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Abbreviations
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xxiii
SCD sequential compression device
SCIP Surgical Care Improvement Project
SCORE Surgical Council on Resident Education
SDB Sleep disordered breathing
SDGs Sustainable Development Goals
SEN Simulation Education Network
SGA Supraglottic airway
SMART Specic, Measurable, Achievable, Relevant, and Timely
SOR Safe operating rooms
SP Source patient
SPSC Saudi Patient Safety Center
SSH Society for Simulation in Healthcare
SSI(s) Surgical site infection(s)
S-TEAMS Surgical Teamworking in Emergency and Acute Medical
Situations
STPC Standardization, Technology, Pharmacy / Prelled / Premixed,
and Culture
SURPASS SURgical PAtient Safety System
SV Stroke volume
SVV Stroke volume variation
TACO Transfusion-associated circulatory overload
TAP Transversus abdominus plane
TASH Trauma-associated severe hemorrhage [score]
TBSS Traumatic bleeding severity score
TEA Thoracic epidural anesthesia
TeamSTEPPS™ Team Strategies and Tools to Enhance Performance and
Patient Safety
TEG Thromboelastography
THA Total hip arthroplasty
TID Three times a day [dose]
TKA Total knee arthroplasty
TQIP Trauma Quality Improvement Program
TRALI Transfusion-related acute lung injury
TRIM Transfusion-related immunomodulation
TTI(s) Transfusion-transmitted infection(s)
TXA Tranexamic acid
UFH Unfractionated heparin
UHC United Health Care
UHC University HealthSystem Consortium
UHC Universal health overage
US Ultrasound
USMLE United States Medical Licensing Examination
UTI(s) Urinary tract infection(s)
VA Veterans Affairs
VEST© Virtual Electrosurgery Skill Trainer
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VET Viscoelastic testing
ViSIOT Video-Supported Simulation of Interactions in the
Operating Theater
VL Video laryngoscope
VRE Vancomycin-resistant Enterococci
VTE Venous thromboembolism
WFSA World Federation of Societies of Anaesthesiologists
WHO World Health Organization
Abbreviations
Part I
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Perioperative Optimization
Human Factors andPrinciples ofPatient
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Safety: TheJames Reason Model
RyanHoward andJustinB.Dimick
Introduction
The case scenario below, which will be revisited throughout this chapter, is an
example of a situation in which people working within a complex system precipitate
an adverse event despite nobody intending to do so. The traditional approach to this
situation tends to focus on the individuals involved. The emergency department is to
blame for not notifying the surgery service at the time of the patient’s initial presentation. The radiology resident is to blame for not remarking on the presence of
mesenteric swirling on her initial interpretation. The medicine team is to blame for
not seeing that the imaging interpretation had been updated with critical information.
There is widespread cultural underpinning to this “person approach.” It fullls a
desire for compensation and allows individuals to match the degree of blame with
the harm of an error. This approach, however, fails to recognize that error is part of
the human condition [1, 2]. Moreover, this approach fails to address the critical
issues that can lead to prevention of a similar situation in the future [3]. Quite often,
investigation of what appears to be an error on the part of an individual leads to the
conclusion that the individual is not to blame. In aviation maintenance, it has been
reported that up to 90% of lapses in quality are “blameless” [3, 4]. To focus exclusively on the individuals involved in an error fails to recognize the context of the
larger system within which the error occurred. This is evidenced by the fact that the
person approach rarely leads to action that can improve the system in which an error
occurs, and rarely leads to systematic improvement [5].
1
R. Howard (*)
Department of Surgery, University of Michigan, Ann Arbor, MI, USA
e-mail: rhow@med.umich.edu
J. B. Dimick
Frederick A.Coller Distinguished Professor and Chair Department of Surgery, Michigan
Medicine, University of Michigan, Ann Arbor, MI, USA
© 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_1
3
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In contrast to the person approach is the “system approach,” which recognizes
that humans are fallible and human error is inevitable. Rather than view human
errors as the cause of an adverse event, human errors are viewed as the consequences of failures of systemic safeguards and barriers. In this light, the fatigued
resident who orders the wrong dose of medication for a patient is a reection of
failures in reasonable work-hour limitations, appropriate supervision, and even lack
of pharmacist support. Within the system approach, error analysis seeks to discover
the systematic failures that lead to an adverse outcome in order to design better
safeguards. Importantly, because the system approach analyzes the entire framework within which humans perform their duties, potential weaknesses can be identied and xed before they result in an adverse event, as opposed to retrospectively
trying to identify which individual is at fault once an adverse event has occurred.
This is the cornerstone of human factors analysis and the Swiss cheese model of
human error.
R. Howard and J. B. Dimick
Case Scenario
A 45-year-old woman presents to the emergency department of a large academic
medical center with nausea, vomiting, and severe abdominal pain. She has a history
of a Roux-en-Y gastric bypass. She is evaluated by an emergency medicine resident,
and her initial laboratory workup is largely unremarkable. A CT scan is performed,
but the radiology resident does not specically remark on any evidence of an internal hernia. Therefore, the patient is admitted to a general medicine service for further evaluation and management. The following day, the attending radiologist reads
the CT scan, and notes a swirled appearance to the central mesentery and vasculature. While the interpretation is subsequently updated in the medical record, the
patient’s team is not notied of this change, and does not revisit the CT scan results.
The following night, the patient’s condition deteriorates—she develops worsening
abdominal pain, tachycardia, and hypotension. At this point, the surgical service is
consulted, after the patient had been in the hospital for 3days. Their review of her
clinical presentation and imaging are immediately concerning for an internal hernia
with vascular compromise, and she is taken emergently to the operating room. An
exploratory laparotomy is performed, revealing extensive ischemic and necrotic
bowel, which requires resection, leaving the patient with less than 100cm of viable
small bowel, and TPN-dependent indenitely.
James Reason andtheSwiss Cheese Model ofHuman Error
The “Swiss cheese model” was a metaphor proposed by James Reason to explain
and analyze the occurrence of adverse events within a complex system (Fig.1.1) [3,
6–10]. In this model, there are hazards and losses. Hazards are the potential harms
to patients that can occur because of human error—a wrong medication dose,
wrong-site surgery, iatrogenic harm. Losses are the end result that occurs when a
1 Human Factors andPrinciples ofPatient Safety: TheJames Reason Model
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Fig. 1.1 Swiss cheese
model
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harm reaches a patient—pain, disability, and even death. Because human error is
inevitable, complex systems such as hospitals have innumerable “defenses, barriers,
and safeguards” to help prevent errors from occurring [6, 7, 9]. In 1990, Reason
proposed that these barriers to mistakes are not infallible, but rather have weaknesses or “holes” that make them vulnerable to failure. Because these holes are
inconsistent or sometimes temporary, they usually do not align, and errors still do
not occur. An example would be a medication verication system being ofine, but
a pharmacist still reviewing that the correct dosage is dispensed. Another hole in a
defense against harm may be a fatigued resident at the end of a shift, but the additional layer of appropriate oversight on the part of a teammate or nurse provides a
barrier to prevent harm. In the Swiss cheese model, however, there are occasionally
situations in which the transient holes in each level of defense align and allow a
hazard to reach the patient. A situation may arise where the resident is fatigued, the
medication verication system is ofine, and the pharmacist is attending to another
matter. As Reason points out, “When an adverse event occurs, the important issue is
not who blundered, but how and why the defenses failed” [3].
Within the Swiss cheese model, human errors can be divided into active failures
and latent conditions. The active failures are the unintentional, actual mistakes com-
mitted by the healthcare provider that result in patient harm. This could be failing to
recognize a critical change in patient condition or performing the wrong procedure.
Active failures have an immediate effect but are typically limited to a single instance
(i.e., one active failure does not go on to harm other patients). These active failures
are also referred to as being at the “sharp end” on Reason’s model. The individual
at the sharp end of an error may be the actual surgeon who is holding the scalpel and
performs a wrong-site surgery, even while she may entirely think that she is performing the correct procedure. Active human failures can occur in a variety of
forms, and within human factor analysis are typically divided into skill-based errors
and mistakes (Fig.1.2) [11, 12].
A skill-based error can occur due to a slip or a lapse. A slip is essentially performing the wrong action, or an error in the execution stage of an action. This could
also be known as an error of commission. For example, this may involve performing
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Fig. 1.2 Human factor analysis
R. Howard and J. B. Dimick
wrong-site surgery while having no actual intent to do so, or giving the right medication to the wrong patient. On the other hand, a lapse is essentially a failure of
memory, such as forgetting to restart an intravenous infusion after pausing it to
transport a patient. This could also be known as an error of omission. These skillbased errors typically occur with tasks that require little active thought and are carried out mostly automatically. In both of these errors, the provider intends to perform
the right action but fails to do so.
A mistake is a failure of the decision-making or planning stage of an action. The
provider succeeds in carrying out the intended action, but the intended action is
based on an incorrect assumption. In our case study, the emergency department resident not immediately consulting the surgery service may be an example of a mistake. Reason divides mistakes into rule-based and knowledge-based [7]. A rule-based
mistake results when a rule or set of conditions is applied to a situation but results
in a poor outcome. A classic example of a rule-based mistake is ignoring a re alarm
during a real re because you’ve come to realize that the last 20 re alarms were
false alarms or drills. In our original scenario, the medicine team may have made a
rule-based mistake in assuming that a patient who was determined not to have a
surgical problem by the emergency department truly does not have a surgical problem. On the other hand, a knowledge-based mistake is probably what is most universally understood when we talk about someone “making a mistake.” In this case,
a lack of knowledge results in an error: a radiology resident misses a diagnosis of
mesenteric ischemia because they are unfamiliar with its appearance on a CT scan.
Knowledge-based mistakes can also be procedural, such as a trainee who causes a
pneumothorax when placing a central line, or causes bleeding due to an insecure
surgical knot. Skill-based errors and mistakes are examples of active failures.
Arguably, the more important element of a medical error within the context of
the Swiss cheese model are the latent conditions that allow human error to occur and
to result in patient harm. Metaphorically, latent conditions are the holes in the slices
of cheese which, when aligned, allow a potential harm to reach a patient. Reason
1 Human Factors andPrinciples ofPatient Safety: TheJames Reason Model
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called latent conditions the “resident pathogens” within a system that exist due to
how the system is designed or managed. In contrast to active failures, the impact of
latent conditions is not limited to a single patient or event. The unsafe design of a
piece of medical equipment could result in harm to a great number of patients.
These conditions may exist and lie dormant for years before conditions align to
result in an actual error or may result in a number of adverse events before being
recognized. Critical to the idea of latent conditions is that because they exist in the
design of a complex system such as a hospital, they can be identied and remedied
before causing any adverse event through safety analysis strategies.
Many industries—from healthcare to aviation to nuclear power—share similar
latent conditions that can result in error. If the slices of cheese in Reason’s model
represent the barriers and defenses to human error, one slice may represent the barrier of clear communication. The next may represent adequate training. Subsequent
slices, or defenses, may be adequate supervision, appropriate stafng, safe procedures, safe design, fatigue prevention, and so on. Therefore, the latent conditions, or
holes, are gaps in these defenses. A nursing unit may be understaffed due to a hiring
freeze. A supervisor may be unavailable for part of a critical procedure due to an
emergency involving another patient. In our case of the surgical patient with an
internal hernia, the design of the radiology software does not create any kind of alert
once results are updated (even when the update represents an important diagnostic
change).
Reason likened active failures—slips, lapses, and mistakes—to mosquitos,
which could be swatted again and again, but would invariably keep coming back. A
more durable solution is to address and remove the conditions that allow the mosquitos to breed in the rst place, namely, by xing the “ever-present latent
conditions.”
7
Mitigating Human Error
If human error is an inevitable part of healthcare, what measures can be taken to
improve outcomes and minimize the losses caused by human error? The following
section reviews the principles of a reporting or just culture, human factors engineering strategies, failure mode and effect analysis (FMEA), and root cause analysis (RCA).
Reporting Culture/Just Culture
A key element to detecting and xing the latent conditions in a system that can lead
to patient harm is what Reason described as the creation of a “just culture.” A just
culture is “an atmosphere of trust in which people are encouraged, even rewarded,
for providing essential safety-related information, but in which they are also clear
about where the line must be drawn between acceptable and unacceptable behavior.” [8, 10] This is in juxtaposition to “blame” and “no blame” cultures. Whereas a
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R. Howard and J. B. Dimick
“blame culture” punishes the individual for mistakes and leads to potential hazards
going unreported for fear of retribution, a “no blame” culture leads to a lack of
accountability and a feeling that if no line has been crossed, nothing needs to
change. A just culture, on the other hand, is an environment in which there is a clear
distinction between inevitable human error and reckless behavior, but in which a
provider is not punished simply for reporting a safety incident. Unfortunately, the
U.S. Agency for Healthcare Research and Quality’s 2018 Patient Safety Survey
database revealed that 47% of respondents felt like reporting an unsafe event would
be held against them, and that it was the individual, not the event, that was being
“written up” once an event was reported [13].
Leadership engagement and support is central to creating a just culture. When
health system leaders serve as models for a reporting culture and are willing to
report mistakes themselves, other managers and staff are more likely to model this
accountability [14]. Once leadership is engaged in promotion of a culture of incident reporting without retribution, tools can be implemented to make it easy for
employees to report safety concerns. An example of the effectiveness of these tools
is found in this case report published by the Joint Commission:
Monteore Medical Center created a user-friendly version of the just culture decision tree
to encourage its use in everyday situations. The use of this tool and the rollout of an elec-
tronic event reporting system were a part of a transformational change to a just and learning
culture that improved reporting of adverse events from 6097in 2014 to nearly 9000in 2017,
including increased reporting by groups that traditionally would not be involved in report-
ing, such as attending physicians, who made 542 reports in 2017. Through training and
empowering staff across the health system, including members of 50 peer review commit-
tees, Monteore increased root cause analyses from 60 a year to several every day. Near-
miss and unsafe conditions reporting went up from 681 in 2014 to 2493 in 2017. This
improved reporting has saved lives and has pointed to additional systemic safety issues that
the organization can address and improve [15].
Revisiting the case scenario presented at the beginning of this chapter, we can
see that a just culture may have provided several opportunities for residents and
faculty to report a safety concern. A just culture may have encouraged the emergency medicine resident to speak up and ask whether it would have been appropriate to consult a surgical service; the medicine team may have felt empowered to
voice their lack of familiarity with caring for a patient who may have a surgical
complication; and the radiology team certainly could have pointed to the lack of any
kind of further notication to other providers once their subsequent interpretation
had been changed.
Central to creating the just culture that Reason describes is the use of error- or
incident-reporting systems within healthcare systems. In 1999, when the Institute of
Medicine estimated that up to 98,000 patients died each year due to medical errors,
they called for these reporting systems as a crucial strategy to learn from adverse
events and prevent their recurrence [16, 17]. These systems allow healthcare
employees to anonymously voice safety concerns without fear of retribution. In a
just culture, such reporting is even viewed as a positive contribution to the safety
culture of an organization rather than an admission of guilt. Implementation of one
1 Human Factors andPrinciples ofPatient Safety: TheJames Reason Model
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such system, The University of Texas Close Call Reporting System, which is funded
by the Agency for Healthcare Research and Quality (AHRQ), collected nearly
26,000 safety reports in just under 2years, which resulted in a number of targeted
quality improvement initiatives that redesigned processes in order to maximize
safety [18]. Additionally, while it may appear that hospitals or units with a higher
number of safety reports are performing poorly, it has been shown that higher
reporting rates are associated with a more positive safety culture and identication
of unsafe events [19].
9
Human Factors Engineering Strategies
There are a number of systemic strategies that can be employed to mitigate human
errors. Case studies of institutional implementation have demonstrated that the outcomes of measures can range from least reliable to most reliable [20].
Some of the least reliable strategies include additional education and training, or
creating new rules, policies, or procedures. While these approaches attempt to help
providers perform the correct action, they nevertheless result in providers relying on
memory to perform a task. For example, having a new surgical resident complete a
computer-based module about how to place a central line may in fact familiarize the
resident with the steps of completing this task. However, when it time to carry this
out, the resident may not remember, or may incorrectly remember, certain portions
of how to safely insert the catheter, and her previous training does not offer any hard
stops or useful checklists during the task to ensure that a mistake is not made. The
same is true for new rules and policies, which may try to raise awareness about how
to correctly carry out a task, but fail to ensure any kind of enforcement.
More reliable strategies to mitigate human errors involve standardizing processes
so that variability is minimized as much as possible. Standardization means that the
same process is completed the same way, regardless of the different providers or
teams who are completing the process [21]. It has been demonstrated that when
processes and equipment are standardized across institutions and the same steps are
followed to complete the same task, errors are reduced and efciency is increased
[22]. Therefore, in the example of a surgical resident inserting a central line, human
error can be mitigated by ensuring that this process is standardized and performed
the same way every time. In this specic example, the dramatic impact of standardization can be highlighted by the widespread practice of requiring ultrasound use
for all central line placements, regardless of an individual provider’s previous training or preference. This practice has been shown to reduce iatrogenic complications
associated with this practice [23].
A critical tool in improving standardization is the use of checklists. While rules
and education sessions are ultimately limited by human memory, checklists ensure
that the steps of a given procedure are carried out in the same way regardless of the
provider or team performing them. In the central line example, this would involve a
checklist of the exact steps and order that should be observed to complete the action.
Within surgery specically, checklists have been shown to signicantly reduce
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