Quantifying Intraoperative Workloads Across the Surgical Team Roles: Room for Better Balance?

Abstract

BackgroundSurgical performance, provider health, and patient safety can be compromised when workload demands exceed individual capability on the surgical team. The purpose of this study is to quantify and compare intraoperative workload among surgical team members.MethodsObservations were conducted for an entire surgical day for 33 participating surgeons and their surgical team at one medical institution. Workload (mental, physical, case complexity, distractions, and case difficulty) was measured for each surgical team member using questions from validated questionnaires. Statistical analyses were performed with a mixed effects model.ResultsA total of 192 surgical team members participated in 78 operative cases, and 344 questionnaires were collected. Procedures with high surgeon mental and physical workload included endovascular and gastric surgeries, respectively. Ratings did not differ significantly among surgeons and residents, but scrub nurses physical demand ratings were 14–22 (out of 100) points lower than the surgeons, residents, and surgical assistants. Residents reported the highest mental workload, averaging 19–24 points higher than surgical assistants, scrub nurses, and circulating nurses. Mental and physical demands exceeded 50 points 28–45 % of the time for surgeons and residents. Workload did not differ between minimally invasive and open techniques.ConclusionThe workload questionnaires are an effective tool for quantifying intraoperative workload across the surgical team to ensure mental and physical demands do not exceed thresholds where performance may decrease and injury risk increase. This tool has the potential to measure the safety of current procedures and drive design of workload interventions.

Systematic review of measurement tools to assess surgeons' intraoperative cognitive workload

“…Despite more than 550 studies using NASA‐TLX reported in the past 20 years, few have proposed the workload redline when using this tool – a point on the scale that indicates when the workload is considered so high that it may affect human performance. A modified version of NASA‐TLX was developed and validated specifically to capture the surgical context, the Surgery Task Load Index (SURG‐TLX). In two of the reviewed studies, the NASA‐TLX questionnaire was used to capture surgeons' cognitive load over repeated training sessions, and correlated with technical performance and errors.…”

“…Only five studies (6 per cent) assessed the cognitive load of multiple operating theatre team members besides the surgeon. Team members included registered nurses (3 studies), anaesthetists (3 studies), registered nurse anaesthetists (2 studies), theatre nurses (2 studies), scrub nurses (2 studies), physician assistants (1 study), surgical technicians (2 studies), circulating nurses (1 study) and perfusionists (1 study).…”

“…The number of participants included in the reviewed studies varied from a minimum of one to a maximum of 192, totalling 2053 unique participants. Twenty-three studies ( 30,46 , circulating nurses (1 study) 30 and perfusionists (1 study) 46 .…”

Interruptions in Surgery: A Comprehensive Review

“…There exist effective tools to assess quality and safety in the OR: adverse event measurement allows identification of potential errors in the surgical process, 3 workload and stress assessment by validated scales points out their negative impact on surgical performance. 8,9,10 It is now accepted that errors resulting from adverse events are mainly secondary to a lack of non-technical skills (NTS). 4 NTS are divided into cognitive (situation awareness, mental readiness, assessing risks…) and interpersonal (communication, leadership, teamwork, planning…) skills.…”

Human-based dynamics of mental workload in complicated systems

“…The reason for errors, crashes, accidents and disasters made by human can be due to unbalance mental workload resulting in overload and underload situations exposing operators to approach or exceed the redlines of their performance (Xie and Salvendy, 2000[ 36 ]; Paxion et al, 2014[ 27 ]; Young et al, 2015[ 39 ]; Wascher et al, 2016[ 33 ]). On the other hand, the balance in the workload reduces the human error and increases the task performance of operators (Xie and Salvendy, 2000[ 36 ]; Yu et al, 2016[ 40 ]; Zhao et al, 2016[ 41 ]). Therefore, the concept of mental workload and mechanism of its effect on task performance in different human-machine systems is considered by practitioners and researchers in a variety of cognitive activities, such as conventional driving (Allahyari et al, 2014[ 1 ]; Hassanzadeh-Rangi et al, 2014[ 18 ]; Yan et al, 2019[ 37 ]), automated driving (Ko and Ji, 2018[ 22 ]), train driving (Balfe et al, 2017[ 6 ]), nuclear power plants (Choi et al, 2018[ 12 ]), advanced surgery programs (Cavuoto et al, 2017[ 9 ]), air traffic monitoring (Dasari et al, 2017[ 14 ]), control rooms (Melo et al, 2017[ 24 ]), workplace activities (Chen et al, 2017[ 11 ]), information technologies (Buettner, 2017[ 7 ]) and other complex human-machine systems (Xiao et al, 2015[ 35 ]).…”