Safer Surgery part 39 doc

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base on surgical training and technical performance, the technical skill of the
surgeon (i.e., surgeons’ motor skill) has been recognized as a factor that mediates
the relationship between patient risk factors and patient outcomes (e.g., Aggarwal
et al. 2004, Dankelman and DiLorenzo 2005, Fried and Feldman 2008).
In the past ve years, it has been proposed that this relationship should be
qualied further. A number of other skills and factors have been suggested as
potential determinants of performance and outcomes, alongside motor skills.
These include cognitive and behavioural skills and also other factors, such as
the operating theatre environment and procedures. Because of its multi-factorial
perspective on surgical performance, error and outcome, this approach has been
termed the ‘systems approach’ (Calland et al. 2002, Healey and Vincent 2007,
Vincent et al. 2004).
The systems approach to surgical performance is novel, and thus the existing
conceptual and empirical work that stems from it is still somewhat limited.
Interpersonal and cognitive skills are required for many occupations; specic
subsets of such skills have been identied in the relevant literature as being
essential for surgeons (Healey et al. 2006a, Yule et al. 2006). On the one hand,
there are skills that are related to the way the operating surgeon interacts with
other members of the operating theatre team – including assistant surgeon(s) and
members of the anaesthetic and nursing sub-teams. On the other hand, there are
the skills that reect surgeons’ cognitive competence, such as decision-making.
These skills are complementary to the manual dexterity of the surgeons and they
have been termed, collectively, ‘non-technical skills’. The working hypothesis for
non-technical skills is that they contribute to surgical patient safety. The focus of
this chapter is on one of these non-technical skills, namely decision-making.
Decision-making is becoming increasingly prominent in the surgical skills and
training literature (e.g., Flin et al. 2007, Sevdalis and McCulloch 2006). Decision-
making is a cognitive skill, involving a number of inter-related steps (which may
occur in very rapid, often unconscious sequence):

recognition that choice between different courses of action is available;
perception of different courses of action;
evaluation of each course of action in relation to its potential risks and
benets;
actual choice;
monitoring of the patient’s progress in relation to the decision taken (with
review and change of plan if appropriate).
As in other high-risk environments, in surgery there are a number of different
decision-making ‘modes’ (Flin et al. 2007, Sevdalis and McCulloch 2006). These
modes of thinking span a continuum, ranging from implicit/cognitively untaxing
modes, characterized by intuition and simply ‘knowing what to do’, (recognition-
primed decisions; Klein 1998) to explicit/cognitively taxing (analytical
decisions, in which the various options available are weighed up consciously and
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carefully). Typically, a surgeon applies different decision strategies to different
problems, depending on a variety of factors including the type of problem, whether
it is familiar or not, time pressure, the potential consequences, the surgeon’s
level of expertise, and other factors (Flin et al. 2007, Sevdalis and McCulloch
2006). For instance, the decision whether to offer surgery to a patient presenting
with symptoms suggestive of gallstone disease may be intuitive (if the patient is
signicantly symptomatic from gallstones and t for an operation, making the
decision clear cut), or nearer the analytical end of the continuum if the patient is
elderly and frail and the balance of risks and benets is less clear cut. In contrast,
the decision when a patient can eat and drink post-operatively appears to be a rule-

based decision (with rules that differ somewhat between surgeons; Jacklin et al.
2008a).
(ii) Surgical Decision-Making in Context
Surgeons are faced with important choices at all stages of patient care and their
decisions may be made in very different ways. At the pre-operative stage, deciding
whether or not to operate can be a delicate balance of risks and benets, made at
leisure and collaboratively with the patient in the context of elective surgery. In the
emergency situation, the same decision is likely to be made under time pressure.
Intra-operatively, a sequence of operative steps is carried out, but decision-making
continues – for example, deciding whether the anatomy has been clearly identied
and whether the operation can proceed as anticipated, or the steps require re-
evaluating. For instance, if a strangulated hernia is operated on, a decision must be
made as to whether the bowel that was contained within it remains viable (and can
be returned to the abdomen safely) or is beyond salvage (and must be resected),
with attendant risks of leak from the anastomosis and longer post-operative
recovery.
As in other high-risk environments, decision-making in surgery has some
distinctive characteristics. Firstly, many surgical decisions carry high stakes. For
the patient, the potential consequences of an operation (in addition to the desired
ones) may include disability or death. Operating without causing some harm is
impossible, so in every decision to operate there is a trade-off between the likely
benet and the inevitable anatomical (as well as physiological and psychological)
damage caused to the patient as a primary consequence of the surgery itself.
Secondly, surgery is associated with complications and their consequences,
which may be difcult to predict for any individual patient, but tend to have a
relatively predictable incidence overall. In other words, surgical decisions are
associated with uncertainty about their outcomes at the level of the individual
patient. For example, elective open repair of abdominal aortic aneurysms has a
mortality of up to 7 percent in some institutions (Hertzer 2006)
A third special feature of surgical decisions is their potential irreversibility.

Once a laparotomy has been performed or tissue has been excised, this cannot
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be undone. Reversibility of surgical decisions is relative, as some aspects of an
operation may be reversible. For example, where a stoma has been created and the
gut left in discontinuity, the continuity may subsequently be restored at a further
operation.
Finally, unlike many other medical decisions, intra-operative decision-making
usually cannot be shared with the patient. Although operative details and likely
ndings can be discussed with patients pre-operatively, signicant procedures take
place under general anaesthetic or with spinal/local block often in combination
with sedation. Patients are either unconscious or have impaired consciousness,
with responsibility for operative aspects of decision-making resting with the
primary or senior surgeon and their team.
(iii) Methods for Studying Surgical Decision-Making
There is a substantial established body of theory and experimental research into
the psychology of decision-making and the related eld of problem solving, and
the cognitive processes that they involve. For a comprehensive summary of the
eld, see Koehler and Harvey’s handbook (2004). In addition, there is a related
literature on the nature of expert performance. Research into these areas has been
published for the most part in a number of dedicated journals, such as the Journal
of Behavioral Decision Making, Organizational Behavior and Human Decision
Processes, the Journal of Risk and Uncertainty, Group Decision and Negotiation
and Medical Decision Making.
Although the methods used by decision researchers are unfamiliar to many
surgical researchers, many have been adapted for use in the healthcare setting.
A number of theoretical approaches and empirical applications are described
in Chapman and Sonnenberg’s Decision Making in Health Care edited volume
(2003). The book incorporates various decision research approaches to medical
decision-making (including decision modelling, health economics and cognitive

approaches) and covers a number of applications of this line of work (including
decision support and assessment of patients’ preferences). From a methodological
viewpoint, Harries and Kostopoulou (2005) provide a thorough review of empirical
approaches to the study of medical decision-making. Building on these reviews, in
what follows we provide a brief overview of selected methodological approaches
for empirical research into how surgeons actually make decisions in practice.
(iii-i) Self-report
Self-report, typically elicited in interviews, offers the opportunity for detailed
exploration of particular decision-making issues. Interviewing surgeons about
how they arrive(d) at a decision complements other methodological approaches
by providing detailed information about the relevant cues to a decision, or
identifying important contextual factors. Retrospective investigation of specic,
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357
recent, real-life decisions using detailed interviews forms the basis of the critical
incident approach. This is used extensively within a research paradigm known as
Naturalistic Decision-Making (NDM; Klein et al. 1993, Lipshitz et al. 2001). NDM
approaches focus on how experts actually make decisions in naturally occurring
working environments (e.g., in the operating theatre). In surgery, interviews have
been used successfully to capture surgeons’ subjective experience of stressors
and impediments to their performance (Arora et al. 2009, Wetzel et al. 2006) and
they can be useful additions to direct observation in the development of tools that
capture expert knowledge in an accessible form and facilitate teaching/training of
novice professionals, such as Hierarchical Task Analysis (e.g., Sarker et al. 2008).
In the empirical section of this chapter, we describe an interview-based knowledge
elicitation approach, in which interviews were used to capture expert knowledge
on a given topic.
(iii-ii) Structural Approaches and Decision Modelling
Structural approaches are a group of methodologies that have in common their
statistical approach to modelling relationships between inputs to a judgement or

decision (i.e., decision cues) and their outputs. Judgement Analysis (Cooksey
1996a, 1996b) is one such structural approach. This methodology is based on
presentation of a series of multiple-cue case proles. The impact of different
factors may be assessed by varying the values of the selected cues in differing
combinations. Using linear regression it is then possible to determine the inuence
of different variables/factors on participants’ judgements. The analysis yields
multiple regression-derived beta weights for individual risk factors, and model
t. Data are typically analysed separately for each participant, but can also be
aggregated to allow subgroup comparisons (e.g., novice vs. expert participants;
Sevdalis and Jacklin 2008). Within surgery, this approach has been used to model
surgeons’ prioritization decision-making for cardiac surgery (Kee et al. 1998)
and general surgery (MacCormick and Parry 2006), and treatment of prostate
cancer (Clarke et al. 2007) – and there are other clinical applications, including
management of typical non-end-stage renal disease (Pster et al. 1999) and
dental surgery (Koele and Hoogstraten 1999). One study described below used
this approach to investigate how surgeons generate risk estimates on the basis of
combinations of pre-operative risk factors.
(iii-iii) Observational and Process Approaches
Interpreted broadly, these approaches seek to characterize the decision-making
process as it unfolds over time. Observation of real-life clinical work may focus on
explicit information search, communication with colleagues and the patient during
the decision-making process, the use of artefacts, or non-verbal interactions. In
such approaches, researchers typically seek to capture clinicians’ thinking and/or
behaviours reliably and robustly as these unfold over the time it takes to complete
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the task under investigation (e.g., arrive at a diagnosis or treatment decision, or carry
out a procedure). Such thinking or behavioural ‘protocols’ (verbal or non-verbal)
have been reported in the medical literature – with ‘think aloud’ protocols being
perhaps the most well known (Ericsson and Simon 1984). In such protocols, study

participants report the content of working memory during a decision-making task
(Denig and Haaijer-Ruskamp 1994). Non-verbal approaches, such as eye-tracking
of gaze patterns, can give information about information search patterns, and can
also be used to test the veracity of subjective accounts (e.g., Leong et al. 2007).
Alternatively, researchers may choose to develop an observation protocol (usually
after some pilot observations and testing), which is then used to collect data in real
time. Such observational tools focus more on observable behaviours and less on
underlying cognitive processes (as the former are easier to observe directly than
the latter). Studies of medical and surgical working environments have used this
approach successfully (e.g., Coiera and Tombs 1998, Healey et al. 2006b). The
third set of empirical studies that we report below uses a simulated clinical setting
(simulated operating theatre) to provide a safe and standardized setting to assess
surgical decision-making (among other skills) via real time observation of key
behaviours between team members.
(iv) A Multimodal Approach to Surgical Decision-making
To date, our research group has investigated surgical decision-making using the
following three approaches:
knowledge elicitation from expert surgeons, used to model a care pathway
from the decision-making perspective (Jacklin et al. 2008a);
experimental approaches to the modelling of surgical risk estimation
(Jacklin et al. 2008b, Sevdalis and Jacklin 2008);
simulation-based assessment of decision-making, in which decision-
making is assessed alongside other skills (Undre et al. 2007, Koutantji et
al. 2008).
In what follows, we present the methodology and key ndings of these studies
(readers are referred to original publications for more detail). We discuss the
ndings and their implications in the concluding section of the chapter.
(iv-i) Knowledge elicitation
One of the distinguishing features of expertise is that when expert and novice
professionals are presented with a situation that requires action or a problem that

needs addressing, their perception of it (including their prioritization for actions
to be taken and when) is markedly different. Training junior colleagues, therefore,
involves an expert conveying how they grasp a situation – for instance, how they
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359
use just the relevant information and discard irrelevant ‘noise’. In the context of
surgery, however, such training is rather hard, as only rarely are surgical decisions
of experts explicitly deconstructed into their constituent parts and explained to
trainee surgeons. We conducted an interview study with the aim to provide such
a method of deconstructing a series of interrelated surgical decisions (Jacklin et
al. 2008a).
Methods Semi-structured interviews were conducted with ten expert surgeons
(three senior specialist registrars and seven consultants), focusing on the care
pathway of patients with symptomatic gallstone disease. First of all, participants
were instructed to think of a patient attending an outpatient clinic with chronic
symptoms of gallstone disease. Secondly, participants were asked to think of a
patient presenting acutely at an emergency department, again with symptoms
suggestive of a complication of gallstones. Participants were prompted to think
about the decisions that they would be required to make throughout the patient’s
care (consultation, admission, surgery, recovery and discharge). They identied
the decisions made in each setting, along with the relevant cues for each decision,
and any strategies or rules of thumb.
A coding frame was developed to identify decisions and associated cues and
rules from the text. Participants’ responses were coded for content by a surgeon
(RJ) and a psychologist (NS) and the relevant decisions identied. Decisions were
dened as any nodal choice in the pathway of care.
Results The surgeon and the psychologist coders identied similar numbers

of decisions per interview (M
Surgeon
= 16; M
Psychologist
= 15). A positive correlation
between numbers of decisions per interview identied by each coder suggested
reliable coding between raters (Spearman’s ρ = 0.61, N = 10, p < 0.06). Interestingly,
whereas the surgeon coder considered ‘identication of anatomy’ as a key intra-
operative decision, the psychologist coder did not – perhaps due to differences in
their training and ensuing focus.
Eighteen decisions that were identied in six or more of the interviews were
extracted to form a decision ‘hot list’. A sample of these decisions across the care
pathways is given below:
Pre-operative: are the symptoms due to gallstones or not? Should the
patient be offered surgery or not?
Intra-operative: open port insertion or Veress needle? Is an intra-operative
cholangiogram needed or not?
Post-operative: when to take drains out? When to discharge?
In addition, two distinct strategies for making these decisions were identied
based on the surgeons’ self-reports taken from the coded transcripts. The rst was
an intuitive strategy, described by participants as ‘experience based’, which was
applied to decisions involving the assessment of a risk (e.g., decision whether the
•
•
•
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symptoms were due to gallstones or not; decision whether to operate or not). Such
decisions were characterized by multiple features taken into account to balance
risks and benets, though how these were integrated into a decision could not be

precisely articulated. Formal risk calculation tools were not used. The second,
more rule-based strategy was associated with explicit criteria. For example, for
the decision when to remove a drain post-operatively, surgeons often specied
the absence of bile in the drain along with a volume criterion, the detail of which
varied between individuals. Some technical aspects of the procedure (e.g., open
port insertion or use of a Veress needle to create the pneumoperitoneum) were also
subject to personal rules, again subject to individual variation.
(iv-ii) Experimental/modelling approach
A key limitation of self-report methodologies, such as knowledge elicitation as
described above, is that participants may be unaware of some aspects of their own
decision-making process (Nisbett and Wilson 1977). Thus, in addition to direct
elicitation from experts, we also attempted in another study to model decision-
making quantitatively, without resorting to the participants’ own perceptions of
their decision-making process.
We used Judgment Analysis (JA) to model surgeons’ estimation of the risk
of converting a laparoscopic (key-hole) cholecystectomy to open (Jacklin et al.
2008b, Sevdalis and Jacklin 2008).
Methods Thirty junior surgeons (minimum six months’ experience as trainee
in general surgery after full registration as a doctor, or completion of the Royal
College of Surgeons examination) participated in the study.
Participants were presented with 84 case vignettes – 64 design cases and 20
repeat cases to assess reliability. The clinical factors that were manipulated across
vignettes were patient’s biliary history, age/co-morbidity, previous surgery, obesity,
sex and race (see Figure 21.1). In order to eliminate effects of the participants’
position on the learning curve with respect to operative expertise, participants
were instructed that the procedure would be carried out by Mr J, an experienced
laparoscopic surgeon. Participants were asked to indicate the likelihood (0–100
percent) that, given the case presentation, the procedure would have to be converted
from laparoscopic to open. One key feature of this study was the incorporation of
an outcome-based ‘gold standard’ model against which each case could be scored.

This provided an evidence-based estimate of the likelihood of conversion for each
of the cases in the study, against which to assess participants’ risk judgements.
We analysed the use of the available information (cues) across participants. We
also analysed participants’ reliability, accuracy and their use of the cues (i.e., cue
beta weights in the regression models) with the gold standard model. Within the
gold standard model, the biliary history, the patients’ sex and previous abdominal
surgery were the only variables that inuenced the likelihood of conversion to
open.
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361
Results We observed signicant variation across participants regarding the
correlation of their estimates with the gold standard: we obtained a range of
Pearson r correlation coefcients between 0.08 and 0.72 – with lower coefcients
indicating lower agreement with the gold standard (i.e., lower accuracy). The
average observed r was 0.48 (SD = 0.14). Similar variation was observed in the
cue utilization across participants (see Figure 21.2).
Variability was obtained in model t across individual participants as well.
Obtained model t ranged between R
2
adjusted
= 0.12 (poor t) to R
2
adjusted
= 0.76
Figure 21.1 A model for the study, with the cues that were available to
participating surgeons
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362
(very good t), with mean R
2

adjusted
= 0.53. The data shows that judgement analysis
methodology can be used to model of surgeons’ risk judgements quantitatively,
as well as to compare them with a gold standard model based on epidemiological
data. Some participants were more consistent in their use of the cues, and, thereby,
their responses were more amenable to modelling. The large variation in accuracy
between individual surgeons was somewhat concerning clinically; for junior
surgeons to be able to undertake tasks such as obtaining informed consent, from
patients for procedures, there is a need for their understanding and estimation of
surgical risks to improve.
(iv-iii) Simulation
In the past few years, simulation-based training has been used extensively for the
honing of technical skill of surgical trainees (Aggarwal et al. 2004, Dankelman
and DiLorenzo 2005, Fried and Feldman 2008). In commercial aviation (and
other high risk industries), similar training modules have been developed for
training pilots’ non-technical and crisis-management skills (Helmreich et al. 1999,
Klampfer et al. 2001).
We carried out two series of simulations, aiming to assess surgical teams’
crisis management in a simulated operating theatre (Undre et al. 2007,
Figure 21.2 Cue utilization across individual surgeons
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363
Koutantji et al. 2008). The simulated theatre is a fully equipped functional operating
theatre separated from a control room by a one-way mirror and containing a
standard operating table, operating lights, suction apparatus, anaesthetic machine
and other equipment required for standard open or laparoscopic surgery, together
with a moderate delity anaesthesia simulator mannequin (SimMan
®
Laerdal,
UK). The mannequin is connected to a compressor and controlled by a computer

from the control room, with software that enables the controller to create an
anaesthesia crisis for training and feedback. We modied existing, standardized
scales that assess non-technical skills in the context of commercial aviation,
assessed their reliability, and used them to assess non-technical skills (including
decision-making) in surgical crisis simulation.
Methods The rst training series consisted of 20 half-day simulations, in which
a full operating theatre team of trainees (surgeon, anaesthetist, scrub nurse and
operating department practitioner (these practitioners are technicians trained
to assist the anaesthetists performing tasks similar to those performed in some
contexts by anaesthetic nurses)) completed a sapheno-femoral junction ligation
procedure that involved a number of crises. For the surgeons, the crisis was
bleeding halfway through the procedure, leading to cardiac arrest. The second
series consisted of nine full-day simulations, very similarly formatted and carried
out. The difference was a training module (on safety and crisis management) that
the trainees underwent half way through the day – as a pilot intervention.
We used the NOn-TECHnical Skills (NOTECHS) observational tool. The
NOTECHS was designed for use in the aviation industry to assess non-technical
skills in cockpit crews – including decision-making, leadership skills, teamworking
skills and situation awareness (Flin et al. 2003, van Avermaete and Kruijsen 1998).
We revised the scale for use in surgical teams (Moorthy et al. 2005, Moorthy
et al. 2006, Sevdalis et al. 2008). Here we focus on the assessment of surgical
trainees’ decision-making. The trainees were observed (via one-way mirror in
the control room of the simulated operating theatre) and assessed in real time by
expert trainers and at least one psychologist. Upon completion of the procedure,
trainers and trainees completed a revised NOTECHS and received feedback on the
training exercise.
Results Overall, the revised NOTECHS was found to be a reliable tool for the
assessment of all non-technical skills in terms of internal consistency of the tool,
and between participants and their trainers. Specically for decision-making, we
obtained a range of Cronbach α coefcients between 0.82 and 0.92.

Findings from the rst series of simulations can be seen in Table 21.1. We
did not observe signicant differences between professional groups (surgeons,
anaesthetists, scrub nurses and operating department practitioners) in relation to
trainers’ decision-making ratings. However, we did obtain signicant differences
across skills, with decision-making and leadership being rated signicantly lower
than the other skills (F(4, 568) = 24.04, p < 0.001). Finally, trainer surgeons’