The effect of work hours on adverse events and errors in health care

Olds, Danielle; Clarke, Sean P.

doi:10.1016/j.jsr.2010.02.002

Cited by 153 publications

(137 citation statements)

References 29 publications

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“…The results from this study with regard to driving hour concurs with the findings of Hanowski et al, (3) with respect to non-significant differences when comparing the 10th and 11th driving hours. In the Hanowski study, which also used naturalistic data, no statistically significant increase in risk was found for the 11th driving hour when compared to the 10th driving hour.…”

Section: Discussionsupporting

confidence: 92%

“…The results from this analysis showed a statistically significant increase in SCE rate when comparing the 11th driving hour to the 1st (p=0.020) and 2nd (p=0.016) driving hours, but not when comparing to the 11th driving hour to the 10th driving hour (p=0.300). The significant effect for the comparison of the 11th driving hour to the 1st and 2nd driving hours is different than found previously by Hanowski et al, (3) which found that the 1st driving hour had a significantly higher SCE rate when compared to driving hours 2-10. However, the non-effect of the comparison between the 10th driving hour and the 11th driving hour is consistent with the previous Hanowski et al, study.…”

Section: Driving Hourscontrasting

confidence: 86%

“…(2) Additionally, unintentional lane deviations represent -driver errors.‖ While much less serious than crashes, these may reflect potential time-on-task issues. It should be noted that unintentional lane deviations were not used in the previous Hanowski et al, (3) data set. Therefore, the data set used in the current study had a larger number of SCEs available for analysis.…”

Section: Driver Performance Measuresmentioning

confidence: 99%

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The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

Blanco¹,

Hanowski²,

Olson³

et al. 2011

PsycEXTRA Dataset

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FOREWORDThe work performed under this project included a literature review of topics related to commercial motor vehicle driver fatigue (including topics of work hours, driving time, duty periods, and restart/recovery periods) published between 2006 and July 2010. The research also included an assessment of the tasks drivers perform in a typical workday. In addition, analyses were conducted to determine the impact of driving hours, work hours, and breaks on driving performance. NOTICEThis document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for its contents or the use thereof.The contents of this Report reflect the views of the contractor, who is responsible for the accuracy of the data presented herein. The contents do not necessarily reflect the official policy of the Department of Transportation.This Report does not constitute a standard, specification, or regulation.The United States Government does not endorse products or manufacturers named herein. Trade or manufacturers' names appear herein only because they are considered essential to the objective of this document. Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers' operating hours. Besides assessing activities performed in the 14-hour workday, the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks was investigated. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data. The assessment of the drivers' workday determined that, on average, drivers spent 66 percent of their shift driving, 23 percent in non-driving work, and 11 percent resting. Analyses on driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14-hour workday, SCE risk was found to increase. The finding from the workday characterization that drivers spent approximately 23 percent of their workday performing non-driving work provides a possible explanation for this time-on-task effect across work hours. Breaks from driving were found to be beneficial in reducing SCEs (during 1-hour window after a break) and were effective to counteract the negative effects of time-on-task. TECHNICAL REPORT DOCUMENTATION PAGE17.

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Section: Discussionsupporting

confidence: 92%

Section: Driving Hourscontrasting

confidence: 86%

Section: Driver Performance Measuresmentioning

confidence: 99%

See 1 more Smart Citation

The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

Blanco¹,

Hanowski²,

Olson³

et al. 2011

PsycEXTRA Dataset

View full text Add to dashboard Cite

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“…There are research studies linking excessive workload to increasing errors, for example, nurses working shifts longer than 12 h or for more than 40 h per week (Olds and Clarke 2010;Rogers et al 2004) and interns working 'frequent shifts of 24 h or more' (Landrigan et al 2004). In the aviation industry, workload as flight time limitation has been addressed since 1944, with harmonised minimum European criteria from 2008 and consideration for human performance throughout the 24-h period ('Window of Circadian Low'; European Cockpit Association 2007).…”

Section: Resources (64%)mentioning

confidence: 99%

More holes than cheese. What prevents the delivery of effective, high quality and safe health care in England?

et al. 2016

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What prevents the delivery of effective, high quality and safe health care in the National Health Service (NHS) in England? This paper presents 760 challenges which 330 NHS staff reported as preventing the delivery of effective, high quality and safe care. Some problems have been known for over 25 years (staff shortages, finance and patient complexity) but other challenges raise questions about the commitment of the NHS to patient and staff safety. Practitioner Summary: 760 challenges to the quality, effectiveness and safety of health care were identified at Human Factors/Ergonomics taster workshops in England. These are used to challenge health care providers to think about a Human Factors Integration (HFI systems) approach for safety, well-being and performance for all people involved in providing and receiving health care.

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“…Fatigue has been associated with an increased risk of injury, medical error or adverse events [2] and a decreased quality of life [3]. Physicians working in the Emergency Departments (EDS) are particularly vulnerable to fatigue-related risk.…”

Section: Introductionmentioning

confidence: 99%

Fatigue-related risk management in the emergency department: a focus-group study

et al. 2018

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Fatigue has major implications on both patient safety and healthcare practitioner's well-being. Traditionally, two approaches can be used to reduce fatigue-related risk: reducing the likelihood of a fatigued operator working (i.e. fatigue reduction), or reducing the likelihood that a fatigued operator will make an error (i.e. fatigue proofing). Recent progress mainly focussed on fatigue reduction strategies such as reducing work hours. Yet it has to be recognized that such approach has not wholly overcome the experience of fatigue. Our purpose is to investigate individual proofing and reduction strategies used by emergency physicians to manage fatigue-related risk. 25 emergency physicians were recruited for the study. Four focus groups were formed which consisted of an average of six individuals. Qualitative data were collected using a semi-structured discussion guide unfolding in two parts. First, the participants were asked to describe how on-the-job fatigue affected their efficiency at work. A mind map was progressively drawn based upon the participants' perceived effects of fatigue. Second, participants were asked to describe any strategies they personally used to cope with these effects. We used inductive qualitative content analysis to reveal content themes for both fatigue effects and strategies. Emergency physicians reported 28 fatigue effects, 12 reduction strategies and 21 proofing strategies. Content analysis yielded a further classification of proofing strategies into self-regulation, task re-allocation and error monitoring strategies. There is significant potential for the development of more formal processes based on physicians' informal strategies.

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The effect of work hours on adverse events and errors in health care

Cited by 153 publications

References 29 publications

The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

The Impact of Driving, Non-Driving Work, and Rest Breaks on Driving Performance in Commercial Motor Vehicle Operations

More holes than cheese. What prevents the delivery of effective, high quality and safe health care in England?

Fatigue-related risk management in the emergency department: a focus-group study

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