Undeniably robotic-assisted surgery (RAS) has become very popular in recent decades. So far, over 7.2 million RAS procedures have been performed by 2019 since the US Food and Drug Association (FDA) approval in 2000 [1]. In all the commercially available RAS systems today, the surgeon is physically disconnected from the patient and the rest of the surgical team, which is very different from the traditional operating theatre (OR) setup, and this has introduced several challenges to how surgeons and their teams’ function, especially to communication, teamwork and situational awareness. On certain platforms, the robotic surgeon may be working several meters away from the patient, which potentially places considerable limitations on their interactions with OR team. Moreover, robotic system components have a considerable footprint and can restrict movement and obstruct the direct line of sight between team members [2]. The immersive environment of the RAS inadvertently affects the surgeon’s situational awareness, which could negatively impact the surgeon’s decision-making [3] and preclude effective communication between operating staff.

Ever since a report by the Institute of Medicine in 1999 highlighting human errors and their consequences in healthcare, Non-Technical Skills (NTS) have been identified as an essential pillar of patient safety [4]. Studies suggest that up to 60% of surgical patients may be involved in adverse events and breakdown in communication was the cause of 43% of errors during surgery [5]. Flin et al. defined NTS as ‘the cognitive, social and personal resource skills that complement technical skills, and contribute to safe and efficient task performance [6]. While there has been a great emphasis on training, assessment and credentialling of surgeons’ technical competencies in RAS, Non-Technical Skills (NTS) have received less emphasis [7]. As with the introduction of any new medical technology, it is crucial to understand NTS specific to RAS and the state of NTS training for RAS teams. Particular emphasis should focus on preventing errors and response to emergency situations including device malfunction, major haemorrhage or air embolism which may require rapid conversion to open surgery.

In 2019, Kwong et al. reported a systematic review to understand NTS in RAS and how it could be assessed [8]. This review however was limited to robotic urological surgery and highlighted the paucity of tools available for assessing NTS in RAS, and most of them were not specific to robotics. Another older review identified key NTS and their assessment in minimally invasive surgery (MIS) teams but did not include RAS teams [9]. A recently published review by Cha et al. identified objective metrics for measurement in the surgical environment, including RAS, but focusing only on the physiological matrix without assessing NTS [10].

This systematic review aimed to update the evidence on the role of NTS in robotic surgery with a specific focus on evaluating assessment tools and their utilisation in training and surgical education in robotic surgery.

Methods

A systematic literature review was performed as per the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) Guidelines [11]. The study has been registered with Research Registry, identification number: review registry 1654.

Eligibility criteria

The PICOS (Population, Intervention, Comparator, Outcomes and Setting) framework was used to create a well-formulated research question to guide the systematic review (Table 1).

Table 1 PICOS (population, intervention, comparator, outcomes and setting) statement
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Studies written in the English language involving the identification, assessment or training of NTS skills in individuals and teams during live or simulated RAS procedures were included in the review. Study types included cross-sectional, cohort, qualitative studies, non-randomised and randomised control trials.

Minimally invasive surgery other than RAS, robotic surgery without general anaesthesia (as they would not involve the entire team) and studies solely on the evaluation of technical skills, were excluded. Articles without empirical evidence, abstracts without full-text articles, duplicate publications and articles without an English translation were also excluded from the review.

A search of the PubMed, PsychINFO, Medline and Embase databases was conducted in December 2022. Studies up to 1985 were included when a robot was first used in a surgical procedure [12]. Key concepts used in the search were ‘Non-Technical Skills’, ‘Robotic Surgery’, ‘Subjective Assessment’, ‘Objective Assessment’, ‘Robotic Surgery Team’ and ‘Outcome’. Table 2 shows the search terms and strategy used.

Table 2 Search strategy and MeSH (medical subject heading search terms)
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Screening

Two independent reviewers searched the databases, selected titles, reviewed abstracts and short-listed studies which met the inclusion criteria. Any disagreements during study selection were resolved by consensus between the two reviewers.

Full-text review of all the studies which meet met the inclusion criteria were reviewed independently by both reviewers and data extracted. The following data fields were extracted:

  1. 1.

    Study characteristics—Authors, year, single or multi-centre, registration/ID, country, name of article, study design, meets the inclusion criteria (yes/no), study setting (dry simulation lab, wet simulation lab, simulated OR, intra-operative), the total number of participants, participant level of experience (Novice, Intermediate, Expert, Unspecified), study funding sources and possible conflicts of interest of the authors.

  2. 2.

    Evaluation and outcome characteristics—Name of the assessment tool, type (subjective or objective), NTS domain or construct tested, evaluator type (Self-rated, Novice, Expert, Crowd-sourced, Not applicable/ other), the content of the intervention, duration, intensity and timing, effects of NTS training/ assessment on staff’s knowledge, attitude, behaviour and patient outcomes.

Data analysis and quality of literature and validity evidence

  1. 1.

    Selected articles were judged on their level of evidence using the OCEBM (Modified Oxford Centre for Evidence-Based Medicine) Working Group Level of Evidence [13].

  2. 2.

    MMERSQI (Modified Medical Education Research Study Quality Instrument) was used to appraise the methodological quality of the studies. Studies have scored a minimum of 23.5 and a maximum of 100 based on 12 outcomes based on the domains of design, sampling, setting, type of data, the validity of assessment, data analysis and outcomes [14].

  3. 3.

    Validity of the judgements made by different NTS assessment tools was evaluated using Messick’s validity framework [15]. Validity evidence was categorised into content, response process, internal consistency, relationship to other variables and consequences [15].

Data management: Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia, a. Available at www.covidence.org was used for deduplication, screening, full-text review, and data extraction. The data synthesised here was then exported to Excel files.

Results

The search databases yielded 27,824 studies, and seven more were added manually. 17 studies met the inclusion criteria and were fully analysed (PRISMA diagram—Fig. 1).

Fig. 1
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PRISMA flowchart (preferred reporting items for systematic review and meta-analysis)

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Twelve were cohort studies; two were cross-sectional studies (surveys), one was a qualitative study (focussed interviews), one was a randomised control trial (RCT), and another involved multiple methods. Eight were performed in a live operating room (OR), seven in a simulated OR and one was performed in a simulation lab using a dry model. Seven of the eight studies performed in the live OR were based on urological procedures, one was performed on gynaecological procedures and in two studies observations included general and colorectal surgeries. In four studies, participants were all experts, two involved only novices, six involved participants with different levels of experience (novice, intermediate and expert), and the experience level was unspecified in five studies (Table 3).

Table 3 Summary of Included Studies on Non Technical Skills in Robotic-Assisted Surgery
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Domains of non-technical skills

Cognitive load

Four studies reported on the use of NASA-TLX (National Aeronautics and Space Administration-Task Load Index) to assess cognitive workload across multiple professions [16,17,18,19,3], therefore, representing potential novel challenges or resolutions to effective NTS. RAS is a highly complex environment; hence it is essential to evaluate the NTS of the entire multi-professional team comprehensively [29].

Limitations of this systematic review include the possibility of missing some unpublished literature and 31 articles were removed as the full text was unavailable. A search of the “grey” literature was not performed due to the large number of titles for screening and time constraints. As a result, publication bias could not be convincingly excluded. Further examination into the implementation of sensor-based measurements utilising distinct physiological parameters with increasingly miniaturised measurement devices will provide a more objective and immediate assessment of NTS. Progression in the design of systems and instruments will facilitate communication between the surgeon and the rest of the team, promoting the formation of a shared mental model during the procedure. The development of telesurgery necessitates the formation of a global, high-fidelity, emergency robotic undocking curriculum, akin to the ATLS (Advanced Trauma Life Support) [34]. Investigating the most advantageous theatre design and set-up, which can diminish crowding and enhance productivity (Refer Fig. 2—Key takeaway).

Fig. 2
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Key takeaways

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Conclusion

This systematic review has highlighted multiple non-technical skills tools, with three main ones, most of which are under evaluated. Whilst promising, increased awareness and widespread use across multiple specialities is lacking. Further evaluative research is required to report on incorporating non-technical skills training and assessment in robotic surgery curricula, to demonstrate the potential benefits and improve patient safety in robotic surgery.