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Intelligent Interruption Management System to Enhance Safety and Performance in Complex Surgical and Robotic Procedures

  • Roger D. Dias
  • Heather M. Conboy
  • Jennifer M. Gabany
  • Lori A. Clarke
  • Leon J. Osterweil
  • David Arney
  • Julian M. Goldman
  • Giuseppe Riccardi
  • George S. Avrunin
  • Steven J. Yule
  • Marco A. Zenati
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11041)

Abstract

Procedural flow disruptions secondary to interruptions play a key role in error occurrence during complex medical procedures, mainly because they increase mental workload among team members, negatively impacting team performance and patient safety. Since certain types of interruptions are unavoidable, and consequently the need for multitasking is inherent to complex procedural care, this field can benefit from an intelligent system capable of identifying in which moment flow interference is appropriate without generating disruptions. In the present study we describe a novel approach for the identification of tasks imposing low cognitive load and tasks that demand high cognitive effort during real-life cardiac surgeries. We used heart rate variability analysis as an objective measure of cognitive load, capturing data in a real-time and unobtrusive manner from multiple team members (surgeon, anesthesiologist and perfusionist) simultaneously. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the identification of specific steps, substeps and tasks that impose low cognitive load. An interruption management system can use these low demand situations to guide the surgical team in terms of the appropriateness of flow interruptions. The described approach also enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies) or in situations that are prone to errors. An in-depth understanding of the relationship between cognitive overload states, task demands, and error occurrence will drive the development of cognitive supporting systems that recognize and mitigate errors efficiently and proactively during high complex procedures.

Keywords

Cognitive load Cardiac surgery Heart rate variability Process model 

Notes

Acknowledgements

The authors wish to acknowledge the contribution, dedication and commitment to excellence of the cardiac surgery team and operating room staff at the VA Boston Healthcare System. Research reported in this publication was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number 1R01HL126896-01A1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Roger D. Dias
    • 1
    • 2
  • Heather M. Conboy
    • 4
  • Jennifer M. Gabany
    • 2
    • 3
  • Lori A. Clarke
    • 4
  • Leon J. Osterweil
    • 4
  • David Arney
    • 2
    • 5
  • Julian M. Goldman
    • 2
    • 5
  • Giuseppe Riccardi
    • 6
  • George S. Avrunin
    • 6
  • Steven J. Yule
    • 1
    • 2
    • 7
  • Marco A. Zenati
    • 2
    • 3
  1. 1.STRATUS Center for Medical SimulationBrigham and Women’s HospitalBostonUSA
  2. 2.Harvard Medical SchoolBostonUSA
  3. 3.Division of Cardiac SurgeryVA Healthcare SystemBostonUSA
  4. 4.University of MassachusettsAmherstUSA
  5. 5.Massachusetts General HospitalBostonUSA
  6. 6.Department of Information Engineering and Computer ScienceUniversity of TrentoTrentoItaly
  7. 7.Department of SurgeryBrigham and Women’s HospitalBostonUSA

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