Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors
Cardiac surgery is one of the most complex specialties in medicine, akin to a complex sociotechnical system. Patient outcomes are vulnerable to surgical flow disruptions (SFDs), a source of preventable harm. Healthcare providers’ (HCPs) sympathetic activation secondary to emotional states represent...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Book Chapter |
| Language: | English |
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Springer Nature
2021
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| Online Access: | https://hdl.handle.net/10356/152452 |
| _version_ | 1824453356944359424 |
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| author | Kennedy-Metz, Lauren R. Bizzego, Andrea Dias, Roger D. Furlanello, Cesare Esposito, Gianluca Zenati, Marco A. |
| author2 | C. Stephanidis |
| author_facet | C. Stephanidis Kennedy-Metz, Lauren R. Bizzego, Andrea Dias, Roger D. Furlanello, Cesare Esposito, Gianluca Zenati, Marco A. |
| author_sort | Kennedy-Metz, Lauren R. |
| collection | NTU |
| description | Cardiac surgery is one of the most complex specialties in medicine, akin to a complex sociotechnical system. Patient outcomes are vulnerable to surgical flow disruptions (SFDs), a source of preventable harm. Healthcare providers’ (HCPs) sympathetic activation secondary to emotional states represent an underappreciated source of SFDs. This study’s objective was to demonstrate the feasibility of detecting elevated sympathetic nervous system (SNS) activity as a proxy for emotional distress associated with a medication error using heart rate variability (HRV) analysis. After obtaining informed consent, audio/video and HRV data were captured intraoperatively during cardiac surgery from multiple HCPs. Following a critical medication administration error by the anesthesiologist in-training, the attending anesthesiologists’ recorded HRV data was analyzed using pyphysio, an open-source signal analysis package, to identify events precipitating this near-miss event. We considered elevated low-frequency/high-frequency (LF/HF) HRV ratio (normal value <2) as a primary indicator of SNS activity and emotional distress. A heightened SNS response by the attending anesthesiologist, observed as an LF/HF ratio value of 3.39, was detected prior to the near-miss event. The attending anesthesiologist confirmed a state of significant SNS activity/distress induced by task-irrelevant environmental factors, which led to a temporarily ineffective mental model. Qualitative analysis of audio/video recordings revealed that SNS activation coincided with an argument over operating room management causing SFD. This preliminary study confirms the feasibility of recognizing potentially detrimental psychophysiological states during cardiac surgery in the wild using HRV analysis. To our knowledge, this is the first case demonstrating SNS activation coinciding with self-reported and observable emotional distress during live surgery using HRV. Irrespective of the HCP’s expertise, transient but intense emotional changes may disrupt attention processes leading to SFDs and preventable errors. This work supports the possibility to detect real-time SNS activation, which could enable interventions to proactively mitigate errors. Additional studies on our large database of surgical cases are underway to confirm this observation. |
| first_indexed | 2024-10-01T07:59:04Z |
| format | Book Chapter |
| id | ntu-10356/152452 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:59:04Z |
| publishDate | 2021 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | ntu-10356/1524522023-03-11T20:21:48Z Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors Kennedy-Metz, Lauren R. Bizzego, Andrea Dias, Roger D. Furlanello, Cesare Esposito, Gianluca Zenati, Marco A. C. Stephanidis M. Antona S. Ntoa School of Social Sciences University of Trento, Italy Social sciences::Psychology Cardiac Surgery Cognitive Engineering Neuroergonomics Emotion Recognition Heart Rate Variability Cardiac surgery is one of the most complex specialties in medicine, akin to a complex sociotechnical system. Patient outcomes are vulnerable to surgical flow disruptions (SFDs), a source of preventable harm. Healthcare providers’ (HCPs) sympathetic activation secondary to emotional states represent an underappreciated source of SFDs. This study’s objective was to demonstrate the feasibility of detecting elevated sympathetic nervous system (SNS) activity as a proxy for emotional distress associated with a medication error using heart rate variability (HRV) analysis. After obtaining informed consent, audio/video and HRV data were captured intraoperatively during cardiac surgery from multiple HCPs. Following a critical medication administration error by the anesthesiologist in-training, the attending anesthesiologists’ recorded HRV data was analyzed using pyphysio, an open-source signal analysis package, to identify events precipitating this near-miss event. We considered elevated low-frequency/high-frequency (LF/HF) HRV ratio (normal value <2) as a primary indicator of SNS activity and emotional distress. A heightened SNS response by the attending anesthesiologist, observed as an LF/HF ratio value of 3.39, was detected prior to the near-miss event. The attending anesthesiologist confirmed a state of significant SNS activity/distress induced by task-irrelevant environmental factors, which led to a temporarily ineffective mental model. Qualitative analysis of audio/video recordings revealed that SNS activation coincided with an argument over operating room management causing SFD. This preliminary study confirms the feasibility of recognizing potentially detrimental psychophysiological states during cardiac surgery in the wild using HRV analysis. To our knowledge, this is the first case demonstrating SNS activation coinciding with self-reported and observable emotional distress during live surgery using HRV. Irrespective of the HCP’s expertise, transient but intense emotional changes may disrupt attention processes leading to SFDs and preventable errors. This work supports the possibility to detect real-time SNS activation, which could enable interventions to proactively mitigate errors. Additional studies on our large database of surgical cases are underway to confirm this observation. Accepted version 2021-08-16T01:13:09Z 2021-08-16T01:13:09Z 2020 Book Chapter Kennedy-Metz, L. R., Bizzego, A., Dias, R. D., Furlanello, C., Esposito, G. & Zenati, M. A. (2020). Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors. C. Stephanidis, M. Antona & S. Ntoa (Eds.), HCI International 2020 – Late Breaking Poster: 22nd International Conference, HCII 2020 (pp. 402-408). Springer Nature. 978-3-030-60699-2 https://hdl.handle.net/10356/152452 10.1007/978-3-030-60700-5_51 2-s2.0-85097112040 402 408 en HCI International 2020 – Late Breaking Poster: 22nd International Conference, HCII 2020 © 2020 Springer Nature Switzerland AG. All rights reserved. This book chapter is made available with permission of Springer Nature Switzerland AG. application/pdf Springer Nature |
| spellingShingle | Social sciences::Psychology Cardiac Surgery Cognitive Engineering Neuroergonomics Emotion Recognition Heart Rate Variability Kennedy-Metz, Lauren R. Bizzego, Andrea Dias, Roger D. Furlanello, Cesare Esposito, Gianluca Zenati, Marco A. Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title | Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title_full | Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title_fullStr | Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title_full_unstemmed | Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title_short | Feasibility of healthcare providers' autonomic activation recognition in real-life cardiac surgery using noninvasive sensors |
| title_sort | feasibility of healthcare providers autonomic activation recognition in real life cardiac surgery using noninvasive sensors |
| topic | Social sciences::Psychology Cardiac Surgery Cognitive Engineering Neuroergonomics Emotion Recognition Heart Rate Variability |
| url | https://hdl.handle.net/10356/152452 |
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