Study reference

Study characteristics

Patient or team characteristics ²

Intervention (I)

Comparison / control (C) ³

Follow-up

Outcome measures and effect size ⁴

Comments

Attarian, 2003

Type of study: Before-and-after intervention study with retrospective OR time data and prospective workflow data.

Recommendations were formulated,

implemented, and revised quarterly. Three years OR data was gathered.

Setting: Single centre, Academic

Specialism: total joint arthroplasty

Country: USA

Source of funding/conflict of interest: Each author certifies that he or she, or a member of his or her

immediate family, has no funding or commercial associations (eg,

consultancies, stock ownership, equity interest, patent/licensing

arrangements, etc) that might pose a conflict of interest in connection

with the submitted article.

Inclusion criteria:

Not applicable (NA)

Exclusion criteria:

NA

N total at baseline:

NA

Number of days of ORs, or teams was not reported.

Important prognostic factors²:

NA, OR teams were evaluated

Groups comparable at baseline?

Unclear

High-efficiency Operating Room:

Key strategies

included dedicated OR efficiency teams, parallel processing,

dedicated hospital resources, and modified physician behaviour

Before implementation of the High-efficiency Operating Room

Length of follow-up:

3 years after implementation

Loss-to-follow-up:

Not applicable

Incomplete outcome data:

Not applicable

2. Efficiency

On-time OR starts (%)

2007:<60%

2011>90%

Average turnover times (minutes)

2007: >60

2011: 35

Average length of stay (days)

Primary

2007: 3.5

2011: 3.1

Revision

2007: 4.4

2011: 3.4

No statistics were performed

Very few details presented

Author’s conclusion:

Our project achieved improved OR efficiency

and productivity using strategies such as process and resource analysis, improved communication, elimination of silo mentalities, and team work.

Carter-Brooks, 2018

Type of study: retrospective

cohort study

Setting: single surgeon at two institutions in one health system

Specialism: robotic-assisted sacrocolpopexy (RASC)

Country: USA

Source of funding/conflict of interest: The authors declare that they have nothing to disclose.

Inclusion criteria:

-all RASCs performed

for pelvic organ prolapse (POP) from June 2010 to August 2015 performed by a

single surgeon with a Female Pelvic Medicine and Reconstruction

Surgery fellow at 2 institutions within the University of Pittsburgh

Medical Center Health System

Exclusion criteria:

-surgeon performed cases without a fellow due a concern for the presence of a fellow being a potential confounder.

N total at baseline:

Intervention: 17

Control: 71

Important prognostic factors²:

Mean age ± SD:

I:60.2 ± 8.65

C: 62.53 ± 10.76

Mean BMI ± SD:

I: 28.71(4.16)

C: 28.45 (5.23)

Groups comparable at baseline?

Yes, for age, parity, race, bmi, premenopausal state, smoking status, medical history, surgical history and Preoperative POP-Q prolapse

Stage. (all P > 0.05).

The community based

hospital had a dedicated robotic team in the operating room

The academic center did not have a dedicated robotic team in the operating room

Length of follow-up:

All RASCs performed

for POP from June 2010 to August 2015. Follow-up of outcomes measures was in-hospital, based on hospital records.

Loss-to-follow-up:

Not applicable, retrospective data

Incomplete outcome data:

Not applicable, retrospective data

1. Clinical outcomes

Composite complications, n (%) (composite

variable that included ≥1 blood transfusion, bladder injury, bowel injury, and conversion to laparotomy)

Dedicated team: 0 (0)

Non-dedicated team: 1 (1.41), p=0.637

2. Efficiency

Mean operative time (min ± SD:)

Dedicated team: 131.8 ± 18.9

Non-dedicated team: 160.2 ± 28.2

Mean decrease:28.4 min for a 17.7% time reduction (P < 0.001 Decrease after multivariable regression: β = −25.98 minutes, P < 0.001) and adjusting for case order on the day (β = −8.6 minutes, P = 0.002) and prior hysterectomy (β = −36.1 minutes, P < 0.001).

Univariate model included: Case order on the day, prior hysterectomy, concomitant

oophorectomy, post-menopausal status,

concomitant midurethral sling, concomitant lysis of adhesions, any major complication, any past medical history, BMI, fellow PGY level, pre-op POP-Q Stage.

Length of hospital stay, mean (sd) in days

Dedicated team: 1.29 (0.30)

Non-dedicated team: 1.20 (0.35)

P=0.385

Readmission, n (%)

Dedicated team: 0 (0)

Non-dedicated team: 3 (4.4)

P=0.545

Author’s conclusion:

A dedicated robotic team during robotic-assisted

sacrocolpopexy significantly decreased operative time by 26 minutes, a 17.7% reduction at our institution.

Lim, 2013

Type of study: Prospective observational study design

where the participants served as their own controls

Setting: University

Hospital

Specialism: patients with biliary tract disease (Acute care)

Country: USA

Source of funding/conflict of interest: Not rpeorted

Inclusion criteria:

all patients with biliary tract disease

admitted to the UAH for the periods of 1 July 2005 to 30

June 2006, 2006, and from 1 July 2007 to 30 June 2009 (1 year

pre-ACS implementation and 2 years post-ACS implementation;

the period 1 July 2006 to 30 June 2007 was

omitted.

Exclusion criteria: patients who

were treated nonoperatively, had an elective cholecystectomy,

or had a primary etiology for admission other than biliary tract disease. Incidental cholecystectomies as part of

another planned operative procedure were also excluded.

N total:

Intervention: 72

Control: 172

Important prognostic factors²:

age:

I: 49.7

C: 51.2

Sex:

I: 51.4 M

C: 44.8% M

Groups were comparable at baseline for all demographics. Statistically significant greater number of

acute cholecystitis diagnoses post-ACS compared to the pre-ACS. There were no significant differences in the other diagnoses.

The ‘‘acute care surgery’’ (ACS) model proposes a dedicated surgical team to address various acute surgical conditions.

The Acute Care Emergency Surgery (ACES) service is comprised of nine dedicated surgeons who rotate weekly, as well as a

senior resident, two junior residents, and two hospitalists.

For a particular week, the designated ACES surgeon and team is on call daily from 07h00 to 19h00 (12 h). At 19h00, a second surgeon and resident team (which varies nightly) takes over call duties until 07h00 the following morning, at which time care is handed back to the designated ACES team. Handovers therefore occur every morning at 07h00 and every evening at 19h00 between the daytime ACES team and the variable night-time ACES team. The ACES service is unique because of funding that allows for a dedicated emergency general surgery daytime operating room that operates during weekday daytime hours from 07:30 to 15:30.

Before implementation of the ACS model

Length of follow-up:

Observations in the two years after implementatie

Loss-to-follow-up:

NA

Incomplete outcome data:

NA

1. Clinical outcomes

Complications: several categories (no composite measure)

2. Efficiency

Mean time from admission/decision to OR in hrs (SD)

pre-ACS: 31.1 (21.4)

post-ACS: 21.5 (14.2)

(p<0.001)

Mean operative time

pre-ACS: 78.8 (35.9)

post-ACS: 98.9 (46.9)

(p = 0.0013)

Mean hospital length of stay in days (SD)

pre-ACS: 6.0 (4.5)

post-ACS: 6.0 (5.4)

NS

Number of patients awaiting daytime

operating room availability

pre-ACS: 95.8%

post-ACS: 60.7%

p<0.001

OR start time past daytime

Hours

pre-ACS: 29.2%

post-ACS: 7%

p<0.001

OR start at night after

waiting for daytime OR

pre-ACS: 26.1%

post-ACS: 7.9%

p<0.001

Author’s conclusion:

We observed a significant decrease in preoperative

time by 10 h with increased access to a readily available operating room.

Having a dedicated ACS team is important, but it is equally important to have a dedicated

operating room with disposable time to care for unpredictable,

emergent cases to realize the full potential benefit

of the ACS model.

McCulloch, 2017

Type of study: Suite of 5 identical controlled before–after intervention studies, with

pre-planned analysis of pooled data for indirect comparisons of strategies.

Setting: Operating theatres in 5 hospitals performing elective surgery

Specialism: elective orthopedic,

plastic, or vascular surgery

Country: UK

Source of funding/conflict of interest: funded by a program grant for applied research

from the UK National Institute for Health Research (NIHR),

The authors report no conflicts of interest.

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline: (observed operations)

All interventions: 255

Control: 198

Before intervention: 219

After interventions:234

Important prognostic factors²:

NA

Control team for each active team was selected from the same hospital Trust, and wherever possible

performed the same type of surgery.

Contamination of controls by circulation of personnel or informal exchange of information was

minimized by selecting teams, geographically or functionally distinct

from the intervention teams.

The three intervention strategies evaluated were:

(a) Teamwork training based on aviation crew resource management

(TT). This training intervention has been widely used in

healthcare, and concentrates on fostering mutual support and

clear communication within teams.

(b) Standard operating procedures (SOP). The use of principles from Ergonomics to analyze, redesign, and standardize work systems and processes.

(c) Lean thinking (Lean). A systems redesign approach, which concentrates on eliminating waste, making error visible, and

engaging staff.

study 1: SOP

study 2: Lean

study 3: TT

study 4: SOP & TT

study 5: TT & Lean

Interventions

commenced with group training sessions, followed up with coaching or group meetings, and lasted four months. Three months of direct observation of operations was carried out before, and again after each

intervention period.

Comparisons before implementation and with control group: active-operating teams with no training

Length of follow-up:

Interventions

commenced with group training sessions, followed up with coaching

or group meetings, and lasted four months. Three months of direct

observation of operations was carried out before, and again after each

intervention period

Loss-to-follow-up:

NA

2. Efficiency

Glitch count in active intervention group (pooled all results:

Before: 7.27 per hour

After: 6.80 per hour

Glitch count in control group (pooled all results:

Before: 7.58 per hour

After: 9.76 per hour

Difference in change

P=0.0014

Mean Glitch count in active intervention TT group (sd):

Before: 7.21 (2.73) per hour

After: 10.20 (3.67) per hour

Difference: 2.99 (95% CI 1.16-4.82)

3. Teamwork and communication

NOTECHS II in active intervention group (pooled all results):

Before: 72.98

After: 76.56

Difference: 3.47 (95% CI 1.56–5.37)

NOTECHS II in control group (pooled all results):

Before: 73.31

After: 73.03 after

Difference: -0.21 (95% CI -1.85–2.28)

Difference in change

(P = 0.025)

NOTECHS II in active intervention TT group:

Before: 71.62

After: 75.68

Difference: 4.06 (95% CI 0.93-7.20)

Author’s conclusion:

Safety interventions combining teamwork training

and systems rationalization are more effective than those adopting either

approach alone. This has important implications for safety improvement

strategies in hospitals.

Mcculloch,

2009 (included in review Sun, 2018)

Type of study: uncontrolled before–after study

Setting: theatre

suite of one UK teaching hospital.

Specialism: laparoscopic cholecystectomy (LC) and carotid endarterectomy

(CEA) operations

Country: UK

Source of funding/conflict of interest: Project grant from the BUPA

Foundation, with additional funding from the Oxford Hospitals Medical Research Fund.

No conflicts of interests.

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline (observed operations):

Before: 48

After: 55

Important prognostic factors²:

NA

Groups comparable at

Baseline?

Unknown

A 9 h classroom non-technical skills

course based on aviation ‘‘Crew Resource Management’’ (CRM) was offered to all staff, followed by 3 months of twice-weekly coaching from CRM experts.

All personnel (n=83) regularly involved in LC or CEA procedures

were invited to the classroom sessions, and 54 (65%) attended.

Before implementation

Length of follow-up:

We first observed performance and outcomes in a series of

operations, then introduced a training intervention, and finally

conducted a second observation period. The three phases lasted

6, 3 and 6 months respectively.

Loss-to-follow-up:

NA

1. Clinical outcomes

complications

Before: 5

After: 3

No statistics

Critical incidence report

Before: 0

After: 1

No statistics

2. Efficiency

Mean Operating technical

Errors (sd)

Before: 1.73 (1.5)

After: 0.98 (0.9)

P=0.009

Mean operating time in minutes (sd)

Before: 103.7(38.9)

After: 101.2 (49.1)

p=0.770

Mean length of stay in days (sd)

Before: 2.23 (0.7)

After: 2.02 (0.6)

P=0.086

3. Teamwork

Mean total NOTECHS (sd)

Before: 37.0 (4.3)

After: 38.7 (3.2)

p=0.021

SAQ teamwork climate (6 items, 5 point likert scale equals scale 1-30 =assumption)

Before: 64.1 (18.9)

After: 69.2 (18.2)

P=0.007

Author’s conclusion:

The operating time was

unchanged, and a non-significant reduction in LOS was observed. Non-technical skills training improved technical performance in theatre, but the effects varied between teams. Considerable cultural resistance to adoption was

encountered, particularly among medical staff. Debriefing and challenging authority seemed more difficult to introduce than other parts of the training. Further studies are needed to define the optimal training package, explain variable responses and confirm clinical benefit.

Forse, 2011

(included in review Sun, 2018)

Type of study: Retrospective cohort study (before-and-after measures)

Setting: One teaching

hospital

Specialism: All ORs

Country: USA

Source of funding/conflict of interest: Not reported

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline:

NA

Number of days of ORs, or teams was not reported.

Important prognostic factors²:

Not applicable, OR teams were evaluated

TeamSTEPPS program for all OR staff

The training occurred over 2 months in 2006-2007 to all members of the OR team, including scrub technicians, nurses, certified registered nurse anesthetists, anesthesiologists,

surgeons, and all anesthesiology and surgical resident staff.

Top-down approach with coaches program Champions by key members (those interested in team training) of anesthesiology, anesthesiology

residents, certified registered nurse

anesthetists, nursing, scrub technicians, surgeons, and surgical residents.

End 2007 there was termination of the program with no further training and support for mentoring, and the coaches.

Before training program implementation

Length of follow-up:

9 months after intervention

21 months after intervention (without support)

Loss-to-follow-up:

NA

Incomplete outcome data:

NA

1. Clinical outcomes

Mortality

Change in % in first 9 months: 2.7% to 1% (P <.05)

Change in % after 21 months: 1% to 1.5%; P <.05

Morbidity (complicaties)

Change in % in first 9 months: 20.2% to 11.0%, P <.05

Change in % after 21 months: 11% to 13%; P <.05

2. Efficiency

OR first case starts on time

Change in % in first 9 months: 69% to 87%

Change in % after 21 months: 87% to 69%

Turnover time

Change in first 9 months: 43 ± 2.4 minutes to 35.5 ± 2.1 minutes (P < .05).

Change after 21 months: decreased to 26.8 ± 1 minutes

3. Teamwork and communication

OR staff team work

After 9 months: score 53.2 to 62.7 (scale unclear) ; P < .05

OR communications

score 47. 5 to 62.7 (scale unclear); P < .05

Author’s conclusion

These data confirm that team training improves OR performance, but continued team

training is required to provide sustained improved OR culture.

Duclos,

2016 (included in review Sun, 2018)

Type of study: prospective cluster RCT

Setting: Multi-centre study, public

and private hospitals

Specialism: 31 surgical departments, included procedures in

orthopaedics, digestive surgery, urology, gynaecology,

cardiovascular surgery and neurosurgery

Country: Located in 4 geographical areas in France

Source of funding/conflict of interest: All phases

of this study were supported by a grant from the Hospital

Clinical Research Programme

Disclosure: The authors declare no conflict of interest.

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline:

Intervention: 16, 8623 patients hospitals

Control: 15, 8222 patients

In total, 22 779 patients were enrolled, including 5934 during a 4-month pre-implementation period.

Important prognostic factors²:

age ± SD:

I: 57.9(18.9)

C: 59.1(19.0)

Sex:

I: 41.4 % M

C: 50.1% M

Groups comparable at baseline?

No differences in patient characteristics and procedures between intervention and control hospitals

Team training was implemented in 16 hospitals allocated to the intervention arm over the next 11 months.

Team training was provided specifically to operating room staff within surgical departments in the intervention hospitals, including surgeons, anaesthetists, nurses and quality managers.

The intervention consisted of two half-day sessions held in each hospital at 6-month intervals.

The first training session focused on three major concepts of CRM: situational awareness, team synergy and interpersonal communication.

The second training session was tailored to each site, the major goal being to encourage the effective implementation of checklists and CRM principles by every surgical

team.

The overall attendance rate during the first session was 69.6% cent among the 481 operating room staffmembers in intervention hospitals.

All sites had implemented the WHO SSC checklist a median of 20

months before the start of the study.

No specific action was undertaken among the 15 hospitals allocated to the control arm.

All sites had implemented the WHO SSC checklist a median of 20

months before the start of the study.

Length of follow-up:

In-hospital (until discharge or for 30 days after the operation)

Loss-to-follow-up:

NA

Incomplete outcome data:

NA

1. Clinical outcomes

Major adverse events during surgery and postoperative hospital stay (including both death and complications)

I: pre-impl: 8.8%

I: post-impl: 5.5%

 (P <0.001)

C: pre-impl: 7.9%

C: post-impl: 5.4%

(P <0.001)

Adjusted analyses (adjusted for geographical area, surgical specialty

and medical record format regarding hospital-level

co-variables):

I: OR 0.57, 95% CI 0.48 to 0.68; P <0.001

C: OR 0.64, 95% CI 0.50 to 0.81; P <0.001

ROR (ratio of the odds ratios): 0.90; P =0.474,

Major adverse events consisted of:

Intraoperative complications:

ROR 1.23; P =0.395

Postoperative complications:

ROR 0.88; P =0.468

Inpatient mortality:

ROR 0.81; P =0.581

Author’s conclusion

Surgical outcomes improved substantially, with no difference between trial arms. Successful

implementation of an aviation-based team training programme appears to require modification and

adaptation of its principles in the context of the surgical milieu.

Morgan, 2015b

Type of study: controlled interrupted time series study

Setting: 3 operating theatres in a district general hospital, 1 acting as a control group and the other 2 as the intervention group.

Specialism: elective orthopaedics

and vascular/

general surgery

Country: UK

Source of funding/conflict of interest: funded by the National

Institute for Health Research (NIHR) under its Programme Grants for Applied

Research programme

No conflicts of interests.

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline: (observations)

Active before:26

Active after: 25

Control before: 11

Control after: 10

Clinical outcome data based on hospital records

Important prognostic factors²:

Mean age

Active before: 57.8

Active after: 57

Control before: 51.7

Control after: 52.2

Sex (% male):

Active before: 48%

Active after: 48%

Control before: 52%

Control after: 51%

Comparable surgery type between groups. Control group had at baseline younger patients and shorter mean duration of surgery.

Two 3 h sessions teamwork training course and communications

training based closely on aviation CRM for all staff, followed by 6 weeks of weekly in-service coaching to embed learning.

No training (control)

Active (before)=before training

Length of follow-up:

observations made for 3 months before and

3 months after a 3-month intervention period

Loss-to-follow-up:

NA

1. Complication

Complication rate, n (%)

Active before: 140 (21.5)

Active after: 185 (26.8)

Control before: 162 (27.1)

Control after: 106 (25.7)

Change difference: p=0.05

Readmission rate, n (%)

Active before: 72 (13)

Active after: 74 (11)

Control before: 51 (8.5)

Control after: 37 (9.0)

Change difference: p=0.25

2. Efficiency:

Mean operation time in minutes (range)

Active before: 113 (61–235)

Active after: 115 (73–219)

Control before: 98 (30–144)

Control after: 71 (30–140)

Mean glitch rate per operation per hour (sd):

Active before:7.21 (2.73)

Active after: 10.20 (3.67)

MD=2.99; 95% CI 1.16 to 4.82; p=0.002

Control before: 10.31 (3.79)

Control after: 10.79 (4.53)

MD: 0.48 (95% CI

−3.38 to 4.34); p=0.796

Change difference: ns (p=0.17)

Length of stay (days)

Active before: 5.09 (11.1)

Active after: 5.38 (13.2)

Control before: 4.82 (13.5)

Control after: 4.93 (11.7)

Change difference: ns (p=0.371)

3. Teamwork

NOTECHS II (max score=98)

Active before: 71.62

Active after: 75.44

MD: 3.82; (95% CI 0.67 to 6.98)

Control before: 72.09

Control after: 70.09

MD: −1.19; 95% CI −5.62 to 3.24

Change difference: 4.54; difference 95% CI 0.06 to 9.02; p=0.047

Subteam analysis revealed that differences in mean NOTECHS scores were non-significant for surgeons

(p=0.806) and anaesthetists (p=0.067), while statistically significant for nurses (p=0.006; difference 1.78; 95% CI 0.40 to 3.16)

Author’s conclusion

Teamwork training was associated with

improved non-technical skills in theatre teams but also

with a rise in operative glitches.

Morgan, 2015a

Type of study: controlled

interrupted time series study

Setting: Two operating theatres in a single hospital system in the active group and 2 theatres in the control group at another hospital site.

Both within a university hospital trust.

Specialism: elective

orthopaedic surgery (lower limb orthopaedic surgery, such as knee arthroscopic procedures and knee and hip primary and revision arthroplasty)

Country: UK

Source of funding/conflict of interest: funded by the National Institute for Health Research (NIHR).

No competing interests

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline:

Pre-Intervention: 567 operations (30 observed)

Post-intervention:

679 operations (33 observed)

Pre-Control: 544 operations (17 observed)

Post-control: 421 operations (21 observed)

Important prognostic factors²:

Unknown

Groups comparable at baseline?

Unknown

SOPs and team training

SOP: aimed to improve standardisation and

visibility of work processes (focus on morning briefing and conduct of WHO Surgical Safety Checklist)

Team training: inform and

coach the theatre team members on the principles of effective teamwork.

1-day interactive

lecture-based training, using

aviation CRM training.

No intervention (of before intervention)

Length of follow-up:

3 months,

before and after a 3 month intervention period (for the

active group only).

Clinical outcome data were obtained

for all relevant patients for 6 months before and 6 months after the intervention period.

Loss-to-follow-up:

Intervention:

N (%)

Reasons (describe)

Control:

N (%)

Reasons (describe)

Incomplete outcome data:

Intervention:

N (%)

Reasons (describe)

Control:

N (%)

Reasons (describe)

1. Complications

Complication rate (any)

Pre-intervention: 81 (14%)

Post-intervention: 123 (18%)

Pre-control: 58 (11%)

Post-control: 64 (15%)

Change difference: p=0.33

Mean glitch rate per operation per hour (sd):

Pre-intervention: 6.84 (3.05)

Post-intervention:5.25 (3.17)

MD: -1.58; (95% CI −3.15 to

−0.02)

Pre-control: 7.67 (4.45)

Post-control: 6.52 (3.06)

MD: −1.16; (95%

CI −3.76 to 1.45)

Change difference:

−1.26; 95% CI −3.01 to 0.49; p=0.153

readmission within 90 days reoperation

Pre-intervention: 72 (13%)

Post-intervention:74 (11%)

Pre-control: 112 (20%)

Post-control: 84 (20%)

Change difference: p=0.29

2. Efficiency

length of hospital stay (days)

Pre-intervention: 3.6 (11)

Post-intervention: 3.0 (7.2)

Pre-control: 10.6 (19)

Post-control: 10.5 (20%)

Change difference:p=0.376

3. Teamwork and communication

NOTECH II (max score=96)

Pre-intervention:74.83

Post-intervention:79.27

MD: 4.44; 95% CI 1.23 to 7.65

Pre-control: 76

Post-control: 71.81

MD: 4.19; 95% CI −8.20 to −0.18

Change difference: 7.46; (95% CI 3.00 to 11.93), p=0.002;

Subteam analysis

revealed differences in mean NOTECHS scores

were non-significant for surgeons (p=0.067) and nurses (p=0.093) while statistically significant for

anaesthetists (p<0.001; difference 4.24; 95% CI 2.77 to 5.68)

Author’s conclusion

Combined training in teamwork and

system improvement causes marked

improvements in team behaviour and WHO

performance, but not technical performance or outcome. These findings are consistent with the synergistic hypothesis, but larger controlled studies with a strong implementation strategy are required to test potential outcome effects.

Neily, 2010

Type of study: retrospective health services study with a

contemporaneous control group was conducted.

Setting: Veterans Health Administration Surgical Quality Improvement Program,

108 facilities

Specialism: all non-cardiac surgeries

Country: USA

Source of funding/conflict of interest: supported with resources and the use of facilities at

the Veterans Health Administration National Center

for Patient Safety, Ann Arbor, Michigan, the Field Office

in White River Junction, Vermont, and the Michael

E. DeBakey VA Medical Center, Houston, Texas.

No conflict of interests

Inclusion criteria:

operations performed under general,

spinal, or epidural anesthesia are candidates

for entry into the database.

Surgical specialties

included general, orthopedics,

urology, vascular, neurosurgery, otolaryngology,

non–cardiac thoracic,

plastic, and other noncardiac subspecialties.

Exclusion criteria:

codes of procedures with

known low morbidity and mortality

rates or transurethral resections of the

prostate (TURPs), transurethral resections

of the bladder tumor (TURBTs)

and herniorraphies exceeding the limit

of five per week

N total at baseline:

Intervention: 74 facilities that had undergone training

Control: 34 facilities not yet trained

182 409 sampled procedures

Important prognostic factors²:

NA

Groups comparable at baseline?

Selection order was not random, based on readiness of facility.

Higher observed and risk-adjusted mortality rates at baseline

VHA Medical

Team Training program.

The program included briefings and debriefings in the operating room and included checklists as an integral part of this process. The training included 2 months of preparation, a 1-day conference, and 1 year of quarterly coaching interviews.

Not (yet) trained

Length of follow-up:

One year after intervention

Loss-to-follow-up:

Intervention:

N (%)

Reasons (describe)

Control:

N (%)

Reasons (describe)

Incomplete outcome data:

Intervention:

N (%)

Reasons (describe)

Control:

N (%)

Reasons (describe)

1. Complications

Annual mortality rate (30 days, in or out the hospital)

Intervention: -18%

RR: 0.82; (95% CI, 0.76-0.91); P=.01

Control: -7%

RR, 0.93; (95% CI, 0.80-1.06) P=.59

Risk-adjusted mortality rate per year(sd):

Intervention: 17 (6) per 1000 procedures per year

Control: 15 (6) per

1000 procedures per year

Propensity matching: RR,1.49; 95%

CI, 1.10-2.07; P=.01, in favour of intervention

dose-response relationship: for every quarter of the training program, a reduction of 0.5 deaths per 1000 procedures occurred (95%

CI, 0.2-1.0; P=.001).

Author’s conclusion

Participation in the VHA Medical Team Training program was associated

with lower surgical mortality.

Rebuck, 2011

Type of study: Before-after study

Setting: One hospital, With the collaboration of the departments of urology, anesthesiology,

nursing, and the OR support staff

Specialism: Robot-assisted laparoscopic radical prostatectomy for prostate cancer

Country: USA

Source of funding/conflict of interest:

Funding not mentioned.

One author is a consultant/advisor for Intuitive Surgical.

The other authors have no conflicts of interest to declare.

Inclusion criteria:

Before: August 2008–January 2009

After: April–November

2009

Exclusion criteria:

NA

N total at baseline:

Before modifications:100

After modifications: 100

Important prognostic factors²:

Mean age (range)

Before: 61.1 (47–76)

After: 59.4 (41–77)

Mean BMI (range):

Before: 27.6 (18.3–50.2)

After: 27.6 (19.5–39.4)

The patient groups were similar in age, BMI, PSA level, Gleason score,

stage, and prostate size. They were also similar across other factors related to surgical time and costs.

Four modifications in OR processes were implemented: Trainee adherence to time oriented surgical goals; use of a dedicated anesthesia team; simultaneous processing by nursing and urology house staff during case turnover; and identification and elimination of unused disposable instruments.

Before modifications

Length of follow-up:

The 100 cases

before the modifications took place over a 6-month period

(August 2008–January 2009) and the 100 cases after the

modifications took place over an 8-month period (April–November

2009).

Loss-to-follow-up:

NA

2. Efficiency

Mean surgical time, min (range)

Before: 256.2 (140–386)

After: 238.8 (116–328)

Difference (% change): -7.4 ( - 6.8%) , p=0.04

Mean anesthetic time, min (range)

Before: 23.7 (7–92)

After: 19.2 (8–71)

Difference (% change): -4.5 ( - 19.1), p=0.006

Mean turnover time, min (range)

Before: 43.0 (21–111)

After: 30.9 (17–53)

Difference (% change): - 12.1 ( - 28.1), p=0.005

4. Costs

Total costs

Before: 11806 (3265–28,704)

After: 29 ( + 4.2)

Total (range) 11806 (3265–28,704)

Difference (% change): -2548 ( - 21.7)*

*payroll costs, surgical supplies costs, operating room costs were all decreased. Anesthesia cost did not change (+ 29 ( + 4.2)

Author’s conclusion

Using simple modifications, it is possible that RALRP efficiency can be improved by decreasing its associated times and costs. These modifications were implemented in an academic setting but may be used in

any institution. These modifications represent an initial attempt to improve RALRP cost-competitiveness with other treatment modalities.

Robertson, 2015

Type of study: A Controlled Before-After Study

Setting: specialist elective orthopaedic and reconstructive surgery hospital,

with 106 beds and six operating theatres

Specialism: a plastic surgery team received the intervention (elective upper limb surgery, osteomyelitis and sarcoma surgery) and an Orthopaedic theatre team acted as a

Control (primary and revision

hip and knee arthroplasty and arthroscopic knee surgery)

Country: UK

Source of funding/conflict of interest: funded by the National Institute for Health Research

(NIHR)

No conflicts of interests.

Inclusion criteria:

NA

Exclusion criteria:

NA

N total at baseline:

Before active group: 151 (26 observed)

After active group: 136 (25 observed)

Before control: 418 (21 observed)

After control: 355 (24 observed)

Important prognostic factors²:

Groups comparable at baseline?

Different setting (difference in operating time), however, seniority and skill-mix of the

nursing, surgical and anaesthetic staff were similar in active and control groups, and the facilities

for pre and post-operative care and patient recovery after anaesthesia were identical

Combining teamwork training (one morning and two evening sessions (20 staff attended one session each + 5 days in-theatre coaching spread over 6 weeks, focusing on WHO surgical safety checklist process, and other non-technical skills.

AND lean process improvement (one half day training session to core members of the frontline healthcare team (11 staff attended) + frequent on-site coaching and support was provided to frontline staff project groups by study team members over the

course of the intervention period)

Following the training sessions, the frontline theatre staff were encouraged to develop their

own agenda for change, and decided on a number of topic areas (briefing, WHO checklist use, debriefing, equipment procedure, prep room organisation, list design, awareness of sterile services function).

Not all of these projects

were successfully completed. Project groups analysed their problem, collected data to measure it and developed solutions

under the supervision of the experts who provided training. New systems of working underwent iterative PDCA cycles of rapid testing until apparent stability was reached.

No intervention in control group (or before intervention)

Length of follow-up:

3 month intervention with 3 months data collection period before and after it.

Complication rate, readmission

rate and length of hospital stay data was recorded 6 months before and 6 months after the intervention.

Loss-to-follow-up: NA

1. Clinical outcomes

Complication rate (%)

Before active: 14 (9%)

After active: 9 (7%)

Before control: 77 (18%)

After control: 98 (28%)

Change difference: p=0.08

Readmission rate (%)

Before active: 3 (2%)

After active: 12 (9%)

Before control: 3 (1%)

After control: 7 (2%)

Change difference: p=0.33

2. Efficiency

Mean operating time Active: 2 hr 17 mins

Control: 1 hr 36 mins

No significant change in the operating time after intervention in either group.

Glitch rate per hour (sd)

Before active: 10.48 (6.68)

After active: 4.38 (2.50)

MD = -6.10 (95% CI -9.29 to -2.92)

Before control: 9.79 (4.12)

After control: 13.20 (sd = 5.37)

MD: 4.87 (95% CI 0.70 to 6.12)

Change difference: p<0.001

Mean length of hospital stay in days (sd)

Before active: 2.5 (6.3)

After active: 1.6 (4.0)

Before control: 5.2 (7.2)

After control: 6.0 (7.9)

Change difference: p=0.09

3. Team work and communications

NOTECHS II

Before active: 69.81

After active: 75.56

MD: 5.75 (95% CI 0.68

to 10.82)

Before control: 72.88

After control: 72.54

MD: -0.36 (95% CI -4.28 to 3.59)

Change difference: p = 0.058

Between-group differences in mean Oxford NOTECHS II scores were non-significant for surgeons (p = 0.101) and anaesthetists (p = 0.876) whilst statistically significant for nurses (difference 2.22; 95% CI 0.22 to 4.24; p = 0.016).

Author’s conclusion:

Combining teamwork training and systems improvement enhanced both technical and nontechnical operating team process measures, and were associated with a trend to better safety outcome measures in a controlled study comparison. We suggest that approaches

which address both system and culture dimensions of safety may prove valuable in reducing risks to patients.

Study reference

(first author, publication year)

Describe method of randomisation¹

Bias due to inadequate concealment of allocation?²

(unlikely/likely/unclear)

Bias due to inadequate blinding of participants to treatment allocation?³

(unlikely/likely/unclear)

Bias due to inadequate blinding of care providers to treatment allocation?³

(unlikely/likely/unclear)

Bias due to inadequate blinding of outcome assessors to treatment allocation?³

(unlikely/likely/unclear)

Bias due to selective outcome reporting on basis of the results?⁴

(unlikely/likely/unclear)

Bias due to loss to follow-up?⁵

(unlikely/likely/unclear)

Bias due to violation of

intention to treat analysis?⁶

(unlikely/likely/unclear)

Duclos, 2016

Participating

hospitals were randomized into two cluster arms (on hospital level). To ensure comparability

between arms, randomization was balanced across

geographical areas. Additionally, hospitals were allocated

according to major adverse events collected during the

preimplementation period in order to guarantee similar

primary outcomes between arms at baseline.

Every month in each participating hospital, the first 50 adults

admitted for surgical procedures were eligible for inclusion.

Unlikely

Unclear

Likely

Likely

Unlikely

Unlikely

Unlikely

Study reference

(first author, year of publication)

Bias due to a non-representative or ill-defined sample of patients?¹

Bias due to insufficiently long, or incomplete follow-up, or differences in follow-up between treatment groups?²

Bias due to ill-defined or inadequately measured outcome ?³

Bias due to inadequate adjustment for all important prognostic factors?⁴

Attarian, 2003

Unclear

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

Carter-Brooks, 2018

Unlikely

Possible selection bias in dedicated team group, however they used a single-surgeon database

Unlikely

However, large different in number of observed patients between groups

Unlikely

Unlikely (only for operating time multiregression model), for other outcomes no multivariate regression model was made, however, few cases so adjustment would be not relevant.

No adjustment for other factors that relate to time efficiency e.g. operating room staff turnover or hospital-driven quality control

Measures.

Lim, 2013

Unclear

(uncontrolled before-after study)

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

McCulloch, 2017

Unlikely

(minimal contamination)

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

McCulloch, 2009

Unclear

(uncontrolled before-after study)

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

Forse, 2011

Unclear

(uncontrolled before-after study)

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Teamwork outcomes zijn onduidelijk

Likely

Duclos, 2016

Unlikely

(Cluster RCT)

Unlikely

Unlikely

Unlikely

(cluster RCT)

Morgan, 2015b

Unlikely

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

Morgan, 2015a

Unclear

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

Neily, 2010

Likely

Unlikely

Unlikely

Unlikely (propensity matching)

Rebuck, 2011

Unlikely

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely

Robertson, 2015

Unlikely

Unlikely

Unlikely

Likely for observed outcome measures (not blinded)

Likely