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0066 Eye tracking technology and high fidelity simulation the next generation
  1. Kirsty Harris
  1. 1Portsmouth Hospitals NHS Trust, Portsmouth, UK
  2. 2University of Portsmouth, Portsmouth, UK


Background To review how eye tracking technology data can be utilised when examining the eye gaze of the healthcare providers when monitoring a deteriorating simulated patient.

Methodology There are limited publications on high fidelity simulation and eye tracking in the healthcare setting. Wide variations in the eye-tracking data and no standard template make the analysis process impossible to compare and interpret. The analysis of how healthcare student’s eye gaze or eye fixation alters and how eye gaze changes when making a clinical assessment of a deteriorating simulated patient will be explored. Current evidence suggests, eye tracking technology has been used in laparoscopic simulation or anaesthetic airway training and has mainly concentrating on workload and fatigue.1–5

Results The expert eye gaze frequency and scan of the patient’s vital signs displayed on the monitor is reduced but the dwell time increases. In comparison the novice does the opposite i.e., focuses on the task and infrequently looks at the patient’s clinical vital signs. Patient safety is paramount and Schulz et al .2 recorded an increase in visual awareness on the patient monitor from 20% to 30% during a simulated incident.

Potential Identify, how future healthcare professionals need to trained during simulation training. Plus, do the vital sign monitors need to be switched off to encourage physical examination?


  1. Kataoka J, Sasaki M, Kanda K. Effects of mental workload on nurses’ visual behaviours during infusion pump operation. Jpn J Nurs Sci 2011;8:47–56

  2. Schulz CM, Schneider E, Fritz L, Vockeroth J, Hapfelmeier A, Brandt T, Kochs EF, Schneider G. Visual attention of an anaesthetist during simulated critical incidents. Br J Anaesth 2011;106(6):807–813

  3. Atkins MA, Tien G, Meneghetti A, Zheng B, Khan RSA. What do surgeons see: capturing and synchronising eye-gaze for surgery applications? Surg Innov. 2013;20(3):241–248

  4. Di Stasi LL, McCamy MB, Macknik SL, Manikin JA, Hooft N, Catena A. Martinez-Conde S. Saccadic eye movement metrics reflect surgical residents’ fatigue. Ann Surg 2014;259(4):824–829

  5. Henneman PL, Fisher DL, Henneman EA, Pham TA, Campbell MM, Nathanson BH. Patient identification errors are common in a simulated setting. Ann Emerg Med 2010;55(6):503–509

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