/2010. d. Transport Safety Alert. Independent Transport Safety Regulator. Use of Bio-Mathematical Models in Managing Risks of Human Fatigue in the Workplace. 27/7/2010. DISCUSSION POINTS 1. Rail Transport Operators (RTO) using bio-mathematical fatigue models should make necessary adjustments to their practice to minimize over reliance on just the “results” (i.e. Fatigue scores) in making risk management decisions pertaining to fatigue. 2. Current bio-mathematical fatigue models only partially represent the factors that impact on fatigue and performance and cannot be solely relied upon to deliver “rules” to be applied to fatigue risk management. 3. Instructions supporting such models are often unclear and should be supplemented to provide better guidance to users. 4. A FAID score of less than 80 does not necessarily mean that a person is not impaired by fatigue. FAID scores as low as 63.18 represent the exact “fatigue threshold” for FAID. 5. Sleep estimate output of FAID provides supplementary information to assess average opportunity for sleep and provides a general indication of the impact of time of day factors on amount of sleep based on group data not on an individual basis. 6. Factors such as physiological, work environment, social/psychological must also be considered. 7. Fatigue management models need to evolve and include individual direct measures to be best practice. 8. Limitations of bio-mathematical models: (i) In itself it is not a fatigue risk management approach. (ii) “Scores” should never be used as the sole basis for risk management decisions regarding work hours. (iii) Such models are better at predicting fatigue when people are kept awake continuously. They are less effective at predicting the accumulation of performance impairment over many days of sleep loss. (iv) Model outputs are based on averages and should not be used to make decisions on individual worker’s fitness for duty. (v) Such models do not take into account other factors that impact on fatigue (e.g. Time pressure, work/team environment, skill level, experience, age, health and home life). 9. RTO in many cases are applying the general statements by FAID model developers in industry reports/articles for the validation of FAID/FAID scores of <80. The research evidence to support this is not strong. 10. It has not been established if FAID scores can predict the risk of accidents/incidents. 11. Fatigue associated with shift work is cumulative due to partial sleep loss over time and is different to the effects of being continuously awake – which is what the FAID model measurements are made upon. 12. Simple comparisons between fatigue/FAID scores and blood alcohol content (BAC) have limited validity. 13. Performance on some tasks is more sensitive to sleep deprivation than alcohol impairment. 14. A FAID score of <80 does not mean that a work schedule is acceptable or that a person isn’t fatigue impaired. 15. FAID scores grouped as low, moderate and high are general/qualitative descriptions. A person whose score places him/her in the low range can still be fatigue impaired. 16. FAID scores should not be the sole discriminator to determine the acceptability of individual work schedules. 17. Informing workers of their FAID score is not an effective fatigue management control. 18. FAID scores should not be used retrospectively to determine if fatigue was a factor in an incident. 19. FAID outputs do not reflect extended awake time, time on task, the impact of the task/workload on alertness/performance. 20. A FAID score of <80 does not necessarily means that there is adequate opportunity for recovery sleep. 21. RTO using FAID scores should also use FAID sleep estimate output in their decision making. However, FAID sleep estimate appears to be based on average data from train drivers and may be less accurate for other types of shift workers. 22. The default minimum sleep set by FAID is 5 hours in the previous 24, this should not be interpreted as being adequate. Scientific uncertainty surrounds this with some research suggesting a minimum of 6 hours for highly safety critical tasks. 23. There is a range of other indicators that can be used to assess aspects of the effectiveness of a work schedule and fatigue management program including: (i) monitoring performance indicators (e.g. Planned vs. actual hours worked, time on task, consecutive shifts, etc.). (ii) Monitoring operational data (e.g. Errors). (iii) Monitoring absenteeism. (iv) Monitoring self reported fatigue. (v) Collection of sleep data (e.g. Readiband type monitoring). 24. FAID scores do not assess; age, social/psychological issues, health, competing priorities in relation to individual workers. 25. FAID scores of >80 indicate severe fatigue, 70-80 indicate extreme fatigue. A fatigue threshold (level at which fatigue becomes an unacceptable risk) is a FAID score of 60. FAID scores of <80 do not necessarily indicate a lack of fatigue. 26. Accurate estimates of mean FAID and FAST/SAFTE (Sleep, Activity, Fatigue and Task Effectiveness model) scores can be used at a population level but not on an individual basis. Other factors need to be considered. 27. It has not been established if FAID scores can predict the risk of incidents or accidents. 28. FAID (and similar bio-mathematical tools) are (at best) predictors of fatigue for a given work schedule. They are not a direct, objective measure. BACKGROUND The Fatigue Science ReadiBand is an easy to use, wrist-worn device that measures day-to-day sleep quality, quantity and timing. The ReadiBand relies upon the measurement and analysis of wrist movements to detect and characterize sleep/wake periods. The system is highly accurate. A recent comparative study showed the ReadiBand, system to be 93% correlated to sleep lab polysomnography (sleep studies). ReadiBand data provides a range of sleep statistics, such as sleep efficiency, sleep duration, and time to sleep onset. Additionally, ReadiBand data can be used to generate actual (rather than predicted) individual fatigue risk profiles. A major study funded by the U.S. Federal Railway Administration (FRA) validated the SAFTE model (Sleep, Activity, Fatigue, and Task Effectiveness model) and FAST Tool (Fatigue Avoidance Scheduling Tool), upon which the Readiband system is based, as accurate predictors of fatigue-related accidents. A similar system has been validated by the US Department of Transportation for use in the aviation industry. Whilst fatigue can’t be completely eliminated in the workplace, this approach of measuring, mitigating, and evaluating forms a continuous improvement process that significantly reduces the impact of fatigue on safety and improves employee wellbeing. ReadiBand establishes whether an employee is adequately alert when on duty. The FAST tool identifies rostering factors within an organization that creates unnecessarily high levels of fatigue and can also be used on an individual basis to mitigate fatigue by teaching employees how to better handle lifestyles to attenuate personal fatigue levels. HOW IT WORKS The Readiband device is placed on the participant’s wrist and is worn 24/7 for 2-4 weeks. The device measures movement only. When the person is active the device records a movement signature, when the person is at rest (not moving) the device records a signature for that. At the end of a 2-4 period the participant returns the device to the facilitator and movement patterns are downloaded. It should be acknowledged that the ONLY way to attenuate the effects of fatigue is to obtain adequate periods of restorative sleep. Movement during periods of time otherwise designated as “sleep” indicate that the participant, although in bed for say 7 hours, may have had multiple periods of wakefulness during that period indicating sleep patterns are less than optimal. The participant (as necessary), is then counselled as to how to improve sleep hygiene (e.g. Limiting caffeine intake within 6 hours of bed-time, improving lifestyle habits – eating, exercise, improving the sleep environment by darkening the room, using a source of white noise, etc.). The participant then reattaches the Readiband and incorporates the suggested modifications into their lifestyles. 2-4 weeks later the data is once again downloaded and compared against the initial baseline data to ascertain; (a) if sleep patterns have been improved and/or (b) to recommend other interventions (e.g. Polysomnography - sleep studies) be prescribed to ascertain whether or not the individual is suffering from maladies such as sleep apnoea and therefore jeopardizing safety from a fatigue perspective. Devices such as the Readiband provide the link from “predictive” estimations of fatigue to “actual measures” and in so doing evolve the QRN Bulk East Fatigue Management Program (FMP). It should be noted that: 1. Individual data obtained from participants is only reported to that participant. The organisation sees no individual data sets. 2. De-identified data can be pooled by site, across the organisation, etc. as necessary/requested by management, to ascertain which locations, etc. may have fatigue related issues/concerns. Resources can then be allocated accordingly. For example, if sleep apnoea is indentified as being a significant cause of fatigue at a certain site a Health and Wellness initiative could be deployed to improve lifestyle habits as sleep apnoea is strongly collated with excess body weight. RECOMMENDATIONS A number of sites across Bulk East have been most receptive HSE initiatives such as Participative Ergonomics (PE), on-site physiotherapy and the 24 Week Lifestyle Behavioural Change Program. Many aspects of these programs dovetail together and support/leverage one another. A trial of the Readiband system would compliment a number of aspects of the above programs as well. Identify a “typical” site (from the above) with supportive management and a 24/7 operational load. Aim to get a sample size of 20-30 volunteers working across all shift combinations and permutations over a 6-8 week test period. Have the above 20-30 volunteers involved in a pilot trial to identify and assess: (i) The effectiveness of the system in delivery, (ii) the effectiveness of the system in identifying fatigue, (iii) adherence of volunteers over the duration of the trial, (iv) the effectiveness of suggested behavioural changes in attenuating fatigue and improving individual outcomes, (v) the effectiveness of the Readiband reporting system in providing detailed group reports capable of elucidating issues and intervention strategies on a site by site basis. Get the above scenario costed with a view to ultimately, if deemed to be an effective intervention, being able assess targeted sites, classes of employees, etc. to ascertain trend data and potential global interventions to improve Fitness for Work from a Fatigue Management perspective.
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