Presentation (CTI)

OBJECTIVES: Health systems face increasing workforce pressures, with sickness absence contributing to reduced capacity and higher costs. In orthopaedic surgery, high physical and psychological workload drives musculoskeletal and stress-related absence. Robotic-assisted (RA) systems are increasingly adopted in routine practice; however, their impact on workforce outcomes remains poorly understood. Evidence using NASA Task Load Index (NASA-TLX) demonstrates reduced physical and mental workload during RA procedures, generating the hypothesis of reduced workforce absence. To our knowledge, this is the first real-world evidence (RWE) evaluation linking RA surgical systems to workforce absence outcomes. The objective of this analysis was to evaluate the association between orthopaedic RA surgical system adoption and staff sickness absence in NHS hospitals, and whether findings are consistent with workload-related mechanisms.
METHODS: This cross-sectional RWE analysis used hospital-level sickness absence data obtained via Freedom of Information (FOI) requests (September 2024-August 2025). Thirty high-volume NHS hospitals were contacted; 23 with complete datasets (10 robotic, 13 non-robotic) were analysed. Outcomes included sickness absence days per staff member, absence episodes, and diagnostic categories (stress and musculoskeletal). A provider-perspective cost analysis estimated absence-related costs per staff member.
RESULTS: Hospitals with a RA surgical system demonstrated lower sickness absence (4.65 vs 8.89 days per staff; difference -4.24), driven by reduced absence duration. Reductions were most pronounced in stress-related (-58.7%) and musculoskeletal (-33.2%) categories. Estimated annual absence-related costs were lower in RA hospitals (£1,001 vs £1,914 per staff member), yielding £913 savings per staff-year, (estimated £91k-£182k annual savings per unit).
CONCLUSIONS: RWE data suggest that orthopaedic RA surgical systems are associated with lower staff sickness absence, with potential economic benefits for healthcare delivery. Findings are consistent with prior evidence indicating reduced procedural workload, although the datasets are independent and cause inference remains limited. These findings highlight the importance of incorporating workforce outcomes into health technology assessment of medical technologies.