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Correlates of non-technical skills in surgery: A prospective study
Journal: BMJ Open
Manuscript ID bmjopen-2016-014480
Article Type: Research
Date Submitted by the Author: 27-Sep-2016
Complete List of Authors: Gillespie, Brigid; Griffith University, NHMRC Centre for Research Excellence in Nursing (NCREN),Centre for Health Practice Innovation (HPI) l Menzies Health Institute Qld (MHIQ) Harbeck, Emma; Griffith University, School of Applied Psychology Kang, Evelyn; Griffith University - Gold Coast Campus, NHMRC Centre for Research Excellence in Nursing (NCREN) Menzies Health Institute Queensland Steel, Catherine; Princess Alexandra Hospital, Division of surgery
Fairweather, Nicole; Princess Alexandra Hospital, Division of surgery Chaboyer, Wendy; Griffith University, National Centre of Research Excellence in Nursing Interventions for Hospitalised Patients, Centre for Health Practice Innovation, Menzies Institute for Health (Queensland)
<b>Primary Subject Heading</b>:
Surgery
Secondary Subject Heading: Communication, Anaesthesia
Keywords: miscommunications, interruptions, teamwork, non-technical skills, surgical team, NOTECHS
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Correlates of non-technical skills in surgery: A prospective study
Authors:
*1Brigid M. Gillespie PhD, RN, FACORN; 2Emma Harbeck BPsych (Hons), 1Evelyn Kang MScHlth
MHealthPrac, RN, 3Catherine Steel MN, RN;
3Nicole Fairweather FANZCA, MBBS &
1Wendy Chaboyer
PhD RN
1NHMRC Centre for Research Excellence in Nursing (NCREN), Menzies Health Institute Qld (MHIQ),
Griffith University, Parklands Drive, Gold Coast Campus QLD, AUSTRALIA
2School of Applied Psychology, Griffith University, Gold Coast Campus, QLD, AUSTRALIA
3 Division of Surgery, Princess Alexandra Hospital, Woolloongabba, Brisbane, QLD, AUSTRALIA
Email addresses:
2Emma Harbeck: [email protected]
1Evelyn Kang: [email protected]
3Catherine Steel: [email protected]
3Nicole Fairweather: [email protected]
1Wendy Chaboyer: [email protected]
*Corresponding author:
Professor Brigid Gillespie: [email protected]
G01_Rm 2.04, Griffith University
Parklands Dr, Southport
Gold Coast, Qld Australia 4222
Funding Statement
Brigid M. Gillespie acknowledges the financial support of the Australian Research Council, Early
Career Discovery Fellowship Scheme and the NHMRC Centre for Excellence in Nursing Research
(NCREN).
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Authors’ Contributions
BMG conceived of the study, assisted in data analysis, interpreted results and drafted the
manuscript. EH performed data analysis and assisted in interpretation. WC assisted in analysis and
interpretation. EK, CS, and NF assisted in recruitment and interpretation. All authors participated in
the coordination of the study and read and approved the final manuscript.
Conflict of interest
The authors have no declared conflict of interest.
Data sharing statement All relevant data have been included in the paper.
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Correlates of non-technical skills in surgery: A prospective study
ABSTRACT
Background: Communication and teamwork failures have frequently been identified as the
root cause of adverse events and complications in surgery. Few studies have examined
contextual factors that influence teams’ non-technical skills in surgery (NOTSS). The purpose
of this prospective study was to identify and describe correlates of NOTSS.
Methods: We assessed NOTSS of teams and professional role at two hospitals using the
revised 23-item NOTECHS and its subscales (communication, situational awareness, team
skills, leadership, and decision making). Over 6 months, two trained observers evaluated
teams’ NOTSS using a structured form. Inter-observer agreement across hospitals ranged
from 86%-95%. Multiple regression models were developed to describe associations
between operative time, team membership, miscommunications, interruptions, and total
NOTECHS and subscales scores.
Results: We observed 161 surgical procedures across eight teams. The total amount of
explained variance in NOTECHS and its five subscales ranged from 14% (adjusted R2 0.12, p <
.001) to 24% (adjusted R2
0.22, p < .001). In all models, inverse relationships between the
total number of miscommunications and total number of interruptions and teams’ NOTSS
were observed.
Conclusions: Miscommunications and interruptions impact on team NOTSS performance.
Key words: Miscommunications, interruptions, Non-technical skills, surgical team, NOTECHS,
Communication, teamwork
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Article Summary
Strengths and Limitations
• This is one of the largest of its kind in this area and included surgical procedures
observed spanned across two hospitals, and captured a wide array of surgeries
relative to complexity.
• The observational nature of this study allowed us to measure performance as it
happened, rather than a retrospective self-report.
• Individuals may have altered their practices in response to being observed during
the observational period.
• Measures upon which the observations were based may be considered somewhat
subjective as they rely on observers’ ability to interpret events. Observers,
however were experienced clinicians and were trained in observational research
and human factors.
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INTRODUCTION
Compared to other hospital settings, medical errors in the operating room (OR) can
have catastrophic consequences for patients. Adverse events and malpractice claims have
been linked to teamwork failures in surgery.1-4 Deficits in teamwork behaviours were
identified as a root cause in 63% of all the sentinel events reviewed by The Joint Commission
between 2004 and 2013.5 While human error is inevitable and cannot be completely
eliminated, the importance of linking the safety of surgery to team culture is increasingly
recognised.6-8
Fostering a climate of teamwork and collaboration, along with safety minded
work processes that focus on error prevention is the ultimate goal of healthcare
organisations.
Nevertheless, surgical errors need to be understood in the context of the surgical
team. Unique challenges stem from the overlapping but different inter-professional
expertise and roles among members, ad hoc team membership, unstructured and variable
communications, frequent distractions, technology, procedural complexity, and competing
priorities. 9-14 Several studies have described the sources and frequencies of intraoperative
interruptions.13 15 16
The results of these studies identified that equipment problems,
telephone calls, conversation and environment problems (e.g., noise) were major sources
of distractions that influenced team performance. It is therefore hardly surprising that as
much as 30% of information gets lost during case-related exchanges.8 17
More recent
research suggests that omissions in team communications related to providing members
with updates about the progress of an operation comprised up to 36% of all observed
communication errors. 18
As surgical teams often work together on an ad hoc basis, a lack
of prior working experience has the potential to impact on team dynamics. Team familiarity,
defined as a core group of individuals who work together regularly, and who share a similar
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mental model, 19 has been identified as an important element of effective teamwork.13 20 An
earlier observational study found that fewer miscommunications occurred in teams with a
history of working together.13 More recently, results of an Australian observational study
suggested a positive association between team familiarity and instrument nurses’ NOTSS
performance across 182 surgical procedures.9 Other studies, using retrospective designs
have found associations between team familiarity and reductions in postoperative
morbidity following cardiac and major abdominal surgeries.21 22
As a means to increase surgical safety, researchers have focussed on
communication, leadership, situational awareness and decision-making, termed collectively
as non-technical skills in surgery (NOTSS). NOTSS are the cognitive (i.e., decision making and
situational awareness) and interpersonal skills (i.e., communication, teamwork and
leadership) that complement the individual’s technical knowledge.23 Previous research
indicates that communication is key to the performance of successful teams. Effective and
timely transfer of information enables team processes and states such as coordination,
cooperation, conflict resolution and situational awareness.8 10 24 The development of astute
NOTSS is critical to patient safety yet surgical teams are challenged by the increasing
technical complexity of surgery and high acuity of patients, who are older, and have multiple
comorbidities.[8] Moreover there is a lack of research that examines the impact that
environmental factors have on teams’ NOTSS performance. In this prospective study, we
hypothesised that longer surgeries, limited team familiarity, miscommunications, and
interruptions negatively influenced teams’ use of NOTSS. A better understanding of the
factors that impinge on teamwork behaviours will help us to design strategies to improve
NOTSS performance.
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METHODS
This was a prospective, observational study of teams’ use of NOTSS during surgery.
Two Australian metropolitan hospitals 70 kilometres from each other, each with a similar
case mix, specialising in all surgical specialities, were included to generate results that would
be applicable across a variety of procedures. In each hospital, four surgical teams comprising
of anaesthetic and surgical consultants, their registrars, and instrument/circulating nurses,
were observed. Teams and surgical procedures across each hospital were purposively
chosen to ensure maximum variation relative to case complexity, particular procedures
within specialties, team membership, and surgical experience. In Hospital A, teams from
paediatric, thoracic, orthopaedic and general surgery were observed on a weekly basis
across 20-25 surgeries. In Hospital B, a similar number of surgeries were observed with
cardiac, vascular, upper gastro-intestinal, and hepatobiliary teams.
Observational data for each hospital were collected during 2015, with an observer
located at each hospital. Observations commenced when the patient entered the operating
room (prior to anaesthesia) and ended when the patient left the room. Both observers were
trained in human factors. To ensure methodologic consistency, interrater checks with 10%
of cases at each hospital site were performed during the observation period by the lead
author, also trained in human factors. Interrater agreement across hospital sites ranged
from 86%-95%. A single observer was present during each procedure and collected data
using pre-specified checklists and free-hand notes. During each surgical procedure,
observers documented explanatory field notes to supplement the structured observations
to better understand contextual factors. Observational data were collected in 2015 over 6-
months.
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Institutional ethics approvals were given by the participating hospitals and the
university. Participants signed a consent form and were advised of their right to
confidentiality and anonymity, and to withdraw at any time during data collection. Patients
whose operations were observed were informed of the likelihood of observations taking
place and given the chance to opt out.
Observational measures
We used the revised Non-TECHnical Skills (NOTECHS) scale, 25
which was originally
developed in the aviation industry for crew resource management. The NOTECHS provides
comprehensive behavioural descriptors for each of its subscales and so requires less training
prior to use. In surgery, it has been shown to differentiate between good and poor
behaviours, thus has demonstrated good construct validity.25 In the revised NOTECHS, five
subscales of NOTSS are assessed: A. communication and interaction; B. situational
awareness and vigilance; C. team skills; D. leadership and managerial skills; and, E. decision
making in a surgical crisis. Each domain is measured on a 7-point scale to rate each item,
with 1 = not done through to 6 = done very well, and, 0 = not applicable. 25
Total NOTECHS
scores range from 5-23 with higher scores indicative of better overall performance on all
five subscales. Scores for individual subscales were as follows; Subscales A and B scores
ranged from 4-24 while Subscales C to E scores ranged from 5-30. The “not applicable”
option meant that a specific item was not relevant or could not be rated on the basis that
the behaviour was not observed. However, participant NOTECHS scores were not affected
by a reduced score for non-observed behaviours. ‘Not applicable’ scores were replaced by
the participant’s individual item mean. In this study, as all subscales were considered of
equal importance, total NOTECHS scores were calculated by the number of items (i.e., 23) as
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the denominator. Scores for total NOTECHS and its individual subscales were calculated
using the mean of all individual team members NOTECHS total scores. We also calculated
the mean NOTECHS scores based on professional role (i.e., surgeon, anaesthetist, nurse).
In this study, team familiarity was defined as a core membership of three members
(i.e., surgeon, anaesthetist, instrument and/or circulating nurses) who had worked together,
weekly or fortnightly, for a minimum of three months. 26 Prior to commencement of each
surgical procedure, the senior nurse in the room was asked by the observer about
regularity, stability, and length of time individual team members had worked together. The
number of familiar team members for each procedure were tallied and recorded.
Miscommunications (i.e., audience, content, occasion, experience) and interruptions (i.e.,
procedural, conversational) were tallied. Operative time included the time from patient skin
preparation to the application of the final wound dressing.
Analyses
All analyses were performed using the Statistical Package for Social Sciences [SPSS]
(version 23, IBM, New York, NY, USA). Data were cleaned and a random sample of 20% was
checked for accuracy. Descriptive analysis included absolute (n) and relative (%) frequencies
to analyse categorical variables (discipline/role, surgical specialty), while means/standard
deviations [SD] or medians/interquartile range [IQR]) were used for continuous data (i.e.,
operative time, number of interruptions, miscommunications, NOTECHS scores).
Independent variables; operative time, team familiarity, number of interruptions and
miscommunications were subsequently included as covariates in simultaneous multiple
regression models with the dependent variable, NOTSS (measured by NOTECHS). A p-value
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of <.05 was considered significant and 95% confidence intervals (CI) were used. Cohen’s f2
was used to calculate effect size.
Sample size calculation
Our a priori sample size estimate was based on the 20:1 rule which states that the
ratio of the sample size to the number of parameters in a regression model should be at
least 20 cases for each predictor variable in the regression model.27 28 As 4 predictor
variables were proposed in this study, a sample size of 100 was considered sufficient in a
parsimonious regression model.
RESULTS
Across both hospital sites, a total of 161 operations were observed (Hospital A n=80;
Hospital B n=81). The number of surgeries observed for each team ranged from 20-25 with
the exception of the thoracic team. Owing to the retirement of the consultant surgeon in
the thoracic team, only 6 surgical procedures were observed in this specialty. In total, 481
individual participant’s observational data were collected (Hospital A n =243; Hospital B
n=238). The mean length of surgery across both sites was 116.3 minutes (±96.5) [Site A =
78.5 minutes, ±71.2; Site B, 153.7 minutes, ±103.8]. Across the 160 procedures we
observed, consistency in team membership ranged from 3-8 team members. Table 1 shows
case characteristics for each surgical specialty relative to number of procedures in each
specialty, operative time, team membership, and NOTECHS scores (by Subscales A-E and
mean total). Subscale E, decision-making during a surgical crisis was observed in only 40-
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50% of cases as these situations were often not observed during field work. Of the eight
teams observed, the Hepatobiliary team had the highest NOTECHS mean scores (20.7±2.3)
while the cardiac team had the lowest (19.1±3.5). Table 2 displays the descriptive results for
NOTSS performance based on professional role. Observed NOTSS performance among
surgeons and anaesthetists was comparable however, nurses scores were somewhat lower.
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Table 1: Case Characteristics (n=161 Surgical Procedures)
Surgical
Specialty
Number of
Procedures
Observed
in each
Specialty
(n/total %)
Operative
Time (mins)
Mean (SD)
Team
Member-
ship
Mdn (IQR)
*Total
NOTECHS
Scores
Mean (SD)
^Subscale A
Communi-
cation and
interaction
Mean (SD)
^Subscale B
Vigilance
/situation
awareness
Mean (SD)
^Subscale C
Team skills
Mean (SD)
^Subscale D
Leadership
and magmt
skills
Mean (SD)
^Subscale 5
Decision
making in a
crisis
Mean (SD)
General 25 (15.5) 119.5 (85.7) 4 (1) 18.7 (3.1) 19.8 (3.5) 20.0 (3.6) 23.9 (4.5) 23.8 (4.7) 24.3 (4.7)
Orthopaedic 25 (15.5) 82.3 (66.6) 4 (2) 20.3 (2.4) 21.0 (3.1) 21.8 (2.6) 25.9 (3.1) 26.7 (3.5) 26.3 (4.0)
Paediatric 25 (15.5) 35.0 (26.1) 3 (2) 20.5 (2.7) 21.5 (2.8) 21.9 (3.0) 26.1 (4.5) 26.5 (4.1) 27.1 (3.5)
Thoracic 6 (3.7) 74.1 (55.8) 4 (3) 19.6 (2.3) 21.6 (3.0) 20.8 (3.0) 25.2 (3.1) 24.6 (3.7) 25.1 (2.4)
Cardiac 20 (12.4) 234.4 (97.5) 8 (3) 18.4 (2.6) 19.1 (3.5) 20.7 (2.7) 22.8 (4.3) 22.5 (4.4) 24.8 (4.2)
Hepatobiliary 20 (12.4) 165.3 (122.2) 5 (1) 20.7 (2.3) 22.1 (2.4) 22.1 (2.5) 26.7 (3.3) 25.7 (3.8) 27.1 (4.0)
Upper GI 20 (12.4) 109.8 (78.6) 4 (2) 20.5 (2.6) 22.1 (2.9) 22.1 (2.5) 26.2 (3.7) 25.1 (4.1) 27.0 (4.7)
Vascular 20 (12.4) 105.4 (51.7) 6 (2) 20.1 (2.4) 22.1 (2.5) 21.9 (2.3) 25.3 (4.3) 23.9 (4.6) 26.6 (4.1)
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and E Scores in domain range 5-30.
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Table 2: Descriptives of NOTSS performance based on professional role (n=481)
Surgeon
Consultant/
Registrar
Anaesthetic
Consultant/
Registrar
Scrub /
Scout Nurse
Total NOTECS
n 161 158 160
Mean 20.5 20.6 18.9
SD 2.1 2.4 3.2
95% CI 20.1-20.8 19.8-20.6 18.4-19.4
Range 14.5-23.0 11.64-23.0 10.04-23.00
Subscale A, Communication
and interaction
n 161 158 160
Mean 21.4 21.5 20.4
SD 2.8 2.87 3.7
95% CI 20.9-21.8 21.0-22.0 19.81-20.96
Range 10.0-24.0 10.0-24.0 10.00-24.00
Subscale B , Vigilance /
situational awareness
n 161 158 160
Mean 22.2 21.3 20.8
SD 2.2 2.6 3.6
95% CI 21.8-22.5 20.9-21.7 20.3-21.4
Range 16.0-24.0 11.0-24.0 8.0-24.0
Subscale C, Team skills
n 161 158 160
Mean 25.9 25.9 24.1
SD 3.5 4.0 4.6
95% CI 25.3-26.4 25.2-26.5 23.3-24.8
Range 15.0-30.0 11.00-30.0 10.0-30.0
Subscale D, Leadership and
management skills
n 161 158 160
Mean 25.5 25.5 23.8
SD 4.1 3.9 4.8
95% CI 24.9-26.2 24.9-26.1 23.0-24.6
Range 14.0-30.0 12.5-30.0 10.0-30.0
Subscale E , Decision making
in a crisis
n 161 158 160
Mean 27.5 27.0 23.6
SD 2.83 3.16 5.2
95% CI 27.1-28.0 26.6-27.6 22.8-24.4
Range 18.0-30.0 17.0-30.0 9.0-30.0
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and
E Scores in domain range 5-30.
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During each surgical procedure, the observers recorded field notes to better
understand and explain the contextual happenings during assessment of teams’ NOTSS. The
following two field notes are provided as exemplars of team communications from the
highest and lowest performing teams on the NOTECHS. Ensuring that both the anaesthetic
and surgical teams had a similar mental model in relation to the procedure was important:
Prior to commencing a liver resection procedure, the Consultant and Registrar
Surgeons and the Anaesthetic Consultant participated in a detailed prebriefing
about the patient’s medical history and anticipated difficulties/challenges from
their discipline perspectives. These physicians had never worked together
before. Prebriefings between the lead surgeon and anaesthetist were
commonplace in this room and were observed to occur in 70% of the cases
observed. (Hepatobiliary: Hepatectomy, Case # 18).
The following field note illustrates an observed miscommunication between the
surgeon and perfusionist:
Consultant Surgeon to Perfusionist, “Give pledgia.”
Perfusionist: “Give another one?”
Consultant Surgeon: ”‘Have you finished with the previous one?”
Perfusionist: “Yes”. Consultant Surgeon appears to be unaware of pledgia
delivery time. There was no further inquiry from the Consultant Surgeon.
(Cardiac: CABGS x 4, Case # 9).
Across the 161 procedures, the number of miscommunications totalled 436 (Hospital A
n=133; Hospital B n=303). The highest number of miscommunications was observed in
cardiac surgery (n=121). Throughout the observed procedures, interruptions occurred in
106/161 (65.8%) cases. Of the 106 procedures where interruptions were observed,
procedural interruptions occurred at least once in 92 procedures (86.8%) (Hospital A n=118;
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Hospital B n=76). The number and types of miscommunications and interruptions for each
surgical specialty appear in Figures 1 and 2.
Multivariate regression analyses
Table 3 shows the six multiple regression models for total NOTECHS scores and its
individual subscales (A-E). The total amount of explained variance in NOTECHS and its
individual subscales ranged from 14% (adjusted R2 0.12, p < .001) to 24% (adjusted R2 0.22,
p < .001). In all six regression models, the total number of miscommunications and
interruptions were consistently significant predictors of teams’ NOTSS (Table 3). Operative
time and team membership were non-significant.
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Table 3: Regression models for predictors of total NOTSS and each NOTSS domain
(n=161 Surgical Procedures)
95% CI
Model Predictor Variable B
Std
Error β t Sig
Lower
Bound
Upper
Bound a
Team NOTECHS Constant 20.70 .38 - 55.01 <.001 19.96 21.45
Team Familiarity .01 .08 .01 .14 .893 -.15 .18
Operative Time .00 .00 .10 .97 .334 -.00 .01
Miscommunications -.27 .06 -.41 -4.82 <.001 -.38 -.16
Interruptions -.29 .12 -.19 -2.44 .016 -.52 -.05 bSubscale A
Communication and
interaction Constant 22.17 .44 - 50.18 <.001 21.30 23.05
Team Familiarity -.04 .10 -.04 -.42 .674 -.23 .15
Operative Time -.00 .00 -.07 -.66 .512 .00 .01
Miscommunications -.23 .07 -.31 -3.57 <.001 -.36 -.10
Interruptions -.35 .14 -.21 -2.54 .012 -.62 -.08 c Subscale B
Vigilance/situation
awareness Constant 21.76 .41 - 55.62 <.001 20.96 22.56
Team Familiarity .09 .09 .09 1.04 .299 -.08 .27
Operative Time .00 .00 .14 1.40 .163 -.00 .01
Miscommunications -.23 .06 -.33 -3.83 <.001 -.35 -.11
Interruptions -.36 .13 -.23 -2.86 .005 -.61 -.11 d
Subscale C
Team skills Constant 26.72 .58 - 46.19 <.001 25.58 27.87
Team Familiarity -.04 .13 -.03 -.32 .753 -.29 .21
Operative Time .00 .00 .04 .41 .686 -.01 .01
Miscommunications -.38 .09 -.38 -4.49 <.001 -.55 -.21
Interruptions -.30 .18 -.13 -1.65 .101 -.66 .06 e Subscale D
Leadership and
management skills Constant 26.67 .56 - 47.72 <.001 25.57 27.78
Team Familiarity -.13 .12 -.09 -1.09 .277 -.38 .11
Previous training .01 .00 .15 1.59 .115 -.00 .01
Miscommunications -.57 .08 -.51 -6.26 <.001 -.68 -.35
Interruptions -.21 .18 -.09 -1.23 .222 -.56 .13 f Subscale E
Decision making
in a crisis Constant 26.65 .56 - 47.92 <.001 25.55 27.75
Team Familiarity .16 .12 .11 1.31 .192 -.08 .40
Operative Time .01 .01 .03 .26 .793 -.01 .01
Miscommunications -.30 .08 -.32 -3.63 <.001 -.46 -.14
Interruptions -.45 .17 -.21 -2.58 .011 -.79 -.11
Note model results
a R=.43, R² .18, R² Adj .16, F= 8.65 df(4/160), p<.001, (f
2)=.22
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b R=.37, R² .14, R² Adj .12, F= 6.22 df(4/160), p<.001, (f
2)=.16
c R=.37, R² .14, R² Adj .12, F= 6.23 df(4/160), p<.001, (f
2)=.16
d R=.41, R² .17, R² Adj .15, F= 7.82 df(4/160), p<.001, (f
2)=.20
e R=.49, R² .24, R² Adj .22, F=12.27df(4/160), p<.001, (f
2)=.32
f R=.38, R² .15, R² Adj .12, F= 6.56 df(4/160), p<.001, (f
2)=.18
DISCUSSION
To the best of our knowledge, this is the first study to examine the correlates of
teams’ NOTSS. This study is also one of the largest single observational studies in this field.
Notably, we found inverse associations between the number miscommunications and
interruptions and team NOTSS across all NOTECHS subscales, suggesting that the fewer
miscommunications and interruptions, the higher teams’ NOTSS performance. These results
seem intuitive but, this study is the first to provide evidence generated through structured
observations conducted in real time (rather than in simulated environments). In this study,
we observed fewer interruptions as compared with miscommunications; with the highest
number of interruptions seen in the general surgery team. Many interruptions may be
considered acceptable when there are no immediate demands from patient care, but are
clearly less appropriate at busy times or when problems occur.29 Some interruptions are
essential for information sharing, or to talk to and reassure patients, but managing
interruptions and distractions is a crucial skill and requires individuals to refocus on their
primary task.13 Interruptions have identified as a major contributor to loss of vigilance in
anaesthetists.29 While teams and individuals scored reasonably highly on the NOTECHS and
its subscales, the lowest NOTSS performance was observed in relation to vigilance/situation
awareness across all teams. Clearly, miscommunications and interruptions have the
potential to erode individual and distributed situational awareness in surgery.13 29
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The hepatobiliary team had the highest NOTSS performance, as indicated by their
NOTECHS scores. The hepatobiliary team also had the lowest number of
miscommunications during the fieldwork period. In field notes, the observer described
routine preoperative discussions that occurred between physicians prior to case start, the
low levels of environmental and conversational noise, and frequent occasions of closed loop
communications between members, which heightened levels of distributed situational
awareness among team members. Taken together, these features contributed to the
smooth coordination of team tasks and patient care processes during these lists.
Conversely, the cardiac team demonstrated the lowest NOTSS performance, which
was unexpected given that this team had clearly defined roles and a small repertoire of
procedures that were ‘routine’ and well-rehearsed. Remarkably, this team also had the
greatest number of observed miscommunications during the field work period. During
observations, the cardiac team experienced considerable environmental, technological and
team-related challenges: The observer noted high noise levels in this room, attributed to
team communications and technology, e.g., cross conversations, repeated requests from
the surgeon to the perfusionist who was distracted by other team members and/or
equipment problems, incessant alarms during the intraoperative period. Additionally,
procedural and conversational interruptions as a result of the entry of external team
members into the room to ask questions, the referral of cell phone calls that occasionally
demanded the recipient to leave the room, contributed to lower observed NOTSS in the
cardiac team.
Strengths and Limitations
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This study has several strengths but we also recognise some limitations: First,
surgical teams’ NOTSS were evaluated through direct observation. Although most research
in this area has been largely observational and has focussed on refining this methodology, 8,
15, 16, 26, 30 individuals may have altered their practices in response to being observed.
Nevertheless contemporaneous observation is a preferred method to self-report which
could be flawed (giving rise to response bias). The observational nature of the NOTECHS
allowed us to measure performance as it happened, rather than a retrospective self-report.
Second, the measures upon which the observations were based may be considered
somewhat subjective as they rely on observers’ ability to interpret events. Yet, observers
were experienced clinicians, trained in observational research and in human factors.
Interrater consistency between observers was acceptable. Additionally, the measures we
used have been previously validated in this field. 25, 26, 30, 31 Third, surgical teams were
purposively selected based on participants’ willingness to be observed. Thus there is the
potential for selection bias. Notwithstanding, the surgical procedures observed spanned
across two hospitals, and captured a wide array of surgeries relative to complexity, and
there was variability in NOTECHS scores. Finally, in this sample the amount of explained
variance in NOTSS and its subscales while reasonable indicates that there are unknown
predictors that warrant further exploration. Despite these limitations, our results contribute
to identifying interventions that specifically target minimising miscommunications and
interruptions, both of which are modifiable with the ultimate goal of improving NOTSS in
surgery.
CONCLUSIONS
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Our observational results suggest that effective communication and interruptions
were consistent correlates of surgical teams’ NOTSS performance. Across teams, we
observed examples of good and poor NOTSS performance. Notwithstanding, these
correlates of team performance are amenable to improvement or change. Implementation
of interdisciplinary team training may contribute to improvements in NOTSS. However such
training programs need to be underpinned by behaviour change frameworks that focus on
sustained improvements in NOTSS performance. It is reasonable to propose that the
behavioural indicators of success for overall performance are transferrable across surgical
specialties and can consequently, be developed.
Words: 3,000 (including Abstract, excluding reference list)
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REFERENCES
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8. Lingard L, Regehr G, Cartmill C, et al. Evaluation of a preoperative team briefing: a new
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9. Kang E, Massey D, Gillespie B. Factors that influence the non-technical skills performance of scrub
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10. Gillespie B, Marshall AP, Gardiner T, et al. The impact of workflow on the use of the Surgical
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23. Armitage-Chan EA. Human factors, non-technical skills, professionalism and flight safety: their
roles in improving patient outcome. Vet Anaesth Analg 2014;41(3):221-23.
24. Mesmer-Magnus J, DeChurch L. Information Sharing and Team Performance: A Meta-Analysis. J
Appl Psychol 2009;94:535-46.
25. Sevdalis N, Davis R, Koutantji M, et al. Reliability of a revised NOTECHS scale for use in surgical
teams. Am J Surg 2008;196:184-90.
26. Gillespie B, Chaboyer W, Fairweather N. Factors that influence the expected length of operation:
Results of a prospective study. Qual Saf Health Care 2012;21(1):3-12.
27. Polit D. Statistics and data analysis for nursing research. Second ed. Upper Saddle River: Pearson,
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28. Department of Biostatistics VU. Statistical Problems to Document and to Avoid Nashville,
Tennessee: Department of Biostatistics, Vanderbilt University; 2014 [Available from:
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29. Campbell G, Arfanis K, Smith A. Distraction and interruption in anaesthetic practice. Br J Anaesth
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30. Healey A, Undre S, Vincent C. Developing observational measures of performance in surgical
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31. Lingard L, Regehr G, Epsin S, et al. A theory-based instrument to evaluate team communication
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Care 2006;15:422-26.
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Table Legend
Table 1: Case Characteristics (n=161 Surgical Procedures)
Table 2: Descriptives of NOTSS performance based on professional role (n=481)
Table 3: Regression models for predictors of NOTSS and each NOTSS domain (n=161 Surgical
Procedures)
Figure Legend
Figure 1: Total number of miscommunications across 8 specialties
Figure 2: Total number of interruptions across 8 specialties
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Figure 1: Categories and total number of miscommunications across 8 specialties in Hospitals A and B
477x207mm (150 x 150 DPI)
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Figure 2: Categories and total number of interruptions across 8 specialties in Hospitals A and B
466x199mm (150 x 150 DPI)
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1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Checklist/page
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the
title or the abstract
3
(b) Provide in the abstract an informative and balanced summary
of what was done and what was found
3
Introduction
Background/rationale 2 Explain the scientific background and rationale for the
investigation being reported
5
Objectives 3 State specific objectives, including any prespecified hypotheses 6
Methods
Study design 4 Present key elements of study design early in the paper 7
Setting 5 Describe the setting, locations, and relevant dates, including
periods of recruitment, exposure, follow-up, and data collection
7
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and
methods of selection of participants. Describe methods of follow-
up
Case-control study—Give the eligibility criteria, and the sources
and methods of case ascertainment and control selection. Give the
rationale for the choice of cases and controls
Cross-sectional study—Give the eligibility criteria, and the
sources and methods of selection of participants
7-8
(b) Cohort study—For matched studies, give matching criteria and
number of exposed and unexposed
Case-control study—For matched studies, give matching criteria
and the number of controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential
confounders, and effect modifiers. Give diagnostic criteria, if
applicable
8
Data sources/
measurement
8* For each variable of interest, give sources of data and details of
methods of assessment (measurement). Describe comparability of
assessment methods if there is more than one group
7-8
Bias 9 Describe any efforts to address potential sources of bias 8,19
Study size 10 Explain how the study size was arrived at 10
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If
applicable, describe which groupings were chosen and why
9
Statistical methods 12 (a) Describe all statistical methods, including those used to control
for confounding
9-10
(b) Describe any methods used to examine subgroups and
interactions
10
(c) Explain how missing data were addressed 9-10
(d) Cohort study—If applicable, explain how loss to follow-up was
addressed
Case-control study—If applicable, explain how matching of cases
and controls was addressed
NA
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2
Cross-sectional study—If applicable, describe analytical methods
taking account of sampling strategy
(e) Describe any sensitivity analyses 9-10
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially
eligible, examined for eligibility, confirmed eligible, included in the study,
completing follow-up, and analysed
10-11
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and
information on exposures and potential confounders
11,13
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over
time
NA
Case-control study—Report numbers in each exposure category, or summary
measures of exposure
Cross-sectional study—Report numbers of outcome events or summary measures
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates
and their precision (eg, 95% confidence interval). Make clear which confounders
were adjusted for and why they were included
10
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a
meaningful time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and
sensitivity analyses
11,12,16
Discussion
Key results 18 Summarise key results with reference to study objectives 17
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or
imprecision. Discuss both direction and magnitude of any potential bias
19
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations,
multiplicity of analyses, results from similar studies, and other relevant evidence
18
Generalisability 21 Discuss the generalisability (external validity) of the study results 18
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if
applicable, for the original study on which the present article is based
1
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and
unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at www.strobe-statement.org.
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Correlates of non-technical skills in surgery: A prospective study
Journal: BMJ Open
Manuscript ID bmjopen-2016-014480.R1
Article Type: Research
Date Submitted by the Author: 02-Nov-2016
Complete List of Authors: Gillespie, Brigid; Griffith University, School of Nursing & Midwifery, Menzies Health Institute Queensland; Gold Coast University Health Services District Harbeck, Emma; Griffith University, School of Applied Psychology Kang, Evelyn; Griffith University - Gold Coast Campus, NHMRC Centre for Research Excellence in Nursing (NCREN) Menzies Health Institute Queensland Steel, Catherine; Princess Alexandra Hospital, Division of surgery Fairweather, Nicole; Princess Alexandra Hospital, Division of surgery
Chaboyer, Wendy; Griffith University, National Centre of Research Excellence in Nursing Interventions for Hospitalised Patients, Centre for Health Practice Innovation, Menzies Institute for Health (Queensland)
<b>Primary Subject Heading</b>:
Surgery
Secondary Subject Heading: Communication, Anaesthesia
Keywords: miscommunications, interruptions, teamwork, non-technical skills, surgical team, NOTECHS
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Correlates of non-technical skills in surgery: A prospective study 1
ABSTRACT 2
Background: Communication and teamwork failures have frequently been identified as the 3
root cause of adverse events and complications in surgery. Few studies have examined 4
contextual factors that influence teams’ non-technical skills (NTS) in surgery. The purpose of 5
this prospective study was to identify and describe correlates of NTS. 6
Methods: We assessed NTS of teams and professional role at two hospitals using the 7
revised 23-item NOTECHS and its subscales (communication, situational awareness, team 8
skills, leadership, and decision making). Over 6 months, two trained observers evaluated 9
teams’ NTS using a structured form. Inter-observer agreement across hospitals ranged from 10
86%-95%. Multiple regression models were developed to describe associations between 11
operative time, team membership, miscommunications, interruptions, and total NOTECHS 12
and subscales scores. 13
Results: We observed 161 surgical procedures across eight teams. The total amount of 14
explained variance in NOTECHS and its five subscales ranged from 14% (adjusted R2 0.12, p < 15
.001) to 24% (adjusted R2
0.22, p < .001). In all models, inverse relationships between the 16
total number of miscommunications and total number of interruptions and teams’ NTS were 17
observed. 18
Conclusions: Miscommunications and interruptions impact on team NTS performance. 19
20
21
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INTRODUCTION 22
Compared to other hospital settings, medical errors in the operating room (OR) can 23
have catastrophic consequences for patients. Adverse events and malpractice claims have 24
been linked to teamwork failures in surgery.1-5 Deficits in teamwork behaviours were 25
identified as a root cause in 63% of all the sentinel events reviewed by The Joint Commission 26
between 2004 and 2013.6 While human error is inevitable and cannot be completely 27
eliminated, the importance of linking the safety of surgery to team culture is increasingly 28
recognised.7-9
Fostering a climate of teamwork and collaboration, along with safety minded 29
work processes that focus on error prevention is the ultimate goal of healthcare 30
organisations. 31
Nevertheless, surgical errors need to be understood in the context of the surgical 32
team. Unique challenges stem from the overlapping but different interprofessional 33
expertise and roles among members, ad hoc team team membership, unstructured and 34
variable communications, frequent distractions, technology, procedural complexity, and 35
competing priorities.10-15 Several studies have described the sources and frequencies of 36
intraoperative interruptions.14 16 17
The results of these studies identified that equipment 37
problems, telephone calls, conversation and environment problems (e.g., noise) were major 38
sources of distractions that influenced team performance. It is therefore hardly surprising 39
that as much as 30% of information gets lost during case-related exchanges.9 18
More recent 40
research suggests that omissions in team communications related to providing members 41
with updates about the progress of an operation comprised up to 36% of all observed 42
communication errors.19
As surgical teams often work together on an ad hoc basis, a lack of 43
prior working experience has the potential to impact on team dynamics. Team familiarity, 44
defined as a core group of individuals who work together regularly, and who share a similar 45
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mental model20, has been identified as an important element of effective teamwork.14 21 An 46
earlier observational study found that fewer miscommunications occurred in teams with a 47
history of working together.14 More recently, results of an Australian observational study 48
suggested a positive association between team familiarity and instrument nurses’ NTS 49
performance across 182 surgical procedures.10
Other studies, using retrospective designs 50
have found associations between team familiarity and reductions in postoperative 51
morbidity following cardiac and major abdominal surgeries. 21 22 52
As a means to increase surgical safety, researchers have focussed on 53
communication, leadership, situational awareness and decision-making, termed collectively 54
as non-technical skills (NTS) in surgery. NTS are the cognitive (i.e., decision making and 55
situational awareness) and interpersonal skills (i.e., communication, teamwork and 56
leadership) that complement the individual’s technical knowledge.23 Previous research 57
indicates that communication is key to the performance of successful teams. Effective and 58
timely transfer of information enables team processes and states such as coordination, 59
cooperation, conflict resolution and sitational awareness.9 11 24 The development of astute 60
NTS is critical to patient safety yet surgical teams are challenged by the increasing technical 61
complexity of surgery and high acuity of patients, who are older, and have multiple 62
comorbidities.8 Moreover there is a lack of research that examines the impact that 63
environmental factors have on teams’ NTS performance. In this prospective study, we 64
hypothesised that longer surgeries, limited team familiarity, miscommunications, and 65
interruptions negatively influenced teams’ use of NTS. A better understanding of the factors 66
that impinge on teamwork behaviours will help us to design strategies to improve NTS 67
performance. 68
69
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METHODS 70
This was a prospective, observational study of teams’ use of NTS during surgery. Two 71
Australian metropolitan hospitals 70 kilometers from each other, each with a similar case 72
mix, specialising in all surgical specialities, were included to generate results that would be 73
applicable across a variety of procedures. In each hospital, four surgical teams comprising of 74
anaesthetic and surgical consultants, their registrars, and instrument/circulating nurses, 75
were observed. Teams and surgical procedures across each hospital were purposively 76
chosen to ensure maximum variation relative to case complexity, particular procedures 77
within specialties, team membership, and surgical experience. In Hospital A, teams from 78
paediatric, thoracic, orthopaedic and general surgery were observed on a weekly basis 79
across 20-25 surgeries. In Hospital B, a similar number of surgeries was observed with 80
cardiac, vascular, upper gastro-intestinal, and hepatobiliary teams. 81
Observational data for each hospital were collected during 2015, with an observer 82
located at each hospital. Prior to the observation period, both observers underwent specific 83
training in the use of the observational tool which included the NOTECHS system. The 84
observers pilot tested the tool and minor changes made to its formatting. During the 85
piloting process, regular meetings were held with the co-resesrchers to ensure greater 86
clarification of recorded events and refine coding. Both observers were trained in human 87
factors and observational research methods. To ensure methodologic consistency, 88
interrater checks with 10% of cases at each hospital site were performed during the 89
observation period by the lead author, also trained in human factors. Interrater agreement 90
across hospital sites ranged from 86%-95%. A single observer was present during each 91
procedure and collected data using pre-specified checklists and free-hand notes. 92
Observations commenced when the patient entered the operating room (prior to 93
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anaesthesia) and ended when the patient left the room. During each surgical procdure, 94
observers documented explanatory field notes to supplement the structured observations 95
to better understand contextual factors. Observational data were collected in 2015 over 6-96
months. 97
Institutional ethics approvals were given by the participating hospitals and the 98
university. Participants signed a consent form and were advised of their right to 99
confidentiality and anonymity, and to withdraw at any time during data collection. Patients 100
whose operations were observed were informed of the likelihood of observations taking 101
place and given the chance to opt out. 102
103
Observational measures 104
We used the revised Non-TECHnical Skills (NOTECHS) scale 25, which was originally 105
developed in the aviation industry for crew resource management. The NOTECHS provides 106
comprehensive behavioural descriptors for each of its subscales and so requires less training 107
prior to use. In surgery, it has been shown to differentiate between good and poor 108
behaviours, thus has demonstrated good construct validity.25
In the revised NOTECHS, five 109
subscales of NTS are assessed: A. communication and interaction; B. situational awareness 110
and vigilance; C. team skills; D. leadership and managerial skills; and, E. decision making in a 111
surgical crisis. Each domain is measured on a 7-point scale to rate each item, with 1 = not 112
done through to 6 = done very well, and, 0 = not applicable 25. Total NOTECHS scores range 113
from 5-23 with higher scores indicative of better overall performance on all five subscales. 114
Scores for individual subscales were as follows; Subscales A and B scores ranged from 4-24 115
while Subscales C to E scores ranged from 5-30. The “not applicable” option meant that a 116
specific item was not relevant or could not be rated on the basis that the behaviour was not 117
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observed. However, participant NOTECHS scores were not affected by a reduced score for 118
non-observed behaviours. ‘Not applicable’ scores were replaced by the participant’s 119
individual item mean. In this study, as all subscales were considered of equal importance, 120
total NOTECHS scores were calculated by the number of items (i.e., 23) as the denominator. 121
Scores for total NOTECHS and its individual subscales were calculated using the mean of all 122
individual team members NOTECHS total scores. We also calculated the mean NOTECHS 123
scores based on professional role (i.e., surgeon, anaesthetist, nurse). 124
In this study, we drew on the literature for definitions and measurement of the 125
observational variables relative to team familiarty, miscommunication and interruption 126
events. Team familiarity was defined as a core membership of three members (i.e., surgeon, 127
anaesthetist, instrument and/or circulating nurses) who had worked together, weekly or 128
fortnightly, for a minimum of three months. 26 Prior to commencement of each surgical 129
procedure, the senior nurse in the room was asked by the observer about regularity, 130
stability, and length of time individual team members had worked together. The number of 131
familiar team members for each procedure were tallied and recorded. We used Lingard et 132
al’s.18 27
taxonomy to classify miscommunications (i.e., audience, content, occasion, 133
experience). Interruptions were classified according to Healey et al’s.16 28 framework (i.e., 134
procedural, conversational). For each procedure, we tallied the number of 135
miscommunications and interruptions in each of their respective categories. In some 136
instances, it was possible that a single miscommunication or interruption could be placed 137
into more than one category. As such, the primary prompt of the miscommunication or 138
interruption was deamed to categorise the event. Operative time included the time from 139
patient skin preparation to the application of the final wound dressing. 140
141
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Analyses 142
All analyses were performed using the Statistical Package for Social Sciences [SPSS] 143
(version 23, IBM, New York, NY, USA). Data were cleaned and a random sample of 20% was 144
checked for accuracy. Descriptive analysis included absolute (n) and relative (%) frequencies 145
to analyse categorical variables (discipline/role, surgical specialty), while means/standard 146
deviations [SD] or medians/interquartile range [IQR]) were used for continuous data (i.e., 147
operative time, number of interruptions, miscommunications, NOTECHS scores). 148
Independent variables; operative time, team familiarity, number of interruptions and 149
miscommunications were subsequently included as covariates in simultaneous multiple 150
regression models with the dependent variable, NTS (measured by NOTECHS). A p-value of 151
<.05 was considered significant and 95% confidence intervals (CI) were used. Cohen’s f2 was 152
used to calculate effect size. 153
154
Sample size calculation 155
Our a priori sample size estimate was based on the 20:1 rule which states that the 156
ratio of the sample size to the number of parameters in a regression model should be at 157
least 20 cases for each predictor variable in the regression model.29 30 As 4 predictor 158
variables were proposed in this study, a sample size of 100 was considered sufficient in a 159
parsimonious regression model. 160
161
162
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RESULTS 163
Across both hospital sites, a total of 161 operations were observed (Hospital A n=80; 164
Hospital B n=81). The number of surgeries observed for each team ranged from 20-25 with 165
the exception of the thoracic team. Owing to the retirement of the consultant surgeon in 166
the thoracic team, only 6 surgical procedures were observed in this specialty. In total, 481 167
individual participant’s observational data were collected (Hospital A n =243; Hospital B 168
n=238). The mean length of surgery across both sites was 116.3 minutes (±96.5) [Site A = 169
78.5 minutes, ±71.2; Site B, 153.7 minutes, ±103.8]. Across the 160 procedures we 170
observed, consistency in team membership ranged from 3-8 team members. On average 171
there were 7 team members present across all procedures including 2 surgeons, 2 172
anaesthetists, and 3 nurses. Table 1 shows case characteristics for each surgical specialty 173
relative to number of procedures in each specialty, operative time, team membership, and 174
NOTECHS scores (by Subscales A-E and mean total). Subscale E, decision-making during a 175
surgical crisis was observed in only 40-50% of cases as these situations were often not 176
observed during field work. Of the eight teams observed, the Hepatobiliary team had the 177
highest NOTECHS mean scores (20.7±2.3) while the cardiac team had the lowest (19.1±3.5). 178
Table 2 displays the descriptive results for NTS performance based on professional role. 179
Observed NTS performance among surgeons and anaesthetists was comparable however, 180
nurses scores were somewhat lower. 181
During each surgical procedure, the observers recorded field notes to better 182
understand and explain the contextual happenings during assessment of teams’ NTS. The 183
following two field notes are provided as exemplars of team communications from the184
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Table 1: Case Characteristics (n=161 Surgical Procedures) 185
Surgical
Specialty
Number of
Procedures
Observed
in each
Specialty
(n/total %)
Operative
Time (mins)
Mean (SD)
Team
Member-
ship
Mdn (IQR)
*Total
NOTECHS
Scores
Mean (SD)
^Subscale A
Communi-
cation and
interaction
Mean (SD)
^Subscale B
Vigilance
/situation
awareness
Mean (SD)
^Subscale C
Team skills
Mean (SD)
^Subscale D
Leadership
and magmt
skills
Mean (SD)
^Subscale E
Decision
making in a
crisis
Mean (SD)
General 25 (15.5) 119.5 (85.7) 4 (1) 18.7 (3.1) 19.8 (3.5) 20.0 (3.6) 23.9 (4.5) 23.8 (4.7) 24.3 (4.7)
Orthopaedic 25 (15.5) 82.3 (66.6) 4 (2) 20.3 (2.4) 21.0 (3.1) 21.8 (2.6) 25.9 (3.1) 26.7 (3.5) 26.3 (4.0)
Paediatric 25 (15.5) 35.0 (26.1) 3 (2) 20.5 (2.7) 21.5 (2.8) 21.9 (3.0) 26.1 (4.5) 26.5 (4.1) 27.1 (3.5)
Thoracic 6 (3.7) 74.1 (55.8) 4 (3) 19.6 (2.3) 21.6 (3.0) 20.8 (3.0) 25.2 (3.1) 24.6 (3.7) 25.1 (2.4)
Cardiac 20 (12.4) 234.4 (97.5) 8 (3) 18.4 (2.6) 19.1 (3.5) 20.7 (2.7) 22.8 (4.3) 22.5 (4.4) 24.8 (4.2)
Hepatobiliary 20 (12.4) 165.3 (122.2) 5 (1) 20.7 (2.3) 22.1 (2.4) 22.1 (2.5) 26.7 (3.3) 25.7 (3.8) 27.1 (4.0)
Upper GI 20 (12.4) 109.8 (78.6) 4 (2) 20.5 (2.6) 22.1 (2.9) 22.1 (2.5) 26.2 (3.7) 25.1 (4.1) 27.0 (4.7)
Vascular 20 (12.4) 105.4 (51.7) 6 (2) 20.1 (2.4) 22.1 (2.5) 21.9 (2.3) 25.3 (4.3) 23.9 (4.6) 26.6 (4.1)
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and E Scores in domain range 5-30. 186
187
188
189
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Table 2: Descriptives of NOTECHS performance based on professional role (n=481) 190
Surgeon
Consultant/
Registrar
Anaesthetic
Consultant/
Registrar
Scrub /
Scout Nurse
Total NOTECS
n 161 158 160
Mean 20.5 20.6 18.9
SD 2.1 2.4 3.2
95% CI 20.1-20.8 19.8-20.6 18.4-19.4
Range 14.5-23.0 11.64-23.0 10.04-23.00
Subscale A, Communication
and interaction
n 161 158 160
Mean 21.4 21.5 20.4
SD 2.8 2.87 3.7
95% CI 20.9-21.8 21.0-22.0 19.81-20.96
Range 10.0-24.0 10.0-24.0 10.00-24.00
Subscale B , Vigilance /
situational awareness
n 161 158 160
Mean 22.2 21.3 20.8
SD 2.2 2.6 3.6
95% CI 21.8-22.5 20.9-21.7 20.3-21.4
Range 16.0-24.0 11.0-24.0 8.0-24.0
Subscale C, Team skills
n 161 158 160
Mean 25.9 25.9 24.1
SD 3.5 4.0 4.6
95% CI 25.3-26.4 25.2-26.5 23.3-24.8
Range 15.0-30.0 11.00-30.0 10.0-30.0
Subscale D, Leadership and
management skills
n 161 158 160
Mean 25.5 25.5 23.8
SD 4.1 3.9 4.8
95% CI 24.9-26.2 24.9-26.1 23.0-24.6
Range 14.0-30.0 12.5-30.0 10.0-30.0
Subscale E , Decision making
in a crisis
n 161 158 160
Mean 27.5 27.0 23.6
SD 2.83 3.16 5.2
95% CI 27.1-28.0 26.6-27.6 22.8-24.4
Range 18.0-30.0 17.0-30.0 9.0-30.0
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and 191
E Scores in domain range 5-30. 192
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highest and lowest performing teams on the NOTECHS. Ensuring that both the anaesthetic 193
and surgical teams had a similar mental model in relation to the procedure was important: 194
Prior to commencing a liver resection procedure, the Consultant and Registrar 195
Surgeons and the Anaesthetic Consultant participated in a detailed prebriefing 196
about the patient’s medical history and anticipated difficulties/challenges from 197
their discipline perspectives. These physicians had never worked together 198
before. Prebriefings between the lead surgeon and anaesthetist were 199
commonplace in this room and were observed to occur in 70% of the cases 200
observed. (Hepatobiliary: Hepatectomy, Case # 18). 201
The following fieldnote illustrates an observed miscommunication between the 202
surgeon and perfusionist: 203
Consultant Surgeon to Perfusionist, “Give pledgia.” 204
Perfusionist: “Give another one?” 205
Consultant Surgeon: ”‘Have you finished with the previous one?” 206
Perfusionist: “Yes”. Consultant Surgeon appears to be unaware of pledgia 207
delivery time. There was no further inquiry from the Consultant Surgeon. 208
(Cardiac: CABGS x 4, Case # 9). 209
Across the 161 procedures, the number of miscommunications totalled 436 (Hospital A 210
n=133; Hospital B n=303). The highest number of miscommunications was observed in 211
cardiac surgery (n=121). Throughout the observed procedures, interruptions occurred in 212
106/161 (65.8%) cases. Of the 106 procedures where interruptions were observed, 213
procedural interruptions occurred at least once in 92 procedures (86.8%) (Hospital A n=118; 214
Hospital B n=76). The number and types of miscommunications and interruptions for each 215
surgical specialty appear in Figures 1 and 2. 216
217
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Multivariate regression analyses 218
Table 3 shows the six multiple regression models for total NOTECHS scores and its 219
individual subscales (A-E). The total amount of explained variance in NOTECHS and its 220
individual subscales ranged from 14% (adjusted R2 0.12, p < .001) to 24% (adjusted R2 0.22, 221
p < .001). In all six regression models, the total number of miscommunications and 222
interruptions were consistently significant predictors of teams’ NTS (Table 3). Operative 223
time and team membership were non-significant. 224
225
DISCUSSION 226
To the best of our knowledge, this is the first study to examine the correlates of 227
teams’ NTS. This study is also one of the largest single observational studies in this field. 228
Notably, we found inverse associations between the number miscommunications and 229
interruptions and team NTS across all NOTECHS subscales, suggesting that the fewer 230
miscommunications and interruptions there are, the higher teams’ NTS performance. These 231
results seem intuitive but, this study is the first to provide evidence generated through 232
structured observations conducted in real time (rather than in simulated environments). In 233
this study, we observed fewer interruptions as compared with miscommunications; with the 234
highest number of interruptions seen in the general surgery team. Many interruptions may 235
be considered acceptable when there are no immediate demands from patient care, but are 236
clearly less appropriate at busy times or when problems occur.31 Some interruptions are 237
essential for information sharing, or to talk to and reassure patients, but managing 238
interruptions and distractions is a crucial skill and requires individuals to refocus on their 239
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Table 3: Regression models for predictors of total NOTECHS and each NOTECHS domain (n=161 Surgical Procedures) 240
95% CI
Model Predictor Variable B
Std
Error β t Sig
Lower
Bound
Upper
Bound a
Team NOTECHS Constant 20.70 .38 - 55.01 <.001 19.96 21.45
Team Familiarity .01 .08 .01 .14 .893 -.15 .18
Operative Time .00 .00 .10 .97 .334 -.00 .01
Miscommunications -.27 .06 -.41 -4.82 <.001 -.38 -.16
Interruptions -.29 .12 -.19 -2.44 .016 -.52 -.05 bSubscale A
Communication and
interaction Constant 22.17 .44 - 50.18 <.001 21.30 23.05
Team Familiarity -.04 .10 -.04 -.42 .674 -.23 .15
Operative Time -.00 .00 -.07 -.66 .512 .00 .01
Miscommunications -.23 .07 -.31 -3.57 <.001 -.36 -.10
Interruptions -.35 .14 -.21 -2.54 .012 -.62 -.08 c Subscale B
Vigilance/situation
awareness Constant 21.76 .41 - 55.62 <.001 20.96 22.56
Team Familiarity .09 .09 .09 1.04 .299 -.08 .27
Operative Time .00 .00 .14 1.40 .163 -.00 .01
Miscommunications -.23 .06 -.33 -3.83 <.001 -.35 -.11
Interruptions -.36 .13 -.23 -2.86 .005 -.61 -.11 d
Subscale C
Team skills Constant 26.72 .58 - 46.19 <.001 25.58 27.87
Team Familiarity -.04 .13 -.03 -.32 .753 -.29 .21
Operative Time .00 .00 .04 .41 .686 -.01 .01
Miscommunications -.38 .09 -.38 -4.49 <.001 -.55 -.21
Interruptions -.30 .18 -.13 -1.65 .101 -.66 .06
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e Subscale D
Leadership and
management skills Constant 26.67 .56 - 47.72 <.001 25.57 27.78
Team Familiarity -.13 .12 -.09 -1.09 .277 -.38 .11
Previous training .01 .00 .15 1.59 .115 -.00 .01
Miscommunications -.57 .08 -.51 -6.26 <.001 -.68 -.35
Interruptions -.21 .18 -.09 -1.23 .222 -.56 .13 f Subscale E
Decision making
in a crisis Constant 26.65 .56 - 47.92 <.001 25.55 27.75
Team Familiarity .16 .12 .11 1.31 .192 -.08 .40
Operative Time .01 .01 .03 .26 .793 -.01 .01
Miscommunications -.30 .08 -.32 -3.63 <.001 -.46 -.14
Interruptions -.45 .17 -.21 -2.58 .011 -.79 -.11
Note model results 241 a
R=.43, R² .18, R² Adj .16, F= 8.65 df(4/160), p<.001, (f2)=.22
b R=.37, R² .14, R² Adj .12, F= 6.22 df(4/160), p<.001, (f
2)=.16
c R=.37, R² .14, R² Adj .12, F= 6.23 df(4/160), p<.001, (f
2)=.16
d R=.41, R² .17, R² Adj .15, F= 7.82 df(4/160), p<.001, (f
2)=.20
e R=.49, R² .24, R² Adj .22, F=12.27df(4/160), p<.001, (f
2)=.32
f R=.38, R² .15, R² Adj .12, F= 6.56 df(4/160), p<.001, (f
2)=.18
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primary task.14 Interruptions have identified as a major contributor to loss of
vigilance in anaesthetists.31
While teams and individuals scored reasonably highly on the
NOTECHS and its subscales, the lowest NTS performance was observed in relation to
vigilence/situation awareness across all teams. Clearly, miscommunications and
interruptions have the potential to erode individual and distributed situational awareness in
surgery.14 31
The hepatobiliary team had the highest NTS performance, as indicated by their
NOTECHS scores. The hepatobiliary team also had the lowest number of
miscommunications during the fieldwork period. In field notes, the observer described
routine preoperative discussions that occurred between physicians prior to case start, the
low levels of environmental and conversational noise, and frequent occasions of closed loop
communications between members, which heightened levels of distributed situational
awareness among team members. Taken together, these features contributed to the
smooth coordination of team tasks and patient care processes during these lists.
Conversely, the cardiac team demonstrated the lowest NTS performance, which was
unexpected given that this team had clearly defined roles and a small repertoire of
procedures that were ‘routine’ and well-rehearsed. Remarkably, this team also had the
greatest number of observed miscommunications during the field work period. Notably, the
degree of difficulty and complexity, technical skills, stress, and patients’ instability and
acuity may be highest in cardiac surgery.13 32 Observer described (in field notes) the
considerable environmental, technological and team-related challenges experienced by the
cardiac during the surgery, which added to case complexity. For instance, the high noise
levels in this room, attributed to team communications and technology, e.g., cross
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conversations, repeated requests from the surgeon to the perfusionist who was distracted
by other team members and/or equipment problems, incessant alarms during the
intraoperative period. Additionally, procedural and conversational interruptions as a result
of the entry of external team members into the room to ask questions, the referral of cell
phone calls that occasionally demanded the recipient to leave the room, contributed to
lower observed NTS in the cardiac team.
Although we had good sampling across surgical specialties and procedures, it is
difficult to speculate about whether the differences in NTS performance can be attributed
to hospital sites, specialties, surgical teams, or individuals. The two hospital sites chosen
were similar in relation to case mix, patient acuity and surgical activity. However the
selection of specialties varied in each hospital, which may in part, explain the differences in
NTS we observed across teams. The observed diffierences may also be attributed to
particular individuals, i.e., good leadership of the consultant surgeon has been linked with
effective team behaviour and task accomplishment.33 Arguably, surgeons may establish
aspects of leadership prior to the start of the procedure to condition intraoperative team
performance. For instance, using the surgical safety checklist or having a team briefing can
contribute to building the team’s shared mental model, and hence increasing distributed
situational awareness.34
Strengths and Limitations
This study has several strengths but we also recognise some limitations: First, while
we found relationships between miscommunications, interruptions and surgical teams’ NTS,
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temporal order and causality cannot be established. Thus there may be some competing
explanations for these results. Notwithstanding, the design does allow statistical
associations and identification of some potential confounders; but, not all have necessarily
been identified. Second, surgical teams’ NTS were evaluated through direct observation.
Although most research in this area has been largely observational and has focussed on
refining this methodology 9 16 17 26 35, individuals may have altered their practices in response
to being observed. Nevertheless contemporaneous observation is a preferred method to
self report which could be flawed (giving rise to response bias). The observational nature of
the NOTECHS allowed us to measure performance as it happened, rather than a
retrospective self report. Third, the measures upon which the observations were based may
be considered somewhat subjective as they rely on observers’ ability to interpret events.
Yet, observers were experienced OR nurses, trained in observatimal research and in human
factors. Interrater consistency between observers was acceptable. Additionally, the
measures we used have been previously validated in this field. 25-27 35 Fourth, surgical teams
were purposively selected based on participants’ willingness to be observed. Thus there is
the potential for selection bias. Notwithstanding, the, and there was variability in NOTECHS
scores. Finally, in this sample the amount of explained variance in NTS and its subscales
while reasonable, indicates that there are unknown predictors that warrant further
exploration. Despite these limitations, our results contribute to identifying interventions
that specifically target minimising miscommunications and interruptions, both of which are
modifiable with the ultimate goal of improving NTS in surgery.
CONCLUSIONS
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Our observational results suggest that effective communication and interruptions
were consistent corrrelates of surgical teams’ NTS performance. Across teams, we observed
examples of good and poor NTS performance. Notwithstanding, these correlates of team
performance are amenable to improvement or change. Implementation of interdisciplinary
team training may contribute to improvements in NTS. However such training programs
need to be underpinned by behaviour change frameworks that focus on sustained
improvements in NTS performance. It is reasonable to propose that the behavioural
indicators of success for overall performance are transferrable across surgical specialties
and can consequently, be developed.
Words: 3,389
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Table Legend
Table 1: Case Characteristics (n=161 Surgical Procedures)
Table 2: Descriptives of NOTECHS performance based on professional role (n=481)
Table 3: Regression models for predictors of NOTECHS and each NOTECHS domain (n=161
Surgical Procedures)
Figure Legend
Figure 1: Total number of miscommunications across 8 specialties
Figure 2: Total number of interruptions across 8 specialties
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Figure 1
477x207mm (300 x 300 DPI)
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Figure 2
466x199mm (300 x 300 DPI)
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1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Checklist/page
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the
title or the abstract
3
(b) Provide in the abstract an informative and balanced summary
of what was done and what was found
3
Introduction
Background/rationale 2 Explain the scientific background and rationale for the
investigation being reported
5
Objectives 3 State specific objectives, including any prespecified hypotheses 6
Methods
Study design 4 Present key elements of study design early in the paper 7
Setting 5 Describe the setting, locations, and relevant dates, including
periods of recruitment, exposure, follow-up, and data collection
7
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and
methods of selection of participants. Describe methods of follow-
up
Case-control study—Give the eligibility criteria, and the sources
and methods of case ascertainment and control selection. Give the
rationale for the choice of cases and controls
Cross-sectional study—Give the eligibility criteria, and the
sources and methods of selection of participants
7-8
(b) Cohort study—For matched studies, give matching criteria and
number of exposed and unexposed
Case-control study—For matched studies, give matching criteria
and the number of controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential
confounders, and effect modifiers. Give diagnostic criteria, if
applicable
8
Data sources/
measurement
8* For each variable of interest, give sources of data and details of
methods of assessment (measurement). Describe comparability of
assessment methods if there is more than one group
7-8
Bias 9 Describe any efforts to address potential sources of bias 8,19
Study size 10 Explain how the study size was arrived at 10
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If
applicable, describe which groupings were chosen and why
9
Statistical methods 12 (a) Describe all statistical methods, including those used to control
for confounding
9-10
(b) Describe any methods used to examine subgroups and
interactions
10
(c) Explain how missing data were addressed 9-10
(d) Cohort study—If applicable, explain how loss to follow-up was
addressed
Case-control study—If applicable, explain how matching of cases
and controls was addressed
NA
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2
Cross-sectional study—If applicable, describe analytical methods
taking account of sampling strategy
(e) Describe any sensitivity analyses 9-10
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially
eligible, examined for eligibility, confirmed eligible, included in the study,
completing follow-up, and analysed
10-11
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and
information on exposures and potential confounders
11,13
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over
time
NA
Case-control study—Report numbers in each exposure category, or summary
measures of exposure
Cross-sectional study—Report numbers of outcome events or summary measures
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates
and their precision (eg, 95% confidence interval). Make clear which confounders
were adjusted for and why they were included
10
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a
meaningful time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and
sensitivity analyses
11,12,16
Discussion
Key results 18 Summarise key results with reference to study objectives 17
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or
imprecision. Discuss both direction and magnitude of any potential bias
19
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations,
multiplicity of analyses, results from similar studies, and other relevant evidence
18
Generalisability 21 Discuss the generalisability (external validity) of the study results 18
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if
applicable, for the original study on which the present article is based
1
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and
unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at www.strobe-statement.org.
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Correlates of non-technical skills in surgery: A prospective study
Journal: BMJ Open
Manuscript ID bmjopen-2016-014480.R2
Article Type: Research
Date Submitted by the Author: 05-Dec-2016
Complete List of Authors: Gillespie, Brigid; Griffith University, National Center of Research Excellence in Nursing (NCREN), Menzies Health Institute Queensland, School of Nursing and Midwifery; Gold Coast University Hospital, Gold Coast Hospital and Health Service, Nursing and Midwifery Education and Research Unit Harbeck, Emma; Griffith University, School of Applied Psychology Kang, Evelyn; Griffith University - Gold Coast Campus, National Centre of Research Excellence in Nursing, Menzies Health Institute Queensland, School of Nursing and Midwifery
Steel, Catherine; Princess Alexandra Hospital, Division of surgery Fairweather, Nicole; Princess Alexandra Hospital, Division of surgery Chaboyer, Wendy; Griffith University, National Center of Research Excellence in Nursing (NCREN), Menzies Health Institute Queensland, School of Nursing and Midwifery,
<b>Primary Subject Heading</b>:
Surgery
Secondary Subject Heading: Communication, Anaesthesia
Keywords: miscommunications, interruptions, teamwork, non-technical skills, surgical team, NOTECHS
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Correlates of non-technical skills in surgery: A prospective study 1
Authors: 2
1,2,3*Brigid M. Gillespie PhD, RN, FACORN; 4Emma Harbeck BPsche (Hons), 1Evelyn Kang 3
MHth (Hons) RN, 5Catherine Steel MN, RN; 5Nicole Fairweather FANZCA, MBBS; & 3Wendy 4
Chaboyer PhD RN 5
6
7
1School of Nursing and Midwifery, Griffith University 8
2 Gold Coast University Hospital, Gold Coast Hospital and Health Service 9
3 National Centre for Research Excellence in Nursing (NCREN), Menzies Health Institute Qld 10
(MHIQ), Griffith University, Parklands Drive, Gold Coast Campus QLD, AUSTRALIA 11
4 School of Applied Psychology, Griffith University, Gold Coast Campus, QLD, AUSTRALIA 12
5 Division of Surgery, Princess Alexandra Hospital, Woolloongabba, Brisbane, QLD, 13
AUSTRALIA 14
15
Email addresses: 16
4Emma Harbeck: [email protected] 17
3Evelyn Kang: [email protected] 18
5Catherine Steel: [email protected] 19
5Nicole Fairweather: [email protected] 20
3Wendy Chaboyer: [email protected] 21
22
23
*Corresponding author: 24
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1,2,3 Professor Brigid Gillespie: [email protected] 25
G01_Rm 2.04, Griffith University 26
Parklands Dr, Southport 27
Gold Coast, Qld Australia 4222 28
Tel: + 61 7 552 9718 29
30
*Corresponding author:
31
Professor Brigid Gillespie: [email protected] 32
33
Competing Interests 34
The authors declare that they have no competing interests. 35
36
Funding Statement 37
Brigid M. Gillespie acknowledges the financial support of the Australian Research Council, 38
Early Career Discovery Fellowship Scheme and the NHMRC Centre for Excellence in Nursing 39
Research (NCREN). 40
41
Authors’ Contributions 42
BMG conceived of the study, assisted in data analysis, interpreted results and drafted the 43
manuscript. EH performed data analysis and assisted in interpretation. WC assisted in 44
interpretation, and edited the manuscript for important intellectual content. EK, CS, TKW, 45
KS and NF assisted in recruitment and assisted in interpretation. All authors participated in 46
the coordination of the study and read and approved the final manuscript. 47
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Correlates of non-technical skills in surgery: A prospective study 51
ABSTRACT 52
Background: Communication and teamwork failures have frequently been identified as the 53
root cause of adverse events and complications in surgery. Few studies have examined 54
contextual factors that influence teams’ non-technical skills (NTS) in surgery. The purpose of 55
this prospective study was to identify and describe correlates of NTS. 56
Methods: We assessed NTS of teams and professional role at two hospitals using the 57
revised 23-item NOTECHS and its subscales (communication, situational awareness, team 58
skills, leadership, and decision making). Over 6 months, two trained observers evaluated 59
teams’ NTS using a structured form. Inter-observer agreement across hospitals ranged from 60
86%-95%. Multiple regression models were developed to describe associations between 61
operative time, team membership, miscommunications, interruptions, and total NOTECHS 62
and subscales scores. 63
Results: We observed 161 surgical procedures across eight teams. The total amount of 64
explained variance in NOTECHS and its five subscales ranged from 14% (adjusted R2 0.12, p < 65
.001) to 24% (adjusted R2
0.22, p < .001). In all models, inverse relationships between the 66
total number of miscommunications and total number of interruptions and teams’ NTS were 67
observed. 68
Conclusions: Miscommunications and interruptions impact on team NTS performance. 69
Strengths and limitations 70
• While we found relationships between miscommunications, interruptions and 71
surgical teams’ non-technical skills, the causal sequence between predictors and the 72
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outcome cannot be established. However, the design allowed us to describe 73
statistical associations and identification of some potential confounders. 74
• Surgical teams’ non-technical skills were assessed using direct observation and so it 75
is possible for individuals to alter their practices giving rise to the potential for the 76
Hawthorne effect Nevertheless contemporaneous observation is preferable to self 77
report which gives rise to an unintentional reporting bias. 78
• Measures upon which observations were based may be considered somewhat 79
subjective as they relied on observers’ ability to interpret events. However, 80
observers were experienced in observational research and trained in observational 81
research and human factors. 82
• There is potential for selection bias as surgical teams were purposively selected 83
based on participants’ willingness to be observed. Despite this, there was variability 84
in NTS scores. 85
Key words: teamwork, communication, interruptions, human factors, surgery 86
87
88
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INTRODUCTION 89
Compared to other hospital settings, medical errors in the operating room (OR) can 90
have catastrophic consequences for patients. Adverse events and malpractice claims have 91
been linked to teamwork failures in surgery.1-5 Deficits in teamwork behaviours were 92
identified as a root cause in 63% of all the sentinel events reviewed by The Joint Commission 93
between 2004 and 2013.6 While human error is inevitable and cannot be completely 94
eliminated, the importance of linking the safety of surgery to team culture is increasingly 95
recognised.7-9
Fostering a climate of teamwork and collaboration, along with safety minded 96
work processes that focus on error prevention is the ultimate goal of healthcare 97
organisations. 98
Nevertheless, surgical errors need to be understood in the context of the surgical 99
team. Unique challenges stem from the overlapping but different interprofessional 100
expertise and roles among members, ad hoc team team membership, unstructured and 101
variable communications, frequent distractions, technology, procedural complexity, and 102
competing priorities.10-15 Several studies have described the sources and frequencies of 103
intraoperative interruptions.14 16 17
The results of these studies identified that equipment 104
problems, telephone calls, conversation and environment problems (e.g., noise) were major 105
sources of distractions that influenced team performance. It is therefore hardly surprising 106
that as much as 30% of information gets lost during case-related exchanges.9 18
More recent 107
research suggests that omissions in team communications related to providing members 108
with updates about the progress of an operation comprised up to 36% of all observed 109
communication errors.19
As surgical teams often work together on an ad hoc basis, a lack of 110
prior working experience has the potential to impact on team dynamics. Team familiarity, 111
defined as a core group of individuals who work together regularly, and who share a similar 112
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mental model20, has been identified as an important element of effective teamwork.14 21 An 113
earlier observational study found that fewer miscommunications occurred in teams with a 114
history of working together.14 More recently, results of an Australian observational study 115
suggested a positive association between team familiarity and instrument nurses’ NTS 116
performance across 182 surgical procedures.10
Other studies, using retrospective designs 117
have found associations between team familiarity and reductions in postoperative 118
morbidity following cardiac and major abdominal surgeries. 21 22 119
As a means to increase surgical safety, researchers have focussed on 120
communication, leadership, situational awareness and decision-making, termed collectively 121
as non-technical skills (NTS) in surgery. NTS are the cognitive (i.e., decision making and 122
situational awareness) and interpersonal skills (i.e., communication, teamwork and 123
leadership) that complement the individual’s technical knowledge.23 Previous research 124
indicates that communication is key to the performance of successful teams. Effective and 125
timely transfer of information enables team processes and states such as coordination, 126
cooperation, conflict resolution and sitational awareness.9 11 24 The development of astute 127
NTS is critical to patient safety yet surgical teams are challenged by the increasing technical 128
complexity of surgery and high acuity of patients, who are older, and have multiple 129
comorbidities.8 Moreover there is a lack of research that examines the impact that 130
environmental factors have on teams’ NTS performance. In this prospective study, we 131
hypothesised that longer surgeries, limited team familiarity, miscommunications, and 132
interruptions negatively influenced teams’ use of NTS. A better understanding of the factors 133
that impinge on teamwork behaviours will help us to design strategies to improve NTS 134
performance. 135
136
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METHODS 137
This was a prospective, observational study of teams’ use of NTS during surgery. Two 138
Australian metropolitan hospitals 70 kilometers from each other, each with a similar case 139
mix, specialising in all surgical specialities, were included to generate results that would be 140
applicable across a variety of procedures. In each hospital, four surgical teams comprising of 141
anaesthetic and surgical consultants, their registrars, and instrument/circulating nurses, 142
were observed. Teams and surgical procedures across each hospital were purposively 143
chosen to ensure maximum variation relative to case complexity, particular procedures 144
within specialties, team membership, and surgical experience. In Hospital A, teams from 145
paediatric, thoracic, orthopaedic and general surgery were observed on a weekly basis 146
across 20-25 surgeries. In Hospital B, a similar number of surgeries was observed with 147
cardiac, vascular, upper gastro-intestinal, and hepatobiliary teams. 148
Observational data for each hospital were collected during 2015, with an observer 149
located at each hospital. Prior to the observation period, both observers underwent specific 150
training in the use of the observational tool which included the NOTECHS system. The 151
observers pilot tested the tool and minor changes made to its formatting. During the 152
piloting process, regular meetings were held with the co-resesrchers to ensure greater 153
clarification of recorded events and refine coding. Both observers were trained in human 154
factors and observational research methods. To ensure methodologic consistency, 155
interrater checks with 10% of cases at each hospital site were performed during the 156
observation period by the lead author, also trained in human factors. Interrater agreement 157
across hospital sites ranged from 86%-95%. A single observer was present during each 158
procedure and collected data using pre-specified checklists and free-hand notes. 159
Observations commenced when the patient entered the operating room (prior to 160
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anaesthesia) and ended when the patient left the room. During each surgical procdure, 161
observers documented explanatory field notes to supplement the structured observations 162
to better understand contextual factors. Observational data were collected in 2015 over 6-163
months. 164
Institutional ethics approvals were given by the participating hospitals and the 165
university. Participants signed a consent form and were advised of their right to 166
confidentiality and anonymity, and to withdraw at any time during data collection. Patients 167
whose operations were observed were informed of the likelihood of observations taking 168
place and given the chance to opt out. 169
170
Observational measures 171
We used the revised Non-TECHnical Skills (NOTECHS) scale 25, which was originally 172
developed in the aviation industry for crew resource management. The NOTECHS provides 173
comprehensive behavioural descriptors for each of its subscales and so requires less training 174
prior to use. In surgery, it has been shown to differentiate between good and poor 175
behaviours, thus has demonstrated good construct validity.25
In the revised NOTECHS, five 176
subscales of NTS are assessed: A. communication and interaction; B. situational awareness 177
and vigilance; C. team skills; D. leadership and managerial skills; and, E. decision making in a 178
surgical crisis. Each domain is measured on a 7-point scale to rate each item, with 1 = not 179
done through to 6 = done very well, and, 0 = not applicable 25. Total NOTECHS scores range 180
from 5-23 with higher scores indicative of better overall performance on all five subscales. 181
Scores for individual subscales were as follows; Subscales A and B scores ranged from 4-24 182
while Subscales C to E scores ranged from 5-30. The “not applicable” option meant that a 183
specific item was not relevant or could not be rated on the basis that the behaviour was not 184
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observed. However, participant NOTECHS scores were not affected by a reduced score for 185
non-observed behaviours. ‘Not applicable’ scores were replaced by the participant’s 186
individual item mean. In this study, as all subscales were considered of equal importance, 187
total NOTECHS scores were calculated by the number of items (i.e., 23) as the denominator. 188
Scores for total NOTECHS and its individual subscales were calculated using the mean of all 189
individual team members NOTECHS total scores. We also calculated the mean NOTECHS 190
scores based on professional role (i.e., surgeon, anaesthetist, nurse). 191
In this study, we drew on the literature for definitions and measurement of the 192
observational variables relative to team familiarty, miscommunication and interruption 193
events. Team familiarity was defined as a core membership of three members (i.e., surgeon, 194
anaesthetist, instrument and/or circulating nurses) who had worked together, weekly or 195
fortnightly, for a minimum of three months. 26 Prior to commencement of each surgical 196
procedure, the senior nurse in the room was asked by the observer about regularity, 197
stability, and length of time individual team members had worked together. The number of 198
familiar team members for each procedure were tallied and recorded. We used Lingard et 199
al’s.18 27
taxonomy to classify miscommunications (i.e., audience, content, occasion, 200
experience). Interruptions were classified according to Healey et al’s.16 28 framework (i.e., 201
procedural, conversational). For each procedure, we tallied the number of 202
miscommunications and interruptions in each of their respective categories. In some 203
instances, it was possible that a single miscommunication or interruption could be placed 204
into more than one category. As such, the primary prompt of the miscommunication or 205
interruption was deamed to categorise the event. Operative time included the time from 206
patient skin preparation to the application of the final wound dressing. 207
208
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Analyses 209
All analyses were performed using the Statistical Package for Social Sciences [SPSS] 210
(version 23, IBM, New York, NY, USA). Data were cleaned and a random sample of 20% was 211
checked for accuracy. Descriptive analysis included absolute (n) and relative (%) frequencies 212
to analyse categorical variables (discipline/role, surgical specialty), while means/standard 213
deviations [SD] or medians/interquartile range [IQR]) were used for continuous data (i.e., 214
operative time, number of interruptions, miscommunications, NOTECHS scores). 215
Independent variables; operative time, team familiarity, number of interruptions and 216
miscommunications were subsequently included as covariates in simultaneous multiple 217
regression models with the dependent variable, NTS (measured by NOTECHS). A p-value of 218
<.05 was considered significant and 95% confidence intervals (CI) were used. Cohen’s f2 was 219
used to calculate effect size. 220
221
Sample size calculation 222
Our a priori sample size estimate was based on the 20:1 rule which states that the 223
ratio of the sample size to the number of parameters in a regression model should be at 224
least 20 cases for each predictor variable in the regression model.29 30 As 4 predictor 225
variables were proposed in this study, a sample size of 100 was considered sufficient in a 226
parsimonious regression model. 227
228
229
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RESULTS 230
Across both hospital sites, a total of 161 operations were observed (Hospital A n=80; 231
Hospital B n=81). The number of surgeries observed for each team ranged from 20-25 with 232
the exception of the thoracic team. Owing to the retirement of the consultant surgeon in 233
the thoracic team, only 6 surgical procedures were observed in this specialty. In total, 481 234
individual participant’s observational data were collected (Hospital A n =243; Hospital B 235
n=238). The mean length of surgery across both sites was 116.3 minutes (±96.5) [Site A = 236
78.5 minutes, ±71.2; Site B, 153.7 minutes, ±103.8]. Across the 160 procedures we 237
observed, consistency in team membership ranged from 3-8 team members. On average 238
there were 7 team members present across all procedures including 2 surgeons, 2 239
anaesthetists, and 3 nurses. Table 1 shows case characteristics for each surgical specialty 240
relative to number of procedures in each specialty, operative time, team membership, and 241
NOTECHS scores (by Subscales A-E and mean total). Subscale E, decision-making during a 242
surgical crisis was observed in only 40-50% of cases as these situations were often not 243
observed during field work. Of the eight teams observed, the Hepatobiliary team had the 244
highest NOTECHS mean scores (20.7±2.3) while the cardiac team had the lowest (19.1±3.5). 245
Table 2 displays the descriptive results for NTS performance based on professional role. 246
Observed NTS performance among surgeons and anaesthetists was comparable however, 247
nurses scores were somewhat lower. 248
During each surgical procedure, the observers recorded field notes to better 249
understand and explain the contextual happenings during assessment of teams’ NTS. The 250
following two field notes are provided as exemplars of team communications from the251
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Table 1: Case Characteristics (n=161 Surgical Procedures) 252
Surgical
Specialty
Number of
Procedures
Observed
in each
Specialty
(n/total %)
Operative
Time (mins)
Mean (SD)
Team
Member-
ship
Mdn (IQR)
*Total
NOTECHS
Scores
Mean (SD)
^Subscale A
Communi-
cation and
interaction
Mean (SD)
^Subscale B
Vigilance
/situation
awareness
Mean (SD)
^Subscale C
Team skills
Mean (SD)
^Subscale D
Leadership
and magmt
skills
Mean (SD)
^Subscale E
Decision
making in a
crisis
Mean (SD)
General 25 (15.5) 119.5 (85.7) 4 (1) 18.7 (3.1) 19.8 (3.5) 20.0 (3.6) 23.9 (4.5) 23.8 (4.7) 24.3 (4.7)
Orthopaedic 25 (15.5) 82.3 (66.6) 4 (2) 20.3 (2.4) 21.0 (3.1) 21.8 (2.6) 25.9 (3.1) 26.7 (3.5) 26.3 (4.0)
Paediatric 25 (15.5) 35.0 (26.1) 3 (2) 20.5 (2.7) 21.5 (2.8) 21.9 (3.0) 26.1 (4.5) 26.5 (4.1) 27.1 (3.5)
Thoracic 6 (3.7) 74.1 (55.8) 4 (3) 19.6 (2.3) 21.6 (3.0) 20.8 (3.0) 25.2 (3.1) 24.6 (3.7) 25.1 (2.4)
Cardiac 20 (12.4) 234.4 (97.5) 8 (3) 18.4 (2.6) 19.1 (3.5) 20.7 (2.7) 22.8 (4.3) 22.5 (4.4) 24.8 (4.2)
Hepatobiliary 20 (12.4) 165.3 (122.2) 5 (1) 20.7 (2.3) 22.1 (2.4) 22.1 (2.5) 26.7 (3.3) 25.7 (3.8) 27.1 (4.0)
Upper GI 20 (12.4) 109.8 (78.6) 4 (2) 20.5 (2.6) 22.1 (2.9) 22.1 (2.5) 26.2 (3.7) 25.1 (4.1) 27.0 (4.7)
Vascular 20 (12.4) 105.4 (51.7) 6 (2) 20.1 (2.4) 22.1 (2.5) 21.9 (2.3) 25.3 (4.3) 23.9 (4.6) 26.6 (4.1)
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and E Scores in domain range 5-30. 253
254
255
256
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Table 2: Descriptives of NOTECHS performance based on professional role (n=481) 257
Surgeon
Consultant/
Registrar
Anaesthetic
Consultant/
Registrar
Scrub /
Scout Nurse
Total NOTECS
n 161 158 160
Mean 20.5 20.6 18.9
SD 2.1 2.4 3.2
95% CI 20.1-20.8 19.8-20.6 18.4-19.4
Range 14.5-23.0 11.64-23.0 10.04-23.00
Subscale A, Communication
and interaction
n 161 158 160
Mean 21.4 21.5 20.4
SD 2.8 2.87 3.7
95% CI 20.9-21.8 21.0-22.0 19.81-20.96
Range 10.0-24.0 10.0-24.0 10.00-24.00
Subscale B , Vigilance /
situational awareness
n 161 158 160
Mean 22.2 21.3 20.8
SD 2.2 2.6 3.6
95% CI 21.8-22.5 20.9-21.7 20.3-21.4
Range 16.0-24.0 11.0-24.0 8.0-24.0
Subscale C, Team skills
n 161 158 160
Mean 25.9 25.9 24.1
SD 3.5 4.0 4.6
95% CI 25.3-26.4 25.2-26.5 23.3-24.8
Range 15.0-30.0 11.00-30.0 10.0-30.0
Subscale D, Leadership and
management skills
n 161 158 160
Mean 25.5 25.5 23.8
SD 4.1 3.9 4.8
95% CI 24.9-26.2 24.9-26.1 23.0-24.6
Range 14.0-30.0 12.5-30.0 10.0-30.0
Subscale E , Decision making
in a crisis
n 161 158 160
Mean 27.5 27.0 23.6
SD 2.83 3.16 5.2
95% CI 27.1-28.0 26.6-27.6 22.8-24.4
Range 18.0-30.0 17.0-30.0 9.0-30.0
Note: *Total NOTECHS Scores range 1-23; ^Subscales A and B scores in domain range 4-24, Subscales C, D and 258
E Scores in domain range 5-30. 259
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highest and lowest performing teams on the NOTECHS. Ensuring that both the anaesthetic 260
and surgical teams had a similar mental model in relation to the procedure was important: 261
Prior to commencing a liver resection procedure, the Consultant and Registrar 262
Surgeons and the Anaesthetic Consultant participated in a detailed prebriefing 263
about the patient’s medical history and anticipated difficulties/challenges from 264
their discipline perspectives. These physicians had never worked together 265
before. Prebriefings between the lead surgeon and anaesthetist were 266
commonplace in this room and were observed to occur in 70% of the cases 267
observed. (Hepatobiliary: Hepatectomy, Case # 18). 268
The following fieldnote illustrates an observed miscommunication between the 269
surgeon and perfusionist: 270
Consultant Surgeon to Perfusionist, “Give pledgia.” 271
Perfusionist: “Give another one?” 272
Consultant Surgeon: ”‘Have you finished with the previous one?” 273
Perfusionist: “Yes”. Consultant Surgeon appears to be unaware of pledgia 274
delivery time. There was no further inquiry from the Consultant Surgeon. 275
(Cardiac: CABGS x 4, Case # 9). 276
Across the 161 procedures, the number of miscommunications totalled 436 (Hospital A 277
n=133; Hospital B n=303). The highest number of miscommunications was observed in 278
cardiac surgery (n=121). Throughout the observed procedures, interruptions occurred in 279
106/161 (65.8%) cases. Of the 106 procedures where interruptions were observed, 280
procedural interruptions occurred at least once in 92 procedures (86.8%) (Hospital A n=118; 281
Hospital B n=76). The number and types of miscommunications and interruptions for each 282
surgical specialty appear in Figures 1 and 2. 283
284
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Multivariate regression analyses 285
Table 3 shows the six multiple regression models for total NOTECHS scores and its 286
individual subscales (A-E). The total amount of explained variance in NOTECHS and its 287
individual subscales ranged from 14% (adjusted R2 0.12, p < .001) to 24% (adjusted R2 0.22, 288
p < .001). In all six regression models, the total number of miscommunications and 289
interruptions were consistently significant predictors of teams’ NTS (Table 3). Operative 290
time and team membership were non-significant. 291
292
DISCUSSION 293
To the best of our knowledge, this is the first study to examine the correlates of 294
teams’ NTS. This study is also one of the largest single observational studies in this field. 295
Notably, we found inverse associations between the number miscommunications and 296
interruptions and team NTS across all NOTECHS subscales, suggesting that the fewer 297
miscommunications and interruptions there are, the higher teams’ NTS performance. These 298
results seem intuitive but, this study is the first to provide evidence generated through 299
structured observations conducted in real time (rather than in simulated environments). In 300
this study, we observed fewer interruptions as compared with miscommunications; with the 301
highest number of interruptions seen in the general surgery team. Many interruptions may 302
be considered acceptable when there are no immediate demands from patient care, but are 303
clearly less appropriate at busy times or when problems occur.31 Some interruptions are 304
essential for information sharing, or to talk to and reassure patients, but managing 305
interruptions and distractions is a crucial skill and requires individuals to refocus on their 306
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Table 3: Regression models for predictors of total NOTECHS and each NOTECHS domain (n=161 Surgical Procedures) 307
95% CI
Model Predictor Variable B
Std
Error β t Sig
Lower
Bound
Upper
Bound a
Team NOTECHS Constant 20.70 .38 - 55.01 <.001 19.96 21.45
Team Familiarity .01 .08 .01 .14 .893 -.15 .18
Operative Time .00 .00 .10 .97 .334 -.00 .01
Miscommunications -.27 .06 -.41 -4.82 <.001 -.38 -.16
Interruptions -.29 .12 -.19 -2.44 .016 -.52 -.05 bSubscale A
Communication and
interaction Constant 22.17 .44 - 50.18 <.001 21.30 23.05
Team Familiarity -.04 .10 -.04 -.42 .674 -.23 .15
Operative Time -.00 .00 -.07 -.66 .512 .00 .01
Miscommunications -.23 .07 -.31 -3.57 <.001 -.36 -.10
Interruptions -.35 .14 -.21 -2.54 .012 -.62 -.08 c Subscale B
Vigilance/situation
awareness Constant 21.76 .41 - 55.62 <.001 20.96 22.56
Team Familiarity .09 .09 .09 1.04 .299 -.08 .27
Operative Time .00 .00 .14 1.40 .163 -.00 .01
Miscommunications -.23 .06 -.33 -3.83 <.001 -.35 -.11
Interruptions -.36 .13 -.23 -2.86 .005 -.61 -.11 d
Subscale C
Team skills Constant 26.72 .58 - 46.19 <.001 25.58 27.87
Team Familiarity -.04 .13 -.03 -.32 .753 -.29 .21
Operative Time .00 .00 .04 .41 .686 -.01 .01
Miscommunications -.38 .09 -.38 -4.49 <.001 -.55 -.21
Interruptions -.30 .18 -.13 -1.65 .101 -.66 .06
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e Subscale D
Leadership and
management skills Constant 26.67 .56 - 47.72 <.001 25.57 27.78
Team Familiarity -.13 .12 -.09 -1.09 .277 -.38 .11
Previous training .01 .00 .15 1.59 .115 -.00 .01
Miscommunications -.57 .08 -.51 -6.26 <.001 -.68 -.35
Interruptions -.21 .18 -.09 -1.23 .222 -.56 .13 f Subscale E
Decision making
in a crisis Constant 26.65 .56 - 47.92 <.001 25.55 27.75
Team Familiarity .16 .12 .11 1.31 .192 -.08 .40
Operative Time .01 .01 .03 .26 .793 -.01 .01
Miscommunications -.30 .08 -.32 -3.63 <.001 -.46 -.14
Interruptions -.45 .17 -.21 -2.58 .011 -.79 -.11
Note model results 308 a
R=.43, R² .18, R² Adj .16, F= 8.65 df(4/160), p<.001, (f2)=.22
b R=.37, R² .14, R² Adj .12, F= 6.22 df(4/160), p<.001, (f
2)=.16
c R=.37, R² .14, R² Adj .12, F= 6.23 df(4/160), p<.001, (f
2)=.16
d R=.41, R² .17, R² Adj .15, F= 7.82 df(4/160), p<.001, (f
2)=.20
e R=.49, R² .24, R² Adj .22, F=12.27df(4/160), p<.001, (f
2)=.32
f R=.38, R² .15, R² Adj .12, F= 6.56 df(4/160), p<.001, (f
2)=.18
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primary task.14 Interruptions have identified as a major contributor to loss of
vigilance in anaesthetists.31
While teams and individuals scored reasonably highly on the
NOTECHS and its subscales, the lowest NTS performance was observed in relation to
vigilence/situation awareness across all teams. Clearly, miscommunications and
interruptions have the potential to erode individual and distributed situational awareness in
surgery.14 31
The hepatobiliary team had the highest NTS performance, as indicated by their
NOTECHS scores. The hepatobiliary team also had the lowest number of
miscommunications during the fieldwork period. In field notes, the observer described
routine preoperative discussions that occurred between physicians prior to case start, the
low levels of environmental and conversational noise, and frequent occasions of closed loop
communications between members, which heightened levels of distributed situational
awareness among team members. Taken together, these features contributed to the
smooth coordination of team tasks and patient care processes during these lists.
Conversely, the cardiac team demonstrated the lowest NTS performance, which was
unexpected given that this team had clearly defined roles and a small repertoire of
procedures that were ‘routine’ and well-rehearsed. Remarkably, this team also had the
greatest number of observed miscommunications during the field work period. Notably, the
degree of difficulty and complexity, technical skills, stress, and patients’ instability and
acuity may be highest in cardiac surgery.13 32 Observer described (in field notes) the
considerable environmental, technological and team-related challenges experienced by the
cardiac during the surgery, which added to case complexity. For instance, the high noise
levels in this room, attributed to team communications and technology, e.g., cross
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conversations, repeated requests from the surgeon to the perfusionist who was distracted
by other team members and/or equipment problems, incessant alarms during the
intraoperative period. Additionally, procedural and conversational interruptions as a result
of the entry of external team members into the room to ask questions, the referral of cell
phone calls that occasionally demanded the recipient to leave the room, contributed to
lower observed NTS in the cardiac team.
Although we had good sampling across surgical specialties and procedures, it is
difficult to speculate about whether the differences in NTS performance can be attributed
to hospital sites, specialties, surgical teams, or individuals. The two hospital sites chosen
were similar in relation to case mix, patient acuity and surgical activity. However the
selection of specialties varied in each hospital, which may in part, explain the differences in
NTS we observed across teams. The observed diffierences may also be attributed to
particular individuals, i.e., good leadership of the consultant surgeon has been linked with
effective team behaviour and task accomplishment.33 Arguably, surgeons may establish
aspects of leadership prior to the start of the procedure to condition intraoperative team
performance. For instance, using the surgical safety checklist or having a team briefing can
contribute to building the team’s shared mental model, and hence increasing distributed
situational awareness.34
Strengths and Limitations
This study has several strengths but we also recognise some limitations: First, while
we found relationships between miscommunications, interruptions and surgical teams’ NTS,
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temporal order and causality cannot be established. Thus there may be some competing
explanations for these results. Notwithstanding, the design does allow statistical
associations and identification of some potential confounders; but, not all have necessarily
been identified. Second, surgical teams’ NTS were evaluated through direct observation.
Although most research in this area has been largely observational and has focussed on
refining this methodology 9 16 17 26 35, individuals may have altered their practices in response
to being observed. Nevertheless contemporaneous observation is a preferred method to
self report which could be flawed (giving rise to response bias). The observational nature of
the NOTECHS allowed us to measure performance as it happened, rather than a
retrospective self report. Third, the measures upon which the observations were based may
be considered somewhat subjective as they rely on observers’ ability to interpret events.
Yet, observers were experienced OR nurses, trained in observatimal research and in human
factors. Interrater consistency between observers was acceptable. Additionally, the
measures we used have been previously validated in this field. 25-27 35 Fourth, surgical teams
were purposively selected based on participants’ willingness to be observed. Thus there is
the potential for selection bias. Notwithstanding, the, and there was variability in NOTECHS
scores. Finally, in this sample the amount of explained variance in NTS and its subscales
while reasonable, indicates that there are unknown predictors that warrant further
exploration. Despite these limitations, our results contribute to identifying interventions
that specifically target minimising miscommunications and interruptions, both of which are
modifiable with the ultimate goal of improving NTS in surgery.
CONCLUSIONS
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Our observational results suggest that effective communication and interruptions were
consistent corrrelates of surgical teams’ NTS performance. Across teams, we observed
examples of good and poor NTS performance. Notwithstanding, these correlates of team
performance are amenable to improvement or change. Implementation of interdisciplinary
team training may contribute to improvements in NTS. However such training programs
need to be underpinned by behaviour change frameworks that focus on sustained
improvements in NTS performance. It is reasonable to propose that the behavioural
indicators of success for overall performance are transferrable acr
Words: 3,523 (excluding references, figures and tables)
Contributors
BMG conceived of the study, assisted in data analysis, interpreted results and drafted the
manuscript. EH performed data analysis and assisted in interpretation. WC assisted in
analysis and interpretation. EK, CS, and NF assisted in recruitment and interpretation. All
authors participated in the coordination of the study and read and approved the final
manuscript.
Funding
Brigid M. Gillespie acknowledges the financial support of the Australian Research Council,
Early Career Discovery Fellowship Scheme and the NHMRC Centre for Excellence in Nursing
Research (NCREN).
Competing interest
None declared.
Ethics approval
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Metro South Health Human Research Ethics Committee
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Table Legend
Table 1: Case Characteristics (n=161 Surgical Procedures)
Table 2: Descriptives of NOTECHS performance based on professional role (n=481)
Table 3: Regression models for predictors of NOTECHS and each NOTECHS domain (n=161
Surgical Procedures)
Figure Legend
Figure 1: Total number of miscommunications across 8 specialties
Figure 2: Total number of interruptions across 8 specialties
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Figure 1
477x207mm (300 x 300 DPI)
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Figure 2
466x199mm (300 x 300 DPI)
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Correlates of NOTSS in surgery
1
STROBE Statement—checklist of items that should be included in reports of observational studies
Item
No Recommendation
Checklist/page
Title and abstract 1 (a) Indicate the study’s design with a commonly used term in the
title or the abstract
3
(b) Provide in the abstract an informative and balanced summary
of what was done and what was found
3
Introduction
Background/rationale 2 Explain the scientific background and rationale for the
investigation being reported
5
Objectives 3 State specific objectives, including any prespecified hypotheses 6
Methods
Study design 4 Present key elements of study design early in the paper 7
Setting 5 Describe the setting, locations, and relevant dates, including
periods of recruitment, exposure, follow-up, and data collection
7
Participants 6 (a) Cohort study—Give the eligibility criteria, and the sources and
methods of selection of participants. Describe methods of follow-
up
Case-control study—Give the eligibility criteria, and the sources
and methods of case ascertainment and control selection. Give the
rationale for the choice of cases and controls
Cross-sectional study—Give the eligibility criteria, and the
sources and methods of selection of participants
7-8
(b) Cohort study—For matched studies, give matching criteria and
number of exposed and unexposed
Case-control study—For matched studies, give matching criteria
and the number of controls per case
Variables 7 Clearly define all outcomes, exposures, predictors, potential
confounders, and effect modifiers. Give diagnostic criteria, if
applicable
8
Data sources/
measurement
8* For each variable of interest, give sources of data and details of
methods of assessment (measurement). Describe comparability of
assessment methods if there is more than one group
7-8
Bias 9 Describe any efforts to address potential sources of bias 8,19
Study size 10 Explain how the study size was arrived at 10
Quantitative variables 11 Explain how quantitative variables were handled in the analyses. If
applicable, describe which groupings were chosen and why
9
Statistical methods 12 (a) Describe all statistical methods, including those used to control
for confounding
9-10
(b) Describe any methods used to examine subgroups and
interactions
10
(c) Explain how missing data were addressed 9-10
(d) Cohort study—If applicable, explain how loss to follow-up was
addressed
Case-control study—If applicable, explain how matching of cases
and controls was addressed
NA
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Correlates of NOTSS in surgery
2
Cross-sectional study—If applicable, describe analytical methods
taking account of sampling strategy
(e) Describe any sensitivity analyses 9-10
Results
Participants 13* (a) Report numbers of individuals at each stage of study—eg numbers potentially
eligible, examined for eligibility, confirmed eligible, included in the study,
completing follow-up, and analysed
10-11
(b) Give reasons for non-participation at each stage
(c) Consider use of a flow diagram
Descriptive data 14* (a) Give characteristics of study participants (eg demographic, clinical, social) and
information on exposures and potential confounders
11,13
(b) Indicate number of participants with missing data for each variable of interest
(c) Cohort study—Summarise follow-up time (eg, average and total amount)
Outcome data 15* Cohort study—Report numbers of outcome events or summary measures over
time
NA
Case-control study—Report numbers in each exposure category, or summary
measures of exposure
Cross-sectional study—Report numbers of outcome events or summary measures
Main results 16 (a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates
and their precision (eg, 95% confidence interval). Make clear which confounders
were adjusted for and why they were included
10
(b) Report category boundaries when continuous variables were categorized
(c) If relevant, consider translating estimates of relative risk into absolute risk for a
meaningful time period
Other analyses 17 Report other analyses done—eg analyses of subgroups and interactions, and
sensitivity analyses
11,12,16
Discussion
Key results 18 Summarise key results with reference to study objectives 17
Limitations 19 Discuss limitations of the study, taking into account sources of potential bias or
imprecision. Discuss both direction and magnitude of any potential bias
19
Interpretation 20 Give a cautious overall interpretation of results considering objectives, limitations,
multiplicity of analyses, results from similar studies, and other relevant evidence
18
Generalisability 21 Discuss the generalisability (external validity) of the study results 18
Other information
Funding 22 Give the source of funding and the role of the funders for the present study and, if
applicable, for the original study on which the present article is based
1
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and
unexposed groups in cohort and cross-sectional studies.
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and
published examples of transparent reporting. The STROBE checklist is best used in conjunction with this article (freely
available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is
available at www.strobe-statement.org.
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on March 23, 2021 by guest. P
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jopen.bmj.com
/B
MJ O
pen: first published as 10.1136/bmjopen-2016-014480 on 30 January 2017. D
ownloaded from