The Human Factors Analysis Classification System (HFACS) Applied to Health Care

Diller, Thomas; Helmrich, George; Dunning, Sharon; Cox, Stephanie; Buchanan, April O.; Shappell, Scott A.

doi:10.1177/1062860613491623

Cited by 139 publications

(140 citation statements)

References 18 publications

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“…16 Following Reason's categories, the never events were described under four categories: (1) unsafe actions, (2) preconditions for unsafe actions, (3) oversight/supervisory factors, and (4) organizational influences (Figure 1). Unsafe actions include issues with protocol compliance (e.g.…”

Section: Methodsmentioning

confidence: 99%

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Surgical never events and contributing human factors

Thiels

Lal

Nienow

et al. 2015

Surgery

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Introduction We report the first prospective analysis of human factors elements contributing to invasive procedural never events using a validated Human Factors Analysis and Classification System (HFACS). Methods From 8/2009 - 8/2014 surgical and invasive procedural “Never Events” (retained foreign object, wrong site/side procedure, wrong implant, wrong procedure) underwent systematic causation analysis promptly after the event. Contributing human factors were categorized using Reason's 4 levels of error causation and 161 HFACS subcategories (nano-codes). Results During the study approximately 1.5 million procedures were performed and 69 never events were identified. A total of 628 contributing human factors nano-codes were identified. Action-based errors (n=260) and preconditions to actions (n=296) accounted for the majority of the nano-codes across all four types of events, with individual cognitive factors contributing half of the nano-codes. The most common action nano-codes were confirmation bias (n=36) and failed to understand (n=36). The most common pre-condition nano-codes were channeled attention on a single issue (n=33) and inadequate communication (n=30). Conclusion Targeting quality and system improvement interventions addressing cognitive factors and team resource management as well as perceptual biases may reduce errors and further improve patient safety. These results delineate targets to further reduce never events from our healthcare system.

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Section: Methodsmentioning

confidence: 99%

“…14 The HFACS methodology has been validated across several industries 15 , including medicine. 16,17 In this study, we review the results from the prospectively applied HFACS methodology to surgical and procedural never events at our institution…”

Section: Introductionmentioning

confidence: 99%

Surgical never events and contributing human factors

Thiels

Lal

Nienow

et al. 2015

Surgery

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“…Too often, the causes identified by root cause analysis are nonspecific, and therefore cannot be used to develop a realistic correction plan. Lastly, there is no standardized nomenclature that would permit analysis of errors that recur across the organization [6&&]. …”

Section: Reducing the Risk Of Errorsmentioning

confidence: 99%

Threat and error management for anesthesiologists

Ruskin

Stiegler

Park

et al. 2013

Current Opinion in Anaesthesiology

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Purpose of review Patient care in the operating room is a dynamic interaction that requires cooperation among team members and reliance upon sophisticated technology. Most human factors research in medicine has been focused on analyzing errors and implementing system-wide changes to prevent them from recurring. We describe a set of techniques that has been used successfully by the aviation industry to analyze errors and adverse events and explain how these techniques can be applied to patient care. Recent findings Threat and error management (TEM) describes adverse events in terms of risks or challenges that are present in an operational environment (threats) and the actions of specific personnel that potentiate or exacerbate those threats (errors). TEM is a technique widely used in aviation, and can be adapted for the use in a medical setting to predict high-risk situations and prevent errors in the perioperative period. A threat taxonomy is a novel way of classifying and predicting the hazards that can occur in the operating room. TEM can be used to identify error-producing situations, analyze adverse events, and design training scenarios. Summary TEM offers a multifaceted strategy for identifying hazards, reducing errors, and training physicians. A threat taxonomy may improve analysis of critical events with subsequent development of specific interventions, and may also serve as a framework for training programs in risk mitigation.

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“…Data from several studies, [8][9][10][11][12][13][14][15][16] suggest that the HFACS system can be consistently applied by different users.…”

Section: Introductionmentioning

confidence: 99%

“…practicalradonc.org). The human factors analysis and classification system (HFACS) model is perhaps the most widely used method, having been applied in civil and military aviation, 8,9 helicopter maintenance, 10 coal mining, 11 rail transportation, 12 maritime, 13 construction, 14 health care, 15 and road transportation. 16 The HFACS was developed by Shappell and Wiegmann, 17 based on Reason's "Swiss cheese model" (Fig 1) of human error causation of latent and active.…”

Section: Introductionmentioning

confidence: 99%