0218 Biomathematical Modeling Predicts Fatigue Risk in General Surgery Residents

Abstract

Introduction Fatigue and its effects on performance have long been a concern in medicine. Evidence exists that current duty-hour restrictions for resident trainees have a limited impact on physician wellbeing and patient safety, prompting renewed efforts to address this threat. In this study, sleep patterns of general-surgery residents were used to optimize a biomathematical model of performance for use as a tool for fatigue risk management with residents. Methods General surgery residents based at a multi-hospital, general surgery residency program were approached for participation in this study. Enrolled residents wore actigraph devices for 8 weeks and completed subjective sleep assessments. Sleep data and shift schedules were then input into the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model to assess predicted cognitive performance. Performance was compared to an “effectiveness” level of 77 (equivalent to a blood-alcohol content of 0.05g/dL). Eight hours of sleep debt was considered “below reservoir criteria”. Results Sleep actigraphy data was collected from 22 general surgery residents. Modeling results showed that as shift lengths increased, effectiveness scores generally decreased, and the time spent below criterion (77) increased. Additionally, 11.13% of time on shift was below the effectiveness criterion and 42.7% of shifts included time spent below the reservoir criterion. Adjustments to the sleep prediction were made based on actual sleep, and performance predictions from actual sleep and the adjusted model were significantly correlated (p<.0001). Conclusion Despite adherence to national standards limiting work hours, current surgical resident sleep patterns and shift schedules create concerning levels of fatigue. This study illustrates how biomathematical fatigue models can predict resident physician sleep patterns and performance. Modeling represents a novel and important tool for medical educators seeking to create shift schedules that maintain physician preparedness and minimize fatigue risk. Support N/A

Addressing fatigue in medical residents with biomathematical fatigue modeling

“… 39 A recent line of research by our group has focused on modifying a biomathematical model of fatigue based on residents’ own sleep patterns with the intent to create schedule mitigations which are tailored to the needs of the medical resident. These articles by Schwartz et al 40 , 41 and Devine et al 42 demonstrate the utility of fatigue modeling to identify areas of fatigue risk and evaluate how schedule changes could impact fatigue and performance. Devine et al, characterized the trends and patterns in medical resident sleep using actigraph‐collected sleep data over two months.…”

“…Both Schwartz et al papers modeled resident schedules to assess their performance based on when and how long they worked. However, in the second paper, 41 they used the exact sleep data from Devine et al to adjust the model so that estimated sleep closely matched actual resident sleep. Performance data will best represent residents when it is based off of estimated sleep times closely matched to actual sleep times.…”

Nigerian Surgical Trainees’ Work Schedule: It is Time for a Change!

“…Sleep deprivation and overwork have been shown to positively correlate with decreased job satisfaction, reduced job performance, stress, depression, impaired cognition, reduced quality of life, and in the extreme, mortality amongst residents [4–6]. In October 2014, the sudden deaths of three doctors in two tertiary hospitals in Beijing, China, within a 2‐week period, were widely reported in the media.…”

“…Cumulative fatigue from overwork and inadequate sleep, not only adversely affect the health and wellbeing of residents, but also jeopardize patients’ safety [7]. Fatigued surgical residents exhibit reduced levels of alertness and technical dexterity during procedures, increasing the risks of operative complications [6]. This is concerning, and particularly so, as medical errors are a leading cause of death in patient care [8].…”