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M. El Hechi and H. M. A. Kaafarani
Surgical Apgar Score
In 2007, Gawande etal. derived and validated a 10-point Surgical Apgar Score
which was developed using three intraoperative parameters that were independent
predictors of 30-day major complications: estimated blood loss (EBL), lowest heart
rate (HR), and the lowest mean arterial pressure (MAP) during the operation. The
beta coefcients of the variables were used to weigh the points allocated to each
variable in a 10-point score. The score effectively predicted major postoperative
complications within 30 days of both general and vascular surgery [62]. The
Surgical Apgar Score successfully integrated components of patient susceptibility,
procedure complexity, and operative performance to provide a measure of immediate postoperative condition and prognostication [63]. While the Surgical Apgar
Score was potentially useful as a reporting mechanism for iAE, it was not capable
of detecting and properly classifying iAEs.
A major challenge that existed in detecting and reporting of iAEs included considerable variability in reporting iAEs in operative notes. Even when reported in
mortality and morbidity conferences, the rate of capture of their occurrences was
very low [64, 65]. This was mainly due to the absence of a clear denition for what
constitutes an iAE or the surgeon’s personal interpretation of the clinical signicance of the incident [60]. A compelling need to generate not only risk-adjusted but
also severity-adjusted rates of iAEs was present, as from a patient transparency
perspective, severity-adjusted rates of iAEs are more relevant than the crude incidence of such events.
Surgical Intraoperative Adverse Event Classification Scheme
In 2013, using a methodology that combined clinically and administratively generated data and the 15th Patient Safety Indicator (accidental puncture or laceration)
algorithms created by the AHRQ, the Massachusetts General Hospital and Harvard
Medical School developed a six-point severity classication scale for iAE
(Table12.3) [66]. The classication tool was created to be a quality assessment and
improvement tool at the hospital, regional, and national levels, as opposed to being
a tool to screen for iAEs. To maintain objectivity and ease of identication and
reproducibility, the scale severity classication was based on the extent of therapeutic intervention needed to mitigate its effect [66]. On validation, the scale had excellent inter-rater reliability. It also had external validity: high-grade iAEs were
correlated with higher risks of surgical site infections, systemic sepsis, failure to
wean off the ventilator, and a prolonged postoperative length of stay, compared to
lower grade iAEs. A subsequent study by Bohnen etal. [67] quantied the impact
of iAEs on postoperative outcome, suggesting that the risk of 30-day mortality is
more than tripled and the risk of 30-day complications is more than doubled after
the occurrence of an iAE, even when that iAE is addressed intraoperatively.
Furthermore, an anonymous survey of Boston surgeons in 2017 reported that most
surgeons encountered one to six iAEs in the past 12months of practice. In that same
study, approximately half the surgeons pointed out the lack of a standardized iAE
reporting system, the absence of a clear iAE denition, and fear of litigation as the
three most important barriers to iAE reporting [68]. Thus, the true incidence of iAEs
12 Detecting andReporting Errors, Complications, andAdverse Events
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Table 12.3 Intraoperative adverse event severity classication scheme
Class Description
I Injury requiring no repair within the same procedure (e.g., cauterization, use of
prothrombotic material, small vessel ligation)
II Injury requiring surgical repair, without organ removal or a change in the originally
planned procedure (e.g., any suture repair, patch repair)
III Injury requiring tissue or organ removal with completion of the originally planned
procedure
IV Injury requiring a signicant changea and/or incompletion of the originally planned
procedure
V Missed intraoperative injury requiring re-operation within 7days
VI Intraoperative death
Sufx T
Source: Kaafarani HM, Mavros MN, Hwabejire J, Fagenholz P, Yeh DD, Demoya M, et al.
Derivation and validation of a novel severity classication for intraoperative adverse events.
Journal of the American College of Surgeons. 2014;218(6):1120–8
May be subject to copyright.
a
Excludes minimally invasive to open conversions
Add if injury required transfusion of ≥2U blood
211
remained difcult to assess due to the lack of a standardized method for surgeons to
systematically report iAEs.
Subsequently, a prospective study assessed the incidence of iAEs through surgeon self-reporting (surgeons’ willingness to provide this information). The ndings suggested that surgeons are willing to admit and report their iAEs, evidenced
by a high response rate to the inquiries, and having a similar response rate in cases
with and without iAEs. These ndings were pleasantly surprising, given the potential medicolegal, professional, and emotional impact of reporting intraoperative
mishaps. However, there was systematic underreporting of all iAEs, especially iAEs
of low severity, with only 1in 10 of class I iAEs being self-reported. This may be
because of both the lack of a clear iAE denition and their subjective interpretation
of what is clinically insignicant, expected, or inconsequential [69].
The “black box” nature of the operating room and medicolegal and professional
impact of iAEs pose a serious challenge to accurately detecting iAEs. The aforementioned study suggested that operative report review is, in fact, more reliable
than self-reporting, but occasionally misses potentially relevant iAEs that were selfreported by surgeons, yet not documented in the chart. That being said, the true
incidence of iAEs is undoubtedly higher than either method, and the search continues for the optimal method to detect and report iAEs that is independent from the
surgeon’s willingness to self-report or the variation in operative report documentation among different surgeons [69]. Thus, the authors strongly advocate for a consistent and reliable system for iAE detection, reporting, and simultaneous robust
risk adjustment. Risk adjustment will be crucial to avoid penalizing the surgeon
willing to operate on higher risk patients. For a system to be established and ultimately improve the quality of patient care, a culture change in the world of surgery
will be necessary, and such a system will need to be conceived under the protective
umbrella of peer review to avoid medicolegal repercussions.
212
feature detection
automatically detected
further processing
Streams of image data
can be analyzed
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M. El Hechi and H. M. A. Kaafarani
Surgical image undergoes
Fig. 12.2 Computer vision utilizes mathematical techniques to analyze visual images or video
streams as quantiable features such as color, texture, and position that can then be used within a
dataset to identify statistically meaningful events such as bleeding. (Source: Hashimoto DA,
Rosman G, Rus D, Meireles OR.Articial intelligence in surgery: promises and perils. Annals of
surgery. 2018;268(1):70–6. May be subject to copyright)
Relevant features can be
Features undergo
Theoretical solutions to this matter include having a peer surgeon review video
recordings of procedures to identify iAEs. However, this is costly from both an
equipment perspective and the time needed for trained personnel [69]. Alternatively,
this could prove cost-effective and accurate in the near future with the promise of
articial intelligence (AI) and the advent of one of its core subelds, image recognition, and computer vision [70]. Computer vision describes machine understanding
of images and videos, where advances have resulted in machines achieving humanlevel capabilities in object and scene recognition [71]. One important healthcarerelated application of computer vision includes image acquisition and interpretation
in image-guided surgery [72]. For instance, real-time analysis of laparoscopic video
yielded 92.8% accuracy in automated identication of the steps of a sleeve gastrectomy, and even made notice of missing or unexpected steps [73]. Videos contain a
wealth of actionable data, where it is estimated that 1minute of high-denition
surgical video contains 25 times the amount of data found in a high-resolution computed tomography image [74–76].
Thus, although predictive video analysis is in its infancy, such work provides
proof-of-concept that AI can be leveraged to process massive amounts of surgical
data to identify or even predict the occurrence of iAEs in real time (Fig.12.2). Until
this technology becomes readily available and implementable, the authors believe
that a simple measure, such as adding a “Did an iAE occur?” question to the “time
out” phase at the end of a surgical procedure is a good start if a standardized iAE
denition is used [69].
Conclusion
In the interest of our patients, transparency of surgical errors, including iAEs, is
important in a culture that embodies patient safety and aims at understating and
improving the shortcomings and limitations of the care we deliver today. Seeking
systems of adverse events reporting that are accurate, risk-adjusted, severityadjusted, and reasonably automated carries the premise of revolutionizing the quality of care we provide as surgeons.
12 Detecting andReporting Errors, Complications, andAdverse Events
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213
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M. El Hechi and H. M. A. Kaafarani
Simulation Technical Training toImprove
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Safety intheOR
RanaM.Higgins andMarcA.de Moya
Introduction
Simulation is an invaluable part of training and continued professional development
in health care, especially within surgery. It provides helpful training for both technical and non-technical skills. Through the development of skills, patient safety and
efciency in the operating room can be optimized [1]. The purpose of simulation is
to recreate real-world scenarios through an external device or setup. Through this
system, the trainer controls the learning environment by establishing specic goals
of the simulation training and providing feedback [2]. This leads to deliberate practice, which is necessary for skill acquisition and mastery even as it applies to teams.
Within the simulation environment, delity represents the realism of the simulation model. Fidelity is multi-dimensional, incorporating environment, equipment,
and psychological components [2]. Environment delity addresses the extent to
which the simulator replicates the various senses, such as motion and vision, of the
actual environment. Equipment delity addresses the extent to which the appearance of the simulator replicates the actual environment. Psychological delity highlights the extent to which the trainee perceives the simulated environment to be
realistic and representative of the actual environment. These three components can
overlap to varying degrees within each simulation environment.
Three primary categories of simulation vary in the degree to which they incorporate environment, equipment, and psychological delity (Table13.1) [2]. The rst
category of simulation is case studies and role plays, which serve as ctional examples in an attempt to reinforce specic training material. This type of simulation is
13
R. M. Higgins
Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
M. A. de Moya (*)
Division of Trauma and Acute Care Surgery, Medical College of Wisconsin,
Milwaukee, WI, USA
e-mail: mdemoya@mcw.edu
© Springer Nature Switzerland AG 2024
J. J. Hoballah et al. (eds.), Principles of Perioperative Safety and Efciency,
https://doi.org/10.1007/978-3-031-41089-5_13
217
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Table 13.1 Categories of simulation-based training
Teamwork
Simulation type
Case studies/
role plays
Part-task
trainers
Full-mission
simulations
competencies Primary strengths
Knowledge,
attitudes
Knowledge,
skills
Knowledge,
skills
Low cost, positive trainee
reactions
Low cost, distraction-free
environment
Can simulate rare (but
critical) tasks in a safe
environment
R. M. Higgins and M. A. de Moya
Primary weaknesses
Few opportunities for skills
practice
No opportunity for dual
task practice
High cost, currently
limited to a few medical
specialties
typically low cost, with low environment, equipment, and psychological delity. A
second category of simulation is partial-task trainers, which include examples such
as standardized patients and laparoscopic trainers. The purpose of this type of simulation is to break down a complex task into parts. The equipment, environment, and
psychological delity for this type of simulation are all medium. The nal type of
simulation is full-mission simulation, which mimics all the environmental complexities at once. All types of delity are high for this simulation, given that trainees
can practice skills under the most realistic of scenarios, but it does require the highest cost of all three types. Each type of simulation has its role, depending on the
goals of training identied, the purpose of the simulated environment, the available
resources, and the number of people being trained.
Simulation is used to develop both technical and non-technical skills in the operating room. The skills that must be trained and developed vary depending on the
role of the provider in the operating room. Surgeons, anesthesiologists, nurses,
scrub techs, residents, and medical students all play a different role in the operating
room, and therefore simulation training should vary depending on the skill and provider being trained. The ve primary skills that improve surgical outcomes that can
be trained in a simulated environment are:
1. Team-based competency
2. Operating room re safety
3. Infection prevention and control
4. Crisis resource management (CRM)
5. Technical skills training
Team-Based Competency
Team-based competency is a critical skill in the high-risk environment of the operating room. A team is dened as a group of individuals who perform a work-related
task, interact with one another in a dynamic fashion, and share a common goal [3].
It is critically important that all members of the teamwork together to achieve the
common goal, and teamwork is dened as the behaviors that allow for effective and
efcient achievement of this goal. The ve most important behaviors that facilitate
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teamwork are: (1) team leadership, (2) team orientation, (3) mutual performance
monitoring, (4) backup behaviors, and (5) adaptability [2]. Ensuring these behaviors
are optimized in the operating room environment can be challenging, with various
team members and their differing roles, training, and responsibilities. Mill etal. [4]
identied discrepancies between surgeons’ perception of the team operating room
environment in comparison to nurses and anesthesiologists. Surgeons perceived a
stronger culture of safety, communication, and teamwork than either nurses or anesthesiologists. These discrepancies highlight that optimizing teamwork is important
to ensure a safe and efcient operating room environment for patients.
On a national level, the Department of Defense and the Agency for Healthcare
Research and Quality developed a program to improve the quality, safety, and efciency of health care through teamwork. The Team Strategies and Tools to Enhance
Performance and Patient Safety (TeamSTEPPS™) is the program that was developed and released in 2006 and has been implemented in numerous hospitals across
the United States [5]. The curriculum focuses on four competencies including leadership, situational monitoring, mutual support, and communication. Although available as a national program, many facilities have adopted their own institution-based
training programs, focusing on simulation and the development of team-based competency. When applied specically within the operating room environment, the
application of TeamSTEPPS™ has led to a reduction in the occurrence of retained
foreign bodies. Prior to the application of the program, retained foreign bodies were
occurring every 16days, an interval which increased to an average of 69days after
its implementation [6]. Additional implementation sites of TeamSTEPPS™ identied improvements in the quantity and quality of presurgical procedure briengs, as
well as teamwork behaviors during operative cases [7].
One institutional simulation approach to develop team-based competency
focuses on case studies and role plays. Stewart-Parker etal. [8] developed Surgical
Teamworking in Emergency and Acute Medical Situations (S-TEAMS), a one-day
course consisting of lectures, case studies, and simulated patient scenarios focusing
on communication strategies and situational awareness. The three learning objectives of the course are situational awareness, anticipation and planning, and effective communication strategies. The individuals participating in this course are
typically nurses, scrub techs, surgeons, and anesthesiologists. Self-assessments
identied that after the course, 55% of participants felt an increased condence to
speak up in difcult situations. Six months after the course, 94% of course participants felt the course directly improved patient safety. This study highlights that a
course focusing on case studies in conjunction with simulated scenarios provides a
strong foundation of skills for operating room staff regarding team communication
and, ultimately, patient safety.
Another case study-based simulation training from Man etal. [9] focused on crew
resource management (CRM). CRM was a workshop from the National Aeronautics
and Space Administration (NASA) that was created in 1979 to promote and improve
air safety. This concept has expanded across teams in various specialties, including
medicine. The pillars for CRM focus on six areas: (1) managing fatigue, (2) creating
and managing teams, (3) recognizing adverse situations, (4) cross-checking and
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