Die rasche Weiterentwicklung intelligenter Robotersysteme verändert die Arbeitsbedingungen in der Zusammenarbeit, insbesondere im Gesundheitswesen. Dieser Artikel untersucht die Integration des da Vinci-Robotersystems in Operationsteams und enthüllt sowohl die Verbesserungen als auch die Hürden, auf die man stößt. Das da Vinci-System, das für minimal-invasive Operationen eingesetzt wird, bietet bedeutende physische, visuelle und koordinative Verbesserungen, wie erhöhte Freiheitsgrade, verbessertes 3D-Sehen und weniger Koordinationsbedarf während des Eingriffs. Die Einführung dieser Technologie bringt jedoch auch erhebliche Hindernisse mit sich, darunter das Fehlen von haptischem Feedback, Herausforderungen in der Teamkommunikation und die zunehmende körperliche und geistige Distanz zwischen den Teammitgliedern. Der Artikel geht auf die Strategien ein, die chirurgische Teams anwenden, um diese Hindernisse zu überwinden, und konzentriert sich auf die Verwendung von informativen und visuellen Hinweisen, um das situative Bewusstsein und den Zusammenhalt im Team aufrechtzuerhalten. Durch die Untersuchung des dynamischen Zusammenspiels zwischen menschlichen und robotischen Elementen bietet die Studie einen umfassenden Überblick über die organisatorischen und verfahrenstechnischen Anpassungen, die für eine effektive Zusammenarbeit zwischen Mensch und Roboter in kritischen medizinischen Umgebungen erforderlich sind. Die Ergebnisse bieten wertvolle Einblicke in die Zukunft chirurgischer Praxen und die umfassenderen Auswirkungen auf die Integration intelligenter Robotersysteme in Umgebungen mit hohem Einsatz.
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Abstract
Smart robotic systems continue to make their way from industrial contexts to social applications. That shift necessitates further insights into interactions between human teams/team members and smart robots. These interactions have different patterns than interactions in strictly human teams. This study examines surgical teams and their interactions with the endoscopic surgical system (ESS) ‘da Vinci’ as a concrete implementation case. Its focus is the growing distance between team members upon introduction of the ESS robot. We follow a qualitative approach, based on semi-structured expert interviews with nine physicians of diverse fields of expertise and levels of experience with the ESS robot. Our findings show that surgeries with da Vinci bring about certain improvements as well as obstacles. Those can be grouped into physical, visual and coordinative dimensions. The main obstacles seem to be increased physical and mental distance between the ‘concertmaster role’ (i.e., the surgeon) and ‘ensemble roles’ (i.e., the rest of the surgery team). Surgery teams overcome these by applying visual and informational cues. We strengthen existing literature concerning the established physical distance and add the notion of mental distance in ESS-assisted surgeries. We suggest that surgery teams overcome physical and mental distance through visual and informational cues. Furthermore, we find that certain roles within a team get enriched, trimmed, or redesigned. Developers can utilize our findings to improve ESS robots. Medical and general management staff can use our findings for the improvement of team composition and governance, as well as process optimization and coordination, especially in human-robot teams.
Hinweise
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Abkürzungen
ESS
Endoscopic Surgical System
STS
Socio-technical System(s)
P01-P09
Anonymized identification numbers of the respective interviewees (P = physician)
1 Introduction
Smart robotic systems are multifunctional systems that help workers complete tasks by perceiving and manipulating their environments via sensors and actuators (Hunt 1985; Robot Institute of America, 1982, as cited by Hamilton & Hancock 1986). Their importance is expected to increase rapidly, with the market size of smart humanoid robots alone being projected to grow from 1.48 billion US-$ (2021) to 34.96 billion US-$ by 2030 (Gordon 2024).
Smart robots are deeply embedded in collaborative work settings—e.g., in factories—, where they are used in many different ways to increase (individual and organizational) efficiency and cost savings in production (Bednar & Welch 2020; Denagama Vitharanage et al. 2020; Realyvásquez-Vargas et al. 2019). In professional work settings, the organization of work is important for delivering high-quality results to customers. Such work settings are fundamentally changed when smart robotic systems are introduced to augment human work and especially when they operate with their own agency (Aleksander 2017; Curchod et al. 2020; Robert & You 2015). Since collaborative robots (‘cobots’) are gaining momentum in management literature (Matas Hidalgo 2022; Sowa et al. 2021; Tsai et al. 2022), we are striving to add to the literature of (i) human–robot collaboration and (ii) ‘human–human’ team coordination and interaction, by turning to a medical application to better understand these changes. Medical professionals, after all, are well documented to be among the first to implement technological novelties (‘early movers’) and to talk openly about it (Holden 2012; Hsieh 2015; Shinners et al. 2020).
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Healthcare has been impacted by smart robotic systems inmany different ways (Datteri 2013). Important research aspects at the intersection of smart robotics and healthcare have been, for example, patient-side benefits and risks (A. F. Chen et al. 2018; Müller et al. 2019; F. Yu et al. 2018), robotic assistance systems for repetitive tasks in laboratories, pharmacies etc. (Kirschling et al. 2009; Liang et al. 2019; Matas Hidalgo 2022; Summerfield et al. 2011), or psychosocial assistance in patient care (Celiktutan et al. 2018; N. L. Robinson et al. 2019).
However, the focus of this article lies in smart robotic systems and their impact on internal healthcare work practices of nurses and surgeons (Pelikan et al. 2018). In surgery rooms, analogous to other professional work settings, the organization of work is important for delivering high-quality medical services to patients (Abrishami et al. 2014). Many—especially private—healthcare companies constantly seek to improve their business processes, e.g., via robotic process automation (Ratia et al. 2018). However, the structural changes that need to be introduced for the processes to work properly are sometimes not taken into account by the businesses (Mutlu & Forlizzi 2008).
Thus, we conduct an exploratory analysis of surgical teams using a smart endoscopic surgery system (ESS)—the da Vinci robot (Intuitive Surgical, Inc., 2023)—in order to better understand improvements and obstacles that the ESS brings with special regards to work processes. Previous research has shown that one important aspect of the changing work environment with the da Vinci ESS is the increased distance in the work team. Smart robotic systems can enable remote operation procedures that detach the physicians operating the robot from the rest of the team (Sergeeva et al. 2020). This has significant effects on physical and organizational distributions of the team (Pelikan et al. 2018). However, it remains unclear how surgical teams overcome this distance when using smart robotic systems in surgical procedures.
In order to better understand improvements and obstacles that the ESS brings, as well as how teams overcome the growing distance, we answer the following research questions by conducting and analyzing interviews with medical professionals that have been working with the ESS robot in their surgical contexts:
1.
Which improvements and obstacles related to the processes within robot-assisted surgeries follow the implementation of an ESS robot?
2.
How do established healthcare teams providing robot-assisted surgeries overcome the distance that follows from the implementation of an ESS robot?
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We group the process-related improvements and obstacles into three major categories: (i) physical, (ii) visual, and (iii) coordinative. As a result, we find growing distance within teams to be the major obstacle and examine how surgical teams make use of the ESS technology to counteract this effect. This has implications for the design of organizational roles and offers the use of informational and visual cues as resolutions for overcoming physical and mental distance. We add to the literature stream researching the management and organization of teams upon implementation of an embodied robot, which leads to the aforementioned distance within the team, and find that roles and their relative importance to the tasks during the central work processes can change vastly. Our findings should lead to an overhaul of these implementation processes, keeping in mind the possible organizational effects of ‘Digital Taylorism’1 and how these should be addressed ethically.
The rest of the paper is organized into five sections. In the following section (chapter 2), a theoretical background is provided: first, robots will be described from a socio-technical perspective (2.1), before detailing the specific artefact of interest for this article, the da Vinci ESS robot (2.2), and the impact it can have on teamwork, especially regarding our central aspect of distance (2.3). In the third section, the research method is presented. Chapter four reports on the analysis of the conducted interviews and the subsequent findings. In the fifth section, we discuss these findings, their implications for management research and practice, as well as the limitations of our study. Lastly, a brief conclusion is provided in the sixth section.
2 Theoretical background
For this paper, we adopt the concept of a robot in line with the Robot Institute of America as “[a] reprogrammable, multifunctional manipulator designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks” (Robot Institute of America, 1982, as cited by Hamilton & Hancock 1986). If not indicated otherwise, whenever we use the term ‘robots’, we reference physically embodied robots matching the definition above (hence excluding, e.g., chatbots).
The following subchapter serves as an outline of the theoretical viewpoint from which AI and smart robots are being perceived in this article, namely the socio-technical systems (STS) perspective.
2.1 A socio-technical perspective on smart robots
Generally speaking, humans and robots complement each other rather well, as Moravec points out with his renowned paradox: what appears to be simple for humans (e.g. movement) is difficult to compute in robots and what appears to be difficult for humans (e.g. reasoning) can easily be computed in robots (Moravec 1988). This complementarity indicates good circumstances for collaboration between humans and robots in the workplace.
A plethora of studies has confirmed the transformative power of robots in the workplace by researching, e.g., employees’ attitudes, trust, perceived safety, and team identification, as mitigated by aspects such as the robot’s appearance, the task complexity, and the requirements of self-disclosure towards the robot (J. Kim et al. 2015; Stock et al. 2019).
Not only do robots transform the workplace itself, but also its dynamics (Bednar & Welch 2020; A. Kim et al. 2012; Olaronke et al. 2017). They keep moving from industrial applications into social spaces, which leads to the question how these apparently vastly different actors—humans and smart robots—can be harmonized in professional surroundings. Bednar and Welch propose a modern approach to the STS perspective as a solution for this issue by seeking to create “excellen[t] and sustainable systems” (2020). They also clarify that terms such as ‘smartness’ and ‘smart work’ put a bigger emphasis on aspects including collaboration, employee autonomy, talent management, innovation, and flexibility, while putting a smaller emphasis on the physical space in work processes (Bednar & Welch 2020). This implies that work design changes immensely by adding smart machines.
The STS paradigm was developed after World War II to criticize that technology was predominantly viewed as an organizational externality. It established the social subsystem (people, social structures and psychological structures) and the technological subsystem (techniques, technology, tasks) as equally valuable, interdependent parts of the same work system (L. Chen & Nath 2008). From an STS perspective, thus, smart robots are prime examples to be investigated because the transition towards a workplace with robots is a situation that involves changes in both the technical and the social subsystem (Pekkarinen et al. 2020). On the one hand, the technical subsystem is relevant to research due to its novelty and the resulting uncertainty in the usage upon implementation, whose effects on staff and performance are relevant measures (O'Connor et al. 1990). On the other hand, the social subsystem should be examined to understand howthe employees react to and interact with an embodied information system, and how team interactions change, as opposed to collaborating with a ‘traditional’, non-embodied information systems (Bednar & Welch 2020), also Fig. 1.
Fig. 1
Simplified STS model (own depiction, based on Bednar and Welch, 2020)
Translated to the empirical application case of this article, the social subsystem (i.e., the surgery team) and its organization change because of the alterations in the technical subsystem (i.e., the introduction of the ESS robot), since the two subsystems are interdependent.
Robots have certain capacities, while they lack others (Brynjolfsson & McAfee 2014). Among the advantages that robots bring is, for example, the improved autonomy of workers, allowing humans to focus on, e.g., decision-making and responsibility-taking (Smids et al. 2020). Other positive aspects of robotics are projected cost savings, increased efficiency, improved outcomes, compensating understaffing in certain domains, and satisfying the need to stay an innovative and attractive employer (Decker et al. 2017; Saunders & Rutkowski 2019). Saunders and Rutkowski especially highlight that tasks, which are considered too “dangerous, dirty, and dull” for humans, are suitable for robots (2019).
Negative aspects on the side of robots, however, are the lack of flexibility due to environmental and task-specific constraints, e.g., navigating complex, unknown environments (Brynjolfsson & McAfee 2014). Other obstacles for robots are the difficult implementation in work spaces with low frequency of repetitive work (Mettler et al. 2017), and the lack of accuracy in sensing and moving for some systems (Cohen & Peleg 2008). However, the lack of mobility and adaptation to complex, unknown surroundings is not relevant for the case we are examining, as the da Vinci ESS robot is fixed to one position. Further, experiences with the ESS show that lack of repetition and accuracy are not a problem either (Abrishami et al. 2014).
To better understand the application of the embodied ESS robot da Vinci in the surgery context, the next section introduces certain aspects of the robotic device in question.
2.2 Smart robotics in healthcare: the da Vinci ESS robot
The da Vinci ESS robot is a “world-class” surgical system “for hospitals committed to increasing the scale and efficiency of minimally invasive surgery”, according to the website of its production company Intuitive Surgical.2 The adoption of the da Vinci ESS promises the prospect of “lower estimated blood loss, fewer complications and lower length of hospital stay when compared with the open approach and lower or similar rates of conversion, when compared to the laparoscopic3 approach” (Intuitive Surgical, Inc., 2023).
The da Vinci robot is used for minimally invasive surgeries in different procedures, in which it performs medical tasks with its four instrument arms and jointed instruments. The da Vinci system consists of the console unit, from which the physician controls the performance of the system, the patient cart with the four arms and attachable instruments, as well as the vision cart, which allows the stand-by surgeon and other team members to follow the procedure, albeit it being a key-hole operation. ESS-enabled surgery is hence performed remotely, i.e. the console and the patient cart are physically separated (Intuitive Surgical, Inc., 2023). The team composition differs for each respective surgery, but usually, there are a stand-by surgeon, a scrub nurse, and an anesthesiologist or anesthesia nurse involved. Figure 2 shows an overview of the spatial distribution during an ESS-enabled surgery, as compared to a ‘traditional’ surgery.
Fig. 2
Schematic overview of the operating room in (a) traditional surgery contexts (i.e., without da Vinci) and (b) ESS-enabled surgery contexts (own depiction). Abbreviations used in this figure: AC=anesthesia cart, SC=surgeon console, VC=vision cart, ESS=ESS robot/da Vinci. Numbers used in this figure: 1=console surgeon, 2=trainee console surgeon, 3=scrub nurse, 4=stand-by surgeon/assistant surgeon, 5=anesthesiologist/anesthesia nurse. Light grey coloring symbolizes optional roles
The da Vinci ESS robot is not fully autonomous, because it is used in intraoperative settings, in which the systems are usually user-centric (the user being the surgeon, in this case). Fully autonomous systems are being used, however, in postoperative scenarios, as one of the interviewees (P07) points out. The thought of a fully autonomous surgery robot might also leave patients too skeptical as of now (e.g., P05). Nonetheless, such systems are already being researched and developed (see, e.g. Opfermann et al. 2025).
This article, along with already existing research (e.g. Pelikan et al. 2018; Sergeeva et al. 2020), shows—among other things—that the implementation of a robot may change role dynamics and the distance between diverse roles. Hence, the following subchapter addresses team member roles upon implementation of an ESS as well as the factor that distance plays between those roles.
2.3 Robot-mediated team member roles and the distance between them
We depart from an understanding that roles of team members in robot-assisted surgery settings are diverse with regards to a whole host of aspects such as tasks, hierarchical positions, rights, and responsibilities. In addition, the choice/distribution of a role depends on factors such as abilities, expertise, preferences etc. Further, the introduction of an embodied system, such as the da Vinci ESS robot, can alter role specifics (Siemon et al. 2020)
Team roles in healthcare scenarios have been repeatedly identified as an interesting research subject. Vaulont et al. point out the importance of differentiating between “core” and “non-core roles”, as they put it. This article, however, refers to those respective roles as “concertmaster” and “ensemble roles”.4 In a surgery context, the "concertmaster role" would be that of the surgeon, while the other team members would be occupying “ensemble roles” (2021). Other studies seek to improve roles in surgery contexts by translating crew management techniques implemented by pilots in aviation teams (McGreevy et al. 2006) or tobalance out physical and mental workloads to reduce the risk of, e.g., malpractice or injuries (D. Yu et al. 2016).
Considering the implementation of robots in work teams, the team coordination changes due to differing patterns of interaction (Jung et al. 2017). While the building of subgroups in strictly human teams is a positive indicator for performance, a study conducted in a team working with robots finds preliminary results that suggest that subgroups in mixed human–robot teams have adverse effects on outcomes (Robert & You 2015). In a study of work team coordination in a healthcare setting, Beane and Orlikowski find that the outcomes of coordination are heightened in both positive and negative directions, when post-surgery teams work together with a robot (2015).
Robots can also significantly influence—both positively and negatively—team members’ cognitive over- and under-loads. One illustrative example is the extent of alarms that robots might communicate during a task. This could lead to overload on part of the human, who cannot keep up with the processes because they are constantly occupied by responding to the alarms (Saunders et al. 2016). As will be shown in our results section, this aspect is particularly relevant to the present study because some team members—in this case surgery nurses—seem to experience under-load as the ESS robot is introduced to the surgery setting, due to a decrease in responsibilities.
Many studies find changes in the dynamics of teamwork due to physical distance of team members, especially between the concertmaster role (the console surgeon) and the ensemble roles (the rest of the team). That is based on the remote operation of the robot, which results both in augmented and reduced (physical) capabilities, depending on the positions and movements at hand. The distribution of a team changes the coordination processes on the one hand and reconfigures team roles on the other hand (Sergeeva et al. 2020). This impacts both cognitive and affective areas of teamwork during surgeries. Situation awareness and common ground need to be sustained as aspects of cognitive distance. Equally, affective states (whether shared or not) need to be restored, as the team members’ sensitivity towards these issues decreases. Distance can influence power distribution, practice, and collaborative experience within the team (Pelikan et al. 2018).
Overcoming distance has been an important research theme, for example in the literature on virtual teams (Gibbs et al. 2017; Gibson & Cohen 2003; Maznevski & Chudoba 2000). When collaborating over distance, group structure, abilities, and skills are important for the success of this collaboration, as much as trust, shared understanding, and integration. However, so far, there has been a strong focus on the design of the interaction between humans and robots. With the notable exception of a few studies (e.g., Pelikan et al. 2018; Sergeeva et al. 2020), the causes and consequences of robot-induced collaboration on human–human work teams has not been examined sufficiently.
Sergeeva et al. focus on the embodiment of distance and its consequences, however, the impact on interaction and coordination of teamwork was not at the center of the study (2020). While Pelikan et al. regard cognitive and affective states as consequences of physical distance, they only focus on the main surgeon, without detailing the effect it has on the other team members (2018). Thus, the cooperation within teams to overcome distance has not yet been understood in detail. This article seeks to close this gap by understanding first, how distance evolves in a (surgical) team, and second, which strategies those teams take to overcome the distance.
In an effort to clarify this paper’s conceptualization of distance, we mainly look at two perspectives:
(1) the distance of the unit that is built by surgeon and robot (the ‘surgeon-robot-tandem’) vis-à-vis the rest of the team and (2) the distance of the individual role ‘surgeon’ vis-à-vis the rest of the team, while the robot is present. In a general sense, these two concepts of distance cannot truly be separated, since the robot is not (yet) capable of agency5 and, hence, cannot be thought of as an individual team member (= perspective 1). That being said, for this specific context, the more relevant perspective is the growing distance between the surgeon and the other team members as a result of the robot being present (= perspective 2).
3 Research method
For this study, we employ an explorative research design in order to investigate in detail the use of the ESS robot in a specific healthcare context (Miles & Huberman 1994). This explorative design will be detailed in the upcoming chapter.
We examine an ESS robot in a healthcare team for two reasons: first, smart robotic systems (i.e. the ESS robot) significantly influence healthcare work practices (Ramoly et al. 2018; H. Robinson et al. 2014; Tavakoli et al. 2020; Tian et al. 2019). Second, healthcare professionals usually openly discuss technology usage (Holden 2012; Hsieh 2015; Shinners et al. 2020). We apply an interview-based approach to understand robot use in different work environments (McGreevy et al. 2006). We focus on an ESS robot that is used for different surgical procedures—the da Vinci system (Intuitive Surgical, Inc., 2023).
For our analysis of the ESS robot, we used semi-structured expert interviews as our primary data source as it helped us understand how systems are used and what individual experiences with the systems were (Weiss 1995). We interviewed nine healthcare professionals with diverse experiences with the ESS robot and different areas of expertise (i.e. number of performed procedures and field of specialization, e.g., cardiology or gastroenterology)6 in order to increase the generalizability of our results (Miles & Huberman 1994). In accordance with Flick, we used a theoretical sampling strategy (2022): in the first step, we sourced professionals in the medical field with a digitalization focus (i.e., physicians and nurses in, e.g., digitalization think tanks or projects; CDOs/CIOs or other digital specialists at hospitals). From preliminary interviews, the concrete case of da Vinci emerged as the center of our inquiry, which is why the second sampling step focused on physicians using da Vinci and their team members. We would have found it interesting to also interview, e.g., nurses of’da Vinci teams’, however, we encountered two problems that made us focus on physicians only: (i) gatekeeping of team members by the physicians,7 and (ii) time constraints and the high work load of nurses in their daily lives. We made it a point to ask the physicians to include—to the best of their abilities—the perspectives of their team members.
The final sample arose through a Germany-wide search of hospitals using da Vinci and a cold acquisition based on contact information known to us via hospital websites. Additionally, two of the interviewees were suggested to us by other interview partners. Neither did we have a private or professional relationship with anyone from the group of contacted potential and final interview partners, nor were any of them previously known to us.
We sampled physicians with a diverse experience with ESS robots, ranging from an initial understanding to more than 1000 conducted procedures. Table 1 provides an overview of our interview sample. On average, the physicians conducted around 600 procedures. The ‘typical’ team using an ESSrobot consists of five experts, including anesthesiologists, nurses, and surgeons, however, this is highly dependent on the type of procedure performed. The interviews were iteratively conducted by one of the authors in October and November 2020. The interviews lasted around 49 min on average.8
Table 1
Overview of the interview sample (anonymized)
ID
Expertise
Experience with ESS robot
Team size
Duration (min.)
P01
Stomach
High
6
60
P02
Upper GI*
High
5
72
P03
Stomach
Medium
5
65
P04
Thorax
High
6
23
P05
Upper GI
High
4
62
P06
Pain Medicine
Low
4
43
P07
Cardiovascular System
Low
5
29
P08
Upper GI
Medium
6
20
P09
Urology—
Medium
5
62
*GI = gastrointestinal tract
For the interviews, we used interview guidelines that consisted of three topic areas. First, we asked interviewees to describe how the system is used in their work context and how they perceive it. Second, we particularly asked about the interaction with the system, e.g., how the system is operated or how team processes are affected. Third, we asked interviewees to describe episodes of the ESS robot use as illustrations for our questions. Here, we were particularly interested in situations that involved failure and conflict and how the surgical team responded to these scenarios. The interviews were complemented with technical documentation and experience reports on the ESS robot. The participating physicians gave informed consent on our interviewing methods, especially the measures taken to ensure their anonymity and confidentiality.
The interviews were tape recorded and extensive memos were written to synthesize our findings. The memos were used as summaries of the respective interviews, as an aid to get answers to open questions in the next interview, and to support cross-interview synthesis (Weiss 1995). The interviews were transcribed and coded. We initiated the coding process by implementing open codes, before adding analytical codes to finally extract the main categories (Miles & Huberman 1994). Table 2 provides an overview of the coding structure as well as corresponding exemplary quotes from the interviews and concludes chapter 3, before we dive into the results of our research in the next section.
Table 2
Coding structure with exemplary quotes from the data
Quote
Code
Category
„In the traditional laparoscopy, you don’t have the same degrees of freedom” (P09)
Degrees of Freedom
Physical
„The third arm is extremely important” (P04)
Robotic Arms
„…the degrees of freedom and the comfortable sitting of the surgeon. in a normal laparoscopy, you are standing quite uncomfortably” (P09)
Ergonomics
„Every human being has a physiological tremor and the robot does not” (P03)
Bodily Limitations
“The only thing I’m missing is the haptics “ (P02)
Missing Haptics
„I can see in 3D, without any video glasses knickknacks” (P02)
3D Vision
Visual
„We can use fluorescent material, ICG is so-to-speak a classic, a green coloring agent that fluoresces, we can give that into the vein to visualize the status of blood circulation “ (P09)
Augmentation with Additional Information
„Thus, I also have the advantage that I can concentrate for a long time in a row because I can see with 10 × zoom” (P02)
Zoom
„In robotic surgery, I have more perspectives, I can, for example, look up from below. In open surgeries, I can only look down from above” (P08)
Angled Perspective
„If the camera is full ofblood, I can’t see anymore” (P08)
Dirty Camera Lens
“In robotic surgery, I have three arms that I move myself, so I only need one [assistant] at the table and that’s it” (P08)
Higher Autarky
Coordinative
„The da Vinci is not dynamically and flexibly useable” (P01)
Reduced Flexibility
„[…] if the assistant sees an up and down in gas and at the same time the abdominal wall shakes, and I wonder why I cannot see properly, I need the feedback from behind [the assistant]” (P09)
Challenges in Communication
„The da Vinci surgery takes a little longer in the beginning, in the preparation” (P08)
Increased Length of Surgical Procedure
As can be seen from Table 2, three main categories have been extracted from the coding process—namely physical, visual, and coordinative impacts that the implementation of the ESS robot has had on the work of surgery teams. These impacts—both positive and negative—will be presented in more detail in the following chapter.
4 Results
Our findings can be separated into three parts: (i) the work situation itself, (ii) impacts of the ESS robot on the work situation (i.e., improvements and obstacles), and (iii) strategies to overcome the new distance in surgery teams that work with ESS robots. Before diving into these aspects, however, we should first briefly describe the work environment of our case.
When working with an ESS robot, physical space, timing of activities, and roles conducting the activities are affected. During an ESS robot-assisted surgery, the operating room usually consists of the patient on the operating table, the console unit, the patient cart with the four instrument arms, including instruments and the camera, the anesthesiologist equipment, and the vision cart with the screen for the scrub nurse, stand-by assistant, and anesthesiologist (s. also Fig. 2 on p. 7).
An ESS robot-enabled surgical procedure involves four stages: (i) the preparation stage, in which the operating table is prepared, the patient gets anesthetized, washed, and covered, (ii) the docking stage, in which the instrument arms are equipped and the ESS robot gets docked to the patient, (iii) the surgical procedure, in which the console surgeon operates with the ESS robot via the console, and (iv) the conclusion stage, in which the surgeon uses the robot to remove the trocars and suture the wound, before the system gets undocked. Usually, there is also a short debriefing of the team after the operation.
The roles involved in an ESS robot-enabled surgical procedure comprise the anesthesiologist, whose main task is to monitor the patient and their reaction to the anesthesia; the scrub nurse, whose main task is the preparation of the table, the tools, and the patient; the stand-by surgeon, whose main task is to stand by as a sterile back-up surgeon for take-overs in emergency situations; and the console surgeon, whose main tasks are to operate the ESS robot during the procedure as well as to terminate the procedure by suturing the patient via the ESS robot. The console surgeon uses the joysticks in the console to remotely move the four robotic arms of the ESS robot, which perform the procedure on the patient. This, and the team leading capacities that the console surgeon takes up, are the reasons why they can be described as the concertmaster among the involved team members.
4.1 Improvements of the work situation
Our data revealed several improvements and obstacles in ESS robot-enabled surgical procedures. In our study, interviewees described several improvements for their work that were caused by the ESS robot. These include physical, visualization, and coordination improvements. One of the interviewees described them as follows:
In robotic surgeries, you usually have two [degrees of freedom] more. That is the biggest advantage of robotic surgeries, if you ask me. But really, it is the fusion of the three advantages: camera and visualization, freedom of motion, and the ergonomic operating position (P05).
4.1.1 Physical improvements
Starting with the physical improvements, one of the main aspects has already been highlighted in the quote above: the degrees of freedom. This means that in ESS robot-enabled surgeries, the instruments attached to the robotic arms can be moved in every direction, as opposed to non-robotic surgeries. Although open surgeries offer the flexibility of operating in a larger cavity, the space is not enough to navigate the surgeon’s hands and the instruments they are holding. ESS robots thus combine the advantages of open and laparoscopic surgeries by allowing the surgeon to move as freely as possible in the respective cavity, even with a small incision and, hence, less trauma.
[...] when I see that I now have seven degrees of freedom instead of five, I can work much, much better around corners (P02).
A second advantage is that the ESS robot is equipped with four arms, while in a classic operating room the surgeon can only use their natural two arms. Of these four remotely controlled arms, one holds the camera that the surgeon is navigating. The other three robotic arms offer one arm more with which the surgeon can operate, as opposed to a surgery performed with their natural arms. One example to use this third arm is by cutting through tissue and fixing the opening, while the other two arms can be used for the procedure itself.
The nurse prepares the table and everything else, among other things the four arms, of which one is blocked by the camera and three by instruments (P02).
The four robot arms then are all docked, and I can operate with one arm more than I can use in reality (P01).
Other physical improvements are better ergonomics and the compensation of bodily limitations. Improved ergonomics and workplace safety are the results of a seated, slightly tilted operating position at a certain distance from the operating table. The bodily limitations, which are overcome by the ESS robot are, e.g., the adjustment of the hand tremor that every human naturally has, and the improved eyesight.
I definitely see myself as a very good surgeon, also with my own hands. But I also see that I reach a limit with my hands, with my eyes, and that I need additional technologies (P02).
Many surgeons got infected with hepatitis when operating, because those pathogens had not yet been known. Now, that cannot happen anymore, de facto, [...] and other substances also cannot get into the eyes anymore, the surgeon stays simply aside (P01).
4.1.2 Visualization improvements
The visualization of the surgical procedure also bares improvements. One such improvement is 3D vision. In laparoscopic surgery, the on-screen images are usually displayed in 2D vision. This presents a massive improvement, as it allows a simpler navigation in the respective cavity. Some people have low spatial awareness, including surgeons. For these surgeons, navigating in a three-dimensional room with 2D vision presents a challenge, which can be overcome by the 3D vision in the ESS.
I can also change my perspective; in an open surgery, I can only look at the situation from above, with da Vinci, I can also look at it from another angle, from the bottom up for example (P08).
I see it all in 3D and that is without any video glasses ‘knickknacks’, without any lenses that cover half of my field of vision (P02).
Another visual improvement is the augmentation of certain aspects with additional information. For instance, one can select fluorescent lighting to indicate underlying blood vessels or the option of including additional information sources as second images (e.g. ultrasound imaging). The former offers easier identification of blood flow, since—as P02 put it—during the surgery, “everything is a beautiful pink”, however, blood circulation is not directly observable in all cases. Therefore, the highlighting of these vessels makes the surgeons’ work easier. The latter facilitates the process by allowing the surgeons to see both the real-time image of the surgery and previously taken images at the same time without looking up at a second screen.
I also can select additional equipment. If I use my ultrasonic device, for example, I can let the image be fused into my other image. That is really great! (P02).
Standard surgery magnifying equipment allows for a 2.5 × zoom. With the ESS robot, surgeons are able to increase the zoom incrementally. Thus, they can set the magnification to a level of up to10 × zoom, which helps especially in situations where extremely small areas must be visualized.
Traditional magnifying glasses used in surgery offer a 2.5 magnification and the robot is capable of 10 (P03).
ESS robot surgeons are also able to choose between different (angled) perspectives. In addition to a 0° perspective (‘normal’ vision), the surgeon can choose between’30 up’ and’30 down’ perspectives, depending on whether they prefer to view the area of interest from above or below. This indicates that the ESS robot can be applied to many different surgeries. Depending on the performed procedure, that can facilitate the surgery immensely, as P02 points out:
I can also see the optical settings, whether I have a 30 up or a 30 down, so I generally have 30° vision, that means I can work with either looking up or down. Us visceral surgeons usually work with a 30° down vision and like to look from above, while urologists like to use a 0° vision (P02).
4.1.3 Coordination improvements
Lastly, the third group of improvements deals with coordinative improvements. For instance, the need for coordination during the surgical process is reduced because of the higher autarky that surgeons have with the ESS robot. That is, on the one hand, surgeons do not depend on an assistant to hold and navigate the camera, and on the other hand, surgeons have one arm more to, e.g., hold a tissue entrance. Both improvements reduce the need for coordination with the assistant. One surgeon explains:
The surgical procedure itself is in principle easier because you have full control. You can,– with a few minor exceptions be very autarkic. Da Vinci allows you to operate alone, you basically don’t need the assistant anymore, just someone who substitutes the instruments (P03).
Another aspect that supports the improvement of coordination is the higher variability. Surgeons are more variable in that they can operate with the ESS robot, but they can also switch positions to the operating table for additional perspectives or to continue performing one step of the surgery at the table and they can later switch back to the console. One surgeon, for example, reports that they like to step away from the console to perform a certain complex step during their most performed surgery:
Based on the entire duration of the surgery, I only spend one fourth of the time at the console [...] What happens in the meantime? [...] Partly, I decide to intervene actively [...] That takes 20 to 30 minutes each, [...] but other than that, I also stand up when instruments collide, when my assistant tells me that something doesn’t look right. Sometimes, I just stand up to take a five-minute mental break, before heading back in (P01).
Related to the spatial aspect, many experts mention that remote virtual work with da Vinci could be an interesting advancement of the ESS robot (e.g., operating on patients in a war-torn country—think the Gaza Strip for example, for topicality reasons—from a remote location, such as Germany). However, P06—and some of their colleagues—claim that regulations, licenses etc. might become an issue for that.
Obstacles.
4.2 Obstacles of the work situation
Not only the improvements, but also the obstacles can be divided into physical, visualization-, and coordination-related. It is important to point out, however, that other aspects were mentioned by the interviewees (e.g., P06 and P07), such as lack of financing, regulatory hurdles, data protection, data security, and inter-facility cooperation. Nonetheless, these issues will not be detailed in the following, as they are not part of the main focus of this paper.
4.2.1 Physical obstacles
We found the first—and one of the most often mentioned—obstacle to be physical: the missing haptic feedback in ESS robot-enabled surgeries. To put it crudely, the surgeon cannot feel the touch of tissue through the metal arms. That is crucial, however, because haptics is an important sensory feeling that surgeons use to judge on, for example, tissue density. Without it, the surgeon might break a suture and a new one must be handed to them, which costs precious time, as one interviewee indicates:
It would be nice if we had the haptics [...] It’s not only the touch of the tissue, but more so the resistance of the tissue that I miss. For example, if I suture with a thin thread, it happens quite often that the suture breaks. And then, you have to get a new thread and might have to start the suturing over again (P09).
Another physical problem might be the ESS not (correctly) identifying the attached instrument. P09 says that certain error codes can be managed on the spot by the physicians and their team but for other error codes, the emergency phone number written on the console must be called. They add that help is usually quick and easy and they never had the case of the ESS failing to work completely without getting it to start again.
4.2.2 Visualization obstacles
Concerning the visualization, the main obstacle is the soiling of the camera lenses in the cavity. The human body contains blood and, especially in the abdominal cavity, fat. Those two substances can easily spread across the lenses and hinder the vision of the surgeon. This can result in unproductive phases throughout the surgery and, ultimately, in a longer duration of the procedure. P08 summarized it pragmatically: “If the camera is full of blood, I can’t see anymore” (P08).
Another visual obstacle might be the disregard of the outside of the surgeon’s field of vision. This case occurs rather often because the visualization via camera does not allow for the surgeon to simply turn the head, for example, to look to the side. This might result in complications, e.g., when the out-of-sight robotic arm gets in the way and collides with another arm.
Also, the awareness has to be developed in a different way because the visualization is different. You only see the inside perspective of the body; you have no awareness of what is outside of your field of vision. If there is a complication, the reaction time is also higher in case you must leave the console and solve it at the table. That happens, I would say, in every second or third surgery (P05).
4.2.3 Coordination obstacles
Moreover, there are coordinative obstacles due to the implementation of the ESS robot. For example, challenges in the team communication arise. The remote positioning of the console forces a spatial distribution of the operating team. This results in different (indirect) perspectives of team members and a more complex communication. From the physical distance also emerges a mental distance within the team, which can cause team members to feel detached from the procedure.
Apart from the local separation, there is also a mental separation of the team, when the nurses or assistants don’t need to intervene for 20, 30 minutes and then start to chit-chat about more interesting things, which is normal. I don’t always interfere with that, unless it distracts me from the surgery, because I also have the responsibility to make the team comfortable (P05).
Another coordinative obstacle is the lack of spatial flexibility in the ESS robot. Due to its size and weight, as well as the resultant immobility, the da Vinci cannot be flexibly positioned in the operating room. If the ESS robot were smaller, lighter, and/or mobile, it could be moved around the room to allow for a more flexible positioning and a change of perspectives/entry angles throughout the procedure, as P03 explains.
Another minor coordinative obstacle is the sometimes-increased duration of the surgical procedure as caused by the ESS robot. Depending on the respective surgery, the procedure might take longer. P02 argues that—on average—the additional duration is around 20 to 30 min, from their perspective as an upper gastrointestinal—stomach and intestines—surgeon. That might at first not sound like a lot of time, but keeping in mind that every minute in the operating room of a large hospital might cost up to 80 €, an additional half hour of surgery time can cost up to 2400 €. With two ESS robot surgeries per day and five operating days per week, that would add up to around 24,000 € a week.9
[…] it always takes a little longer. It’s not that much. It’s on average more or less 20 to 30 minutes, […] especially for shorter surgical procedures. Given the fact that a minute […] costs around 70–80 €, […] then those are already considerable costs (P02).
The central obstacle overall—and hence the major aspect in answer to RQ1—can be identified as the increased distance between surgeon, team, and patient, because distance is at the root of all the above-mentioned obstacles. The problem of missing haptics is difficult to resolve over the distance between the instruments and the surgeon console. The more complicated team communication is based on the distance and the missing non-verbal communication. The increased duration of surgeries stems mostly from the time-consuming setup but also from time losses due to the other mentioned obstacles, such as mental breaks or phases away from the console, in which the surgeon seeks a different perspective. For the teams, it is thus imperative to find a solution to overcomedistance in ESS robot-enabled teams, which will be the focal point of the following subchapter.
4.3 Overcoming distance in ESS robot-enabled teams
In our data, we found several strategies the surgical teams use to overcome the obstacles imposed by ESS robots, as summarized in Fig. 3. It shows the distance-related obstacles in the coordination within the team (separated in both communication and team understanding) as well as the distance-related obstacles in the interaction with the ‘object’ of the surgery (i.e. the patient). The latter consist of visual (e.g., team members do not have the same perspective on the patient anymore) and physical obstacles (e.g., missing haptics).
Fig. 3
Types of obstacles occurring when surgical teams interact with ESS robots (own depiction)
One of the compensation strategies are visual cues. These are used to overcome the missing haptics. As mentioned earlier, haptics is not yet available in a satisfying manner. Therefore, a previously integral part of the surgery procedure, the use of the touch sense, is now missing. This does not only indicate the loss of feeling the condition and texture of tissue, but also its resistance. Surgeons who operate with da Vinci overcome this issue by visual cues taken from experience.
Missing haptics has a stronger impact on some surgeons than it has on others. [...] Changes in tissue are also observable with a trained eye. [...] We call this ‘optical tactile feedback’ here at [Name of Hospital] (P04).
Another aspect that calls for compensation is the physical distance between the surgeon and the rest of the team. The distance can be overcome by implementing visual cues to highlight certain areas, which could have been simply pointed out before. While now directly pointing towards a region of interest during the surgery is not feasible anymore, due to the different perspectives and fields of vision, the surgeon can visualize the respective area with colored lines, which are being displayed on the vision cart next to the operating table.
I cannot show it directly at the table anymore, but I can visualize it, can mark a region in the cavity and then they [the colleagues] see some blue lines on their display (P04).
Lastly, the coordination of the team’s communication is more difficult due to the increased physical distance. The reasons for this obstacle are that the intended communication via microphone and speaker—albeit it being “easy” as P05 argues in the quote below—takes away from the communication, and that non-verbal information, e.g., making a colleague aware of something via a short gesture, is no longer possible, as P09 points out.10 This can be compensated by explaining the context more in detail via informational cues. What has previously been able to simply be shown via gestures, facial expressions, or brief spoken communication, must now be embedded in more complex contexts.
We communicate very often during a surgery. The communication with the console via microphone and speaker is very easy (P05).
[…] if the assistant sees an up and down in gas and at the same time the abdominal wall shakes, and I wonder why I cannot see properly, I need the feedback from behind [the assistant] (P09).
Thus, our research shows that ESS-enabled surgery teams react to coordinative and visual obstacles by applying informational cues, while physical obstacles are overcome by visual cues. In the following, our results will be briefly summarized and then discussed, before the last chapter offers some concluding remarks.
5 Discussion
This study has explored how surgical teams overcome distance in ESS robot procedures. We found that the surgical teams used many advantages of the system to improve surgical practice, while the implementation of the ESS robot also created obstacles. The main obstacle is the construction of distance between the concertmaster role (i.e. the console surgeon) and the ensemble roles. Our results suggest that the team members used different forms of cues to overcome the physical distance in the surgical team caused by the ESS robot.
This study contributes to the teamwork and communication literature by reinforcing the finding that team dynamics change due to the implementation of robotic assistance. We further confirm that the physical distance between the concertmaster and ensemble roles of the team is increased with the ESS robot (Pelikan et al. 2018; Sergeeva et al. 2020), however, our results also show mental distance within the team. The physical distance creates a situation, in which some ensemble roles do not intervene in the surgical process for significant portions of time, which builds an emotional and cognitive distance from the surgery. The team members cannot engage in the same way as before and thus are detached. This detachment shows itself through mental withdrawal and focus on other topics. Teams develop informational and visual cues to overcome the distance (s. Figure 4).
Fig. 4
Model of how the team overcomes increased distance via informational and visual cues, embedded in the simplified STS model, as seen in Fig. 2 on p. 5 (own depiction, based on Bednar and Welch 2020)
Moreover, we add to the research body of team roles. The implementation of the ESS robot leads to changes in the roles of surgical teams (Belbin 1993; McGreevy et al. 2006; Vaulont et al. 2021; D. Yu et al. 2016). Put more concretely, team roles are trimmed, enriched, and redesigned.
The role of the scrub nurse, for example, is being trimmed. Especially during the procedure, the nurse has few supporting tasks and far in between. Their focus in the process of the surgery lies mostly on the preparatory tasks before the surgery starts, and their interaction focus switches from the surgeon to the ESS robot. The role of supporting and implementing throughout the procedure is trimmed and de facto results in a degradation of importance for the scrub nurse. However, P06 does not see the roles of nurses (or physicians) as at risk of being eliminated any time soon.
In contrast to this, the role of the stand-by surgeon is being enriched. The responsibility of emergency takeover of the surgery procedure lies in the hands of the stand-by surgeon because the console surgeon is physically distant from the operating table and it takes longer for them to react. Also, the console surgeon is not necessarily in sterile attire and might thus not be prepared to take over the process at the table. The perspective of the stand-by surgeon directly at the operating table also becomes a valuable complementation to the remote perspective of the console surgeon. The role of monitoring and evaluating is hence enriched.
Part of the roles is also redesigned. The coordination becomes more standardized to countervail the increased difficulty of coordination. Also, the ESS robot strengthens the surgical skills of the surgeon and enforces the need to increase the level of contextual information in the team communication. That is required mostly because of the physical distance and the resulting omission of non-verbal communication, such as gestures and facial expressions. All in all, the ESS robot strengthens the expertise of the surgeon as well as the standardization and formalization of supporting processes.
To overcome the distance resulting from the ESS robot implementation, team members design cues. On the one hand, they must use informational cues to overcome the change from face-to-face communication to remote communication. That means that they must communicate more clearly, i.e. embed the information in a more concrete context. On the other hand, team members use visual cues to bring together the now different perspectives of the surgeon and the other teammembers. Not only the process of the technology changes but also the interaction with it. The case of the ESS shows the importance of designing the entire interaction, both regarding the social and the technical subsystem. This STS perspective and the resulting design propositions for the entire system are crucial for different work contexts (Lyytinen & Newman 2008).
Previous research in the scientific literature has discovered the great potential of smart robotics in healthcare applications (Beane & Orlikowski 2015; Olaronke et al. 2017; Tsui & Yanco 2007). Our research illustrates the improvement of surgical procedures by supporting surgical team dynamics with the ESS robot. Future research can build on that by designing improved ESS robots with optimized measures of team dynamics.
The virtual work literature investigates the requirements, under which teams that are globally dispersed function and cooperate well (Maznevski & Chudoba 2000). This paper contributes to that idea by showing that the strategies of overcoming problems in virtual work function as well for teams that work in the same room, but are locally (and mentally) distributed.
On top of that, this article contributes to the human–robot interaction literature by showing that the central counterpart of the interaction during the surgery procedure switches from the console surgeon to the ESS robot. That means that we do not only need new interface designs, but also new structures for improved interaction with ESS robots, such that informational, visual, and other potential cues be transferred through the robot and its communication devices.
Our article provides insights into the design of team dynamics in ESS robot-enabled teams: clear communication with a high level of quality in contextual information, changes in role distribution for different members of the surgical team, and standardization of processes. Moreover, we provide insights on how to overcome physical and mental distance. The use of visual and informational cues is imperative in ‘healing the symptoms’ of physical distance. Software and hardware developers can utilize our findings to improve ESS robots.
Furthermore, medical—but also general—management staff can use our findings in various ways: they can improve the composition of (surgery) teams and their governance style. Our STS model shows that the use of teamwork and communication tools can transcend individual boundaries and result in solutions for system issues, optimizing work processes and outcomes.
Our findings are not just limited to the context of da Vinci surgeries, but can be generalized to a broader management audience. Upon implementation of a robot into an existing work team, certain effects might emerge: (i) robots can lead to changes in work processes, team dynamics, and team distribution. Managers should plan in advance, which changes are likely and design plans to counteract, if necessary. (ii) Often overlooked is the necessity of adjusting processes around the robot, which do not directly involve it, to ensure optimal implementation and reduce the risk of novel problems. One example of such problems from our article is the growing mental distance in ensemble roles, which could be overcome by reducing over- and under-load in team members affected by the change of role characteristics and relevance. If possible, such changes should be anticipated and feasible reactions prepared. (iii) The main counterpart of interactions from human team members might well switch from other humans (e.g., the concertmaster role) to the robot, depending on the type of robot implemented, its role, and its embedding into work processes.
Nonetheless, as every research endeavor, our article is subject to limitations, which will be specified hereafter.
6 Limitations and future research
We used an explorative design which allowed us to study the phenomenon in detail, but potentially limited the generalizability of our findings to a certain degree. Given our limited number of interviewees, we strived to sample for diversity in expertise (i.e. medical field) and experience (i.e. level of experience with da Vinci).
A second limitation is that we focused on established teams that adopted ESS robot surgery. Hence, future research could examine how new teams form around this ESS robot. Another option for further research would be an experiment with each of the three types of informational cues that tests their effects on coordination and distance.
An important point of view that is also not represented in our research to the level it would deserve is the further inspection of intra-role phenomena. Such research efforts could highlight the effects that the change of role characteristics and team dynamics upon implementation of an ESS might have on work ethos and identification with one’s own work. Put into the context of this article, one could ask what the trimming of the nurse’s role does with their perceived job satisfaction and well-being, following research such as Smids et al. (2020). Moreover, we were unfortunately not successful in conducting interviews with nurses, yet their role is the one that was found to be the most negatively impacted by the implementation of the ESS robot. Further research could strive for a stronger inclusion of their voices.
In addition to the aforementioned cues that surgery teams use to overcome distance, there are other possible cues, which help overcome the increased distance between team members. One such cue that is conceptually different to the ones mentioned in this paper would be augmented reality (Klinker et al. 2020).
Another interesting aspect would be to see if the findings hold as well, if they are not restricted to one room. As one interviewee pointed out: “there is the possibility of virtual connection. In principle, […] I could call one of my colleagues in the USA and they could see what I am doing in the surgery […] and probably, it would even be possible that they sit at the console in the USA and I sit in [German City], and we operate together” (P03). Possible questions with this idea are as follows: if there was an attack in a war zone, for example in the Gaza Strip, and one console surgeon would perform a surgery on a wounded person remotely from Germany with a surgical team in the Gaza Strip—provided it was legally feasible—would our findings still hold in such a situation (Gibbs et al. 2017; Gibson & Cohen 2003)? And which other aspects could be found to impact the outcome, performance, and coordination of the surgery?
The previous chapters have shown that our research has addressed certain gaps in the existing literature, while opening doors for further examinations. With the last portion of this article, we would like to point out the main aspects of this paper to tie it all together.
7 Conclusion
In this study, we analyzed the interaction of surgical teams with ESS robots for the specific case of the da Vinci system. We interviewed medical professionals of diverse backgrounds, considering both their experience with the system and their area of expertise. The interview questions focused on the interaction with ESS robots. We found that the surgery procedure, conducted via an ESS robot, changes the process of the surgery, the work dynamics, the interaction with the ESS robot, and the interactions within the team. Improvements and obstacles of three different dimensions were identified: physical, visual, and coordinative. The most important obstacle is physical (and mental) distance. Moreover, we found certain cues, which surgery teams employed to overcome the identified obstacles. These cues can be identified as either informational or visual in nature.
Acknowledgements
The authors thank the participating medical practitioners immensely for lending their expertise to our research. To guarantee anonymization, the respective surgeons cannot be thanked individually, nonetheless, we do appreciate each interviewee’s insights. Furthermore, we would like to thank Prof. Dr. Manuel Wiesche for his much appreciated help in the creation of this paper.
Declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
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‘Digital Taylorism’ is the twenty-first century, (digital) knowledge work counterpart of ‘Mechanical Taylorism’ and can be defined as the productivity-driven increase of efficiency in knowledge work brought about by the implementation of new digital technologies. The codifying of specific knowledge by means of algorithms can create effects that make certain roles/jobs obsolete and hence put them at risk of being eliminated (Brown et al. 2010; Schank 2019).
Open approach: respective body area is generously opened with a scalpel and the surgeon operates in the open cavity; laparoscopic approach: minimally invasive surgery with smaller incision—keyholes—and, ergo, less trauma (Veldkamp et al. 2005; Wilson 1971).
While the distinction between “core” and “non-core” roles that Vaulont et al. (2021) make is clear to us, we prefer to use different terms. We find teamwork to be well described by the metaphor of playing in an orchestra– if every orchestra member contributes their part, it’s like a symphony of team effort. Hence, we prefer to speak of the “concertmaster” and “ensemble”, lending from the terminology of orchestral music. This reflects that the console surgeon (“concertmaster”, otherwise known as first violin) sets the tone of the surgery, while still being part of the ensemble (other than a “conductor” might be) and without devaluing the importance of the other ensemble members and their respective roles. We thank Reviewer #1 for the inspiration of this change.
We thank Reviewer #1 for the inspiration of this change.
Agency, here, is understood as “possess[ing] a temporally-embedded capacity to intentionally constrain, complement, and/or substitute for humans in the practice of routines”, as suggested by Murray et al. (2021).
Cardiologists focus on diseases of the heart and gastroenterologists on the organs of the stomach (Definition of Cardiology 2025; Definition of Gastroenterology 2025).
The authors want to emphasize that ‘gatekeeping’, here, is not meant in a disparaging way. We just found physicians to respond to our requests for interviews with further team members with hesitation, explaining their reaction with, e.g., trying to keep the nurses from performing additional (and at that unpaid!) work.
This exemplary calculation stems from P02 and the numbers included in this paragraph are illustrational, yet realistic, values, according to the interviewee.
For a more detailed account on the underlying theoretical background from communication and virtual teams research, see, e.g., Koester (2022) or Andres (2002).
