Decision fatigue in the Emergency Department: How does emergency physician decision making change over an eight-hour shift?

Zheng, Bo; Kwok, Edmund; Taljaard, Monica; Nemnom, Marie‐Joe; Stiell, Ian G.

doi:10.1016/j.ajem.2019.12.020

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…Additionally, the fact that 75% of participants have previously conducted or participated in triage processes may affect this invariability. This corresponds with comparable data presented by Zheng et al [ 28 ]. The team analysed consultations and CT (computed tomography) orders over shifts in the emergency department and observed no decrease in consultations and admissions, concluding that decision fatigue does not occur in 8-h shifts at their emergency department [ 28 ].…”

Section: Discussionsupporting

confidence: 93%

“…This corresponds with comparable data presented by Zheng et al [ 28 ]. The team analysed consultations and CT (computed tomography) orders over shifts in the emergency department and observed no decrease in consultations and admissions, concluding that decision fatigue does not occur in 8-h shifts at their emergency department [ 28 ]. By contrast, Häusser et al showed that sleep deprivation might result in a significant increase in WoA in estimation experiments [ 18 ].…”

Section: Discussionsupporting

confidence: 93%

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The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

Laxar,

Eitenberger,

Maleczek

et al. 2023

BMC Med

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Background During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking. Methods Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians’ second rating (i.e., higher weight-on-advice). Results The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5–5.5), explaining median 7 (IQR 5.5–7.5), p = 0.007). Conclusions Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0–0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a “meeting halfway” approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 93%

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

Laxar,

Eitenberger,

Maleczek

et al. 2023

BMC Med

View full text Add to dashboard Cite

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“…Specifically, the scan rates decreased by 3.6% and 2% as the shift progressed. 14 Nonetheless, they concluded that the EP's judgments regarding patient disposition remained consistent throughout the shift. After assessing the EPs for signs of decision fatigue over an 8-hour duration, no discernible indications of fatigue were detected.…”

Section: Discussionmentioning

confidence: 99%

“…After assessing the EPs for signs of decision fatigue over an 8-hour duration, no discernible indications of fatigue were detected. 14 Strobel et al similarly reported that although imaging decisions by EPs were influenced by the duration of their shifts, these variations did not impact the rate of subsequent “bounce backs” to the ED. 15 Additionally, Matz et al found that while there was a non-significant inclination toward increased scan usage by individual EPs on high-volume days compared with low-volume days, there were no significant changes in the overall rate of scans requested by EP on high-volume days ( p -value: 0.25).…”

Section: Discussionmentioning

confidence: 99%

Impact of Fatigue on Emergency Physicians’ Decision-making for Computed Tomographic Scan Requests and Inpatient Referrals: An Observational Study from a Tertiary Care Medical Centre of the Sultanate of Oman

Hazra,

Al-Arimi,

Al-Alawi

2023

Indian Journal of Critical Care Medicine

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A bstract Objective Multiple factors contribute to decision fatigue experienced by emergency physicians (EPs). This study examines the association between decision fatigue and the frequency of computed tomographic (CT) scan requests and inpatient referrals among EPs. Methods This retrospective database analysis was done for 3 months. Scans and inpatient referral requests were coded and analyzed to assess the impact of physician fatigue on decision-making. Subsequently, the outcomes were evaluated. Results The majority of patients ( n = 481; 51.1%) had a CT brain request. Among these requests, the morning shift (8:00 a.m.–3:00 p.m.) accounted for the highest number ( n = 400; 42.5%), followed by the evening shift (3:00–11:00 p.m.) ( n = 345; 36.7%). Approximately one-third of the patients ( n = 301; 31.9%) had positive CT scan findings. Statistical analysis comparing the first and the second halves of each shift did not reveal significant variations in the percentage of negative CT results ( p -value: 0.093). Inpatient referral was necessary for over half of the patients ( n = 1,048; 52.7%), and the majority of these referrals ( n = 778; 74.2%) were deemed necessary for treatment under various surgical or medical specialties. There was a statistically significant difference in the proportion of negative inpatient referrals between the first and the second halves of the afternoon shift ( p -value < 0.001). Conclusions Fatigue among EPs was observed, leading to more frequent consultations without inpatient admission during the latter half of the afternoon shift. However, the study found no significant impact of decision fatigue on CT scan decision-making. How to cite this article Al-Arimi AH, Hazra D, Al-Alawi AKA. Impact of Fatigue on Emergency Physicians’ Decision-making for Computed Tomographic Scan Requests and Inpatient Referrals: An Observational Study from a Tertiary Care Medical Center of the Sultanate of Oman. Indian J Crit Care Med 2023;27(9):620–624.

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“…Correlation with error rates: Some studies have explored the relationship between decision fatigue and error rates in clinical practice. They investigate whether physicians who experience higher levels of decision fatigue are more prone to making mistakes in diagnosis, treatment, or patient management [9,34].…”

Section: Studies Showing Correlationsmentioning

confidence: 99%

Decision Fatigue in Emergency Medicine: An Exploration of Its Validity

Yadav,

Rawal,

Jeyaraman

2023

Cureus

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Emergency physicians face a relentless stream of complex, high-stakes decisions in a fast-paced and dynamic environment. The concept of decision fatigue, a phenomenon characterized by a decline in the quality of decision-making after a long sequence of choices, has garnered increasing attention within healthcare. Several investigations show that the number and complexity of decisions made during prolonged shifts correlate with increased self-reported fatigue; however, the effect on clinical decision quality is uncertain. Conversely, a subset of studies found no clear relationship between decision fatigue and errors in clinical judgment. Importantly, some researchers argue that decision fatigue may be mitigated by factors such as experience, training, and support systems. This narrative review highlights the existing literature on decision fatigue among emergency physicians and explores whether this concept holds as a valid concern or remains a myth in the context of their practice.

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Decision fatigue in the Emergency Department: How does emergency physician decision making change over an eight-hour shift?

Cited by 9 publications

References 19 publications

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

Impact of Fatigue on Emergency Physicians’ Decision-making for Computed Tomographic Scan Requests and Inpatient Referrals: An Observational Study from a Tertiary Care Medical Centre of the Sultanate of Oman

Decision Fatigue in Emergency Medicine: An Exploration of Its Validity

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