Understanding Emergency Medicine Physicians Multitasking Behaviors Around Interruptions.

MedStar author(s):
Citation: Academic Emergency Medicine. 2018 Jun 11PMID: 29888519Institution: MedStar Institute for Innovation | MedStar Washington Hospital CenterForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: IN PROCESS -- NOT YET INDEXEDYear: 2018Local holdings: Available online from MWHC library: 1997 - present, Available in print through MWHC library:2005-2007ISSN:
  • 1069-6563
Name of journal: Academic emergency medicine : official journal of the Society for Academic Emergency MedicineAbstract: BACKGROUND: Interruptions can adversely impact human performance, particularly in fast-paced and high-risk environments such as the emergency department (ED). Understanding physician behaviors before, during, and after interruptions is important to the design and promotion of safe and effective workflow solutions. However, traditional human factors based interruption models do not accurately reflect the complexities of real-world environments like the ED and may not capture multiple interruptions and multitasking.CONCLUSION: Using this framework provides a more detailed description of the types of physician behaviors in complex environments. Understanding the different types of interruption and resumption patterns, which may have a different impact on performance, can support the design of interruption mitigation strategies. This article is protected by copyright. All rights reserved.Copyright This article is protected by copyright. All rights reserved.METHODS: We present a more comprehensive framework for understanding interruptions that is composed of three phases, each with multiple levels: Interruption Start Transition, Interruption Engagement, and Interruption End Transition. This three-phase framework is not constrained to discrete task transitions, providing a robust method to categorize multitasking behaviors around interruptions. We apply this framework in categorizing 457 interruption episodes.RESULTS: 457 interruption episodes were captured during 36 hours of observation. The interrupted task was immediately suspended 348 (76.1%) times. Participants engaged in new self-initiated tasks during the interrupting task 164 (35.9%) times and did not directly resume the interrupted task in 284 (62.1%) interruption episodes.All authors: Fong A, Ratwani RMFiscal year: FY2018Digital Object Identifier: Date added to catalog: 2018-07-06
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Item type Current library Collection Call number Status Date due Barcode
Journal Article MedStar Authors Catalog Article 29888519 Available 29888519

Available online from MWHC library: 1997 - present, Available in print through MWHC library:2005-2007

BACKGROUND: Interruptions can adversely impact human performance, particularly in fast-paced and high-risk environments such as the emergency department (ED). Understanding physician behaviors before, during, and after interruptions is important to the design and promotion of safe and effective workflow solutions. However, traditional human factors based interruption models do not accurately reflect the complexities of real-world environments like the ED and may not capture multiple interruptions and multitasking.

CONCLUSION: Using this framework provides a more detailed description of the types of physician behaviors in complex environments. Understanding the different types of interruption and resumption patterns, which may have a different impact on performance, can support the design of interruption mitigation strategies. This article is protected by copyright. All rights reserved.

Copyright This article is protected by copyright. All rights reserved.

METHODS: We present a more comprehensive framework for understanding interruptions that is composed of three phases, each with multiple levels: Interruption Start Transition, Interruption Engagement, and Interruption End Transition. This three-phase framework is not constrained to discrete task transitions, providing a robust method to categorize multitasking behaviors around interruptions. We apply this framework in categorizing 457 interruption episodes.

RESULTS: 457 interruption episodes were captured during 36 hours of observation. The interrupted task was immediately suspended 348 (76.1%) times. Participants engaged in new self-initiated tasks during the interrupting task 164 (35.9%) times and did not directly resume the interrupted task in 284 (62.1%) interruption episodes.

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