Evaluation and Impact of Workflow Interruptions During Robot-assisted Surgery

Allers, Jenna C.; Hussein, Ahmed A.; Ahmad, Nabeeha; Cavuoto, Lora; Wing, Joseph; Hayes, Robin M.; Hinata, Nobuyuki; Bisantz, Ann M.

doi:10.1016/j.urology.2016.02.040

Cited by 49 publications

(76 citation statements)

References 12 publications

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“…no nephrectomies involved residents, while all sacrocolpopexies involved residents). Although the sample size is large in comparison to similar observational studies [23,24], and we believe that we controlled for procedure type as much as possible in our analysis and statistics, our conclusions were nevertheless limited. Follow-up studies will seek a more structured selection of cases in order to decrease this bias.…”

Section: Discussionmentioning

confidence: 95%

Barriers to efficiency in robotic surgery: the resident effect

Jain

Fry

Hess

et al. 2016

Journal of Surgical Research

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Background Robotic surgery offers advantages over conventional operative approaches, but may also be associated with higher costs and additional risks. Analyzing surgical flow disruptions (FDs), defined as “deviations from the natural progression of an operation,” can help target training techniques and identify opportunities for improvement. Materials and methods Thirty-two Robotic Surgery operations were observed over a six-week period at one 900-bed surgical center. FDs were recorded in detail and classified into one of 11 different categories. Procedure type, robot model, and resident involvement were also recorded. Linear regression analyses were used to evaluate the effects of these parameters on FDs and operative duration. Results Twenty-one prostatectomies, 8 sacrocolpopexies, and 3 nephrectomies were observed. The mean number of FDs was 48.2 (95% CI 38.6–54.8 FDs), and mean operative duration was 163 minutes (95% CI 148–179 minutes). Each FD added 2.4 minutes (p=0.025) to a case’s total operative duration. The number and rate of FDs were significantly affected by resident involvement (p=0.008 and p=0.006, respectively). Resident cases demonstrated mostly Training, Equipment, and Robot Switch FDs, whereas non-resident cases demonstrated mostly Equipment, Instrument Changes, and External Factors FDs. Conclusions Though the FDs encountered in resident training are more frequent, they may not significantly increase operative duration. Other FDs, such as Equipment or External Factors, may be more impactful. Limiting these specific FDs should be the focus of performance improvement efforts.

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Section: Discussionmentioning

confidence: 95%

Barriers to efficiency in robotic surgery: the resident effect

Jain

Fry

Hess

et al. 2016

Journal of Surgical Research

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“…Despite a relatively swift uptake of robotic surgery for a wide variety of procedures, and some recognised adoption and performance challenges (Lucas, Pattison, and Sundaram 2012), until recently few studies had explored the teamwork, environmental and organisational demands of this new technology (Allers et al 2016; Nyssen and Blavier 2015; Randell et al 2016; Tiferes et al 2016). Indeed, though human factors and ergonomics are growing considerations for medical device designers and regulators, the variability of use cases, environments, organisations, users, techniques and other devices make the wider systems implications of new technologies difficult to predict or understand holistically.…”

Section: Introductionmentioning

confidence: 99%

“…As the surgeon works at a console away from the operating table, this can degrade the shared understanding amongst the team members of the surgical progress and requirements that demands new approaches to teamwork, communication and situation awareness (Randell et al 2016). Even the required size and layout of the room is altered by the size of the robot, associated control consoles and the data and power cables necessary for function (Ahmad et al 2016; Allers et al 2016). This means that a limited number of ORs in any surgical suite may be suitable for robotic surgery.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing barriers to safety and efficiency in robotic surgery

et al. 2017

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Recent studies exploring the effects of surgical robots on teamwork are revealing challenges not reflected in clinical studies. This study is a sub analysis of observational data collected from 89 procedures utilising the da Vinci systems. Previous analyses had demonstrated interactions between flow disruptions and contextual factors. This study sought a more granular analysis to provide better insight for improvement. Raters sub-classified disruptions, based upon the original notes, grouped according to four operative phases (pre-robot; docking; surgeon on console; undocking; and finish). The need for repeated utterances; additional supplies retrieval; fogging or matter on the endoscope and procedure-specific training were particularly disruptive. Variations across phases reflect differing demands across the operative course. Combined qualitative and quantitative observational methodologies can identify otherwise undocumented sources of process variation and potential failure. Future observational frameworks should attempt to merge human reliability analysis, a priori modelling, and post hoc analyses of observational data. Practioner Summary Robotic surgery introduces new challenges into the operating room. Direct observation was used to classify and identify flow disruptions in order to diagnose problems in need of improvement. This technique complements other error prediction and system diagnostic methods which may not account for the complexity and transparency of health care.

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“…1-4 To reduce the rate of preventable adverse events and enhance patient safety, we present what is, to our knowledge, the first clinical use of the HUB, 5 a computer-assisted system designed to support intraoperative team performance.…”

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confidence: 99%

Computer-Assisted Process Modeling to Enhance Intraoperative Safety in Cardiac Surgery

et al. 2016

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Although we tested the HUB in cardiac surgery, HUB algorithms can be developed and applied across all surgical specialties. Unique algorithms can also be tailored for complex procedures involving multiple surgical teams, where communication is critical and susceptible to error. Each team member may check in and check out of the procedure at any time, provided their profile is uploaded to the system preoperatively. Although no final product cost can be estimated at this time, use of the HUB across multiple surgical specialties may reduce the additional cost per case.Ultimately, surgical safety interventions endeavor to reduce morbidity and mortality. The logical next step is to apply the HUB to a larger series of cardiac surgical procedures to determine whether the HUB achieves this goal.

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Evaluation and Impact of Workflow Interruptions During Robot-assisted Surgery

Cited by 49 publications

References 12 publications

Barriers to efficiency in robotic surgery: the resident effect

Barriers to efficiency in robotic surgery: the resident effect

Diagnosing barriers to safety and efficiency in robotic surgery

Computer-Assisted Process Modeling to Enhance Intraoperative Safety in Cardiac Surgery

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