Purpose
Perioperative staff shortages are a problem in hospitals worldwide. Keeping the staff content and motivated is a challenge in the busy hospital setting of today. New operating room technologies aim to increase safety and efficiency. This causes a shift from interaction with patients to interaction with technology. Objectively measuring this shift could aid the design of supportive technological products, or optimal planning for high-tech procedures.

Methods
35 Gynaecological procedures of three different technology levels are recorded: open- (OS), minimally invasive- (MIS) and robot-assisted (RAS) surgery. We annotate interaction between staff and the patient. An algorithm is proposed that detects interaction with the operating table from staff posture and movement. Interaction is expressed as a percentage of total working time.

Results
The proposed algorithm measures operating table interactions of 70.4%, 70.3% and 30.1% during OS, MIS and RAS. Annotations yield patient interaction percentages of 37.6%, 38.3% and 24.6%. Algorithm measurements over time show operating table and patient interaction peaks at anomalous events or workflow phase transitions.

Conclusions
The annotations show less operating table and patient interactions during RAS than OS and MIS. Annotated patient interaction and measured operating table interaction show similar differences between procedures and workflow phases. The visual complexity of operating rooms complicates pose tracking, deteriorating the algorithm input quality. The proposed algorithm shows promise as a component in context-aware event- or workflow phase detection.

Technological advancements are accelerating at an unprecedented pace, reshaping societies, economies, and individual behavior. While these innovations offer benefits such as improved communication, and data-driven decision-making, they also present challenges, including ethical concerns, inequality, job displacement, and regulatory lag. Nowhere are these dynamics more critical than in healthcare, where emerging technologies promise to address rising demand and workforce shortages. However, the gap between technological potential and real-world implementation remains wide.

Healthcare systems, particularly in surgical care, struggle to adopt and sustain innovations like AI and robotics due to their complex, context-specific environments. A projected global shortage of 12.9 million healthcare professionals by 2035, with surgical nurses playing pivotal roles, underscores the urgency of aligning technology with clinical practice. Many MedTech solutions fail to move beyond pilot stages, hindered by a disconnect between design and real-world use.

This thesis investigates how medical technology interacts with the complex, high-stakes environment of the operating room. Across five studies, it examines both systemic and human-centered factors that influence technology adoption, with a focus on workflow dynamics, performance metrics, and professional experiences. A key finding is that successful implementation depends on integrating MedTech into clinical ecosystems, rather than introducing it as isolated technical upgrades....

Literature proposes numerous initiatives for optimization of the Operating Room (OR). Despite multiple suggested strategies for the optimization of workflow on the OR, its patients and (medical) staff, no uniform description of ‘optimization’ has been adopted. This makes it difficult to evaluate the proposed optimization strategies. In particular, the metrics used to quantify OR performance are diverse so that assessing the impact of suggested approaches is complex or even impossible. To secure a higher implementation success rate of optimisation strategies in practice we believe OR optimisation and its quantification should be further investigated. We aim to provide an inventory of the metrics and methods used to optimise the OR by the means of a structured literature study. We observe that several aspects of OR performance are unaddressed in literature, and no studies account for possible interactions between metrics of quality and efficiency. We conclude that a systems approach is needed to align metrics across different elements of OR performance, and that the wellbeing of healthcare professionals is underrepresented in current optimisation approaches.