Abstract
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.
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References
Wiegmann, D.A, ElBardissi, A.W., Dearani, J.A., Daly, R.C., Sundt III, T.M.: Disruptions in surgical flow and their relationship to surgical errors: an exploratory investigation. Surgery 142(5), 658–665 (2007)
LeBlanc, V.R., McConnell, M.M., Monteiro, S.D.: Predictable chaos: a review of the effects of emotions on attention, memory and decision making. Adv. Health Sci. Educ. 20(1), 265–282 (2014)
Mosier, K.L., Fischer, U.: The role of affect in naturalistic decision making. J. Cogn. Eng. Decis. Making 4(3), 240–255 (2010)
Dias, R.D., Ngo-Howard, M.C., Boskovski, M.T., Zenati, M.A., Yule, S.J.: Systematic review of measurement tools to assess surgeons’ intraoperative cognitive workload. Br. J. Surgery 105(5), 491–501 (2018)
Wu, A.W., Lipshutz, A.K.M., Pronovost, P.J.: Effectiveness and efficiency of root cause analysis in medicine. JAMA 299(6), 685–687 (2008)
Bizzego, A., Battisti, A., Gabrieli, G., Esposito, G., Furlanello, C.: pyphysio: a physiological signal processing library for data science approaches in physiology. SoftwareX 10, 1–5 (2019)
Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology: Heart rate variability: standards of measurement, physiological interpretation and clinical use. Eur. Heart J. 17, 354–381 (1996)
Castaldo, R., Melillo, P., Bracale, U., Caserta, M., Triassi, M., Pecchia, L.: Acute mental stress assessment via short term HRV analysis in healthy adults: a systematic review with meta-analysis. Biomed. Signal Process. Control 18, 370–377 (2015)
Dantas, E.M., et al.: Reference values for short-term resting-state heart rate variability in healthy adults: results from the Brazilian Longitudinal Study of Adult Health—ELSA-Brasil study. Psychophysiology 55(6), 1–12 (2018)
Shaffer, F., Ginsberg, J.P.: An overview of heart rate variability metrics and norms. Front. Publ. Health 5(September), 1–17 (2017)
Albayram, Y., Khan, M.M.H., Jensen, T., Buck, R., Coman, E.: The effects of risk and role on users’ anticipated emotions in safety-critical systems. In: Harris, D. (ed.) EPCE 2018. LNCS (LNAI), vol. 10906, pp. 369–388. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91122-9_31
Zenati, M.A., Kennedy-Metz, L., Dias, R.D.: Cognitive engineering to improve patient safety and outcomes in cardiothoracic surgery. Semin. Thorac. Cardiovasc. Surg. 32(1), 1–7 (2019)
Acknowledgment
This work was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health [grant number R01HL126896, PI Zenati].
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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. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2020 – Late Breaking Posters. HCII 2020. Communications in Computer and Information Science, vol 1293. Springer, Cham. https://doi.org/10.1007/978-3-030-60700-5_51
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