Technologies and management strategies for improving operational efficiency in operating theatres: A scoping review

Introduction

Operational efficiency in operating theatres is essential for effective functioning of health care institutions. Effective communication, safety control and teamwork are recognised as key components of high-quality surgical care, contributing to cost reduction and improved patient safety (Gomes et al 2021). This issue has become increasingly relevant in the context of growing surgical demand, budget constraints and the need to reduce waiting times while maintaining high standards of care.

Operating theatres are complex, dynamic and resource-intensive environments that require coordinated strategies to optimise workflow and resource utilisation. Approaches to improving operational efficiency have included process redesign, workflow standardisation and communication strategies, including Lean Six Sigma approaches designed to reduce process variation and eliminate inefficiencies in health care workflows, as well as the use of emerging technologies such as automation, artificial intelligence (AI) and digital monitoring tools. These interventions have demonstrated potential to improve specific aspects of performance, including turnover time, scheduling accuracy and delay reduction (Cupples et al 2025, MacMillan et al 2025, Parikh et al 2021).

Perioperative nurses play a central role in coordinating workflow, managing resources and ensuring safe transitions between surgical phases. Inefficiencies such as delays, communication failures and workflow disruptions directly affect workload, increase stress and may compromise patient safety (Pasquer et al 2024, Tjugum et al 2026). For these professionals, operational efficiency is experienced in practice as the need to manage multiple interdependent processes simultaneously within a high-pressure environment.

Despite the growing body of literature on operating theatre management, existing studies and reviews focus on diverse and often isolated approaches to improving efficiency. These include process-based interventions, organisational strategies and technological tools, each targeting different aspects of perioperative workflow and evaluated using heterogeneous outcome measures (Cohen et al 2024, MacMillan et al 2025, Schouten et al 2023).

In parallel, emerging technologies such as AI, automation and digital communication platforms have demonstrated potential to improve specific components of operating theatre performance, including surgical duration prediction, resource allocation and workflow coordination (Bellini et al 2024). However, these strategies are typically explored independently, and the literature remains fragmented, without a comprehensive synthesis of the range of approaches that contribute to operational efficiency.

For perioperative teams, this diversity of approaches reflects the complexity of managing multiple strategies simultaneously, often without a unified framework to guide practice. To further explore this gap, preliminary searches conducted in major health databases did not identify scoping reviews addressing the breadth of technological and process-improvement strategies applied to operating theatre efficiency. Existing studies tend to examine clinical, technological or organisational aspects separately, rather than mapping the diversity of approaches available in the literature.

Therefore, this study is justified by the need to provide a comprehensive mapping of technological, organisational and process-improvement strategies that contribute to operational efficiency in operating theatres. This scoping review aims to map the technologies, management strategies and practices described in the literature that contribute to improving operational efficiency in operating theatres.

Method

Search strategy

Searches were conducted in PubMed, Scopus, Embase, CINAHL, ScienceDirect and the Virtual Health Library (VHL). Grey literature was explored through Google Scholar and the CAPES Theses and Dissertations Database. In Google Scholar, the first 200 results sorted by relevance were screened.

The selection of databases was guided by the need to ensure comprehensive coverage of the topic across multidisciplinary domains. PubMed and Embase were included due to their strong indexing of biomedical and clinical literature. Scopus was selected for its broad coverage of scientific publications and conference proceedings, particularly relevant for emerging technologies. CINAHL was included to capture nursing and allied health perspectives, which are essential for operating theatre management. The VHL was incorporated to ensure the inclusion of Latin American and regional literature. Together, these databases provide a comprehensive and complementary representation of the available evidence.

The search strategy combined controlled vocabulary (MeSH, DeCS and Emtree) with free-text keywords related to operating theatre efficiency and technological strategies using Boolean operators. Search strategies were adapted for each database, and reference lists of included studies were screened to identify additional relevant publications. Table 1 presents the detailed search strategies.

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Table 1

Search strategy in the databases

Base/Portal	Search strategy
PubMed	(“Operating Rooms”[Mesh] OR “Operating Room” OR “Surgical Center” OR “Surgical Suite” OR “Perioperative Services”) AND (“Efficiency” OR “Operational Efficiency” OR “Workflow” OR “Operating Room Utilization” OR “Turnover Time” OR “Surgical Scheduling”) AND (“Technology” OR “Automation” OR “Artificial Intelligence” OR “Machine Learning” OR “Digital Health” OR “Process Improvement” OR “Lean” OR “Lean Six Sigma”) Filters: 2020–2025
BVS	(“Centro Cirúrgico” OR “Sala de Operações” OR “Operating Room”) AND (“Eficiência Organizacional” OR “Eficiência Operacional” OR “Fluxo de Trabalho” OR “Tempo de Giro”) AND (“Tecnologia em Saúde” OR “Automação” OR “Inteligência Artificial” OR “Melhoria de Processos” OR “Lean Six Sigma”) Filters: 2020–2025
Science Direct	(“operating room” OR “surgical centre”) AND (“operational efficiency” OR “turnover time” OR “surgical scheduling”) AND (“technology” OR “artificial intelligence” OR “process improvement” OR “lean six sigma”) Refine by Years 2020-2025
Cinahl	(MH “Operating Rooms” OR “Operating Room” OR “Surgical Center” OR “Perioperative Services”) AND (“Operational Efficiency” OR “Workflow” OR “Operating Room Utilization” OR “Turnover Time” OR “Surgical Scheduling”) AND (“Technology” OR “Automation” OR “Artificial Intelligence” OR “Machine Learning” OR “Process Improvement” OR “Lean” OR “Lean Six Sigma”) Limiters: 2020–2025
Scopus	(“operating room” OR “surgical center” OR “surgical suite” OR “perioperative services”) AND (“operational efficiency” OR “workflow” OR “operating room utilization” OR “turnover time” OR “surgical scheduling”) AND (technology OR automation OR “artificial intelligence” OR “machine learning” OR “process improvement” OR “lean six sigma”)AND PUBYEAR > 2019
Embase	(‘operating room’/exp OR ‘operating room’ OR ‘surgical suite’ OR ‘perioperative care’) AND (‘efficiency’ OR ‘workflow’ OR ‘operating room utilization’ OR ‘turnover time’ OR ‘surgical scheduling’) AND (‘technology’/exp OR ‘automation’/exp OR ‘artificial intelligence’/exp OR ‘machine learning’/exp OR ‘process improvement’ OR ‘lean six sigma’) AND [2020-2025]/py
Google Scholar	“operating room efficiency” OR “operating room workflow” OR “surgical scheduling optimization” technology OR “artificial intelligence” OR “process improvement”
Capes Database	“operating room efficiency” OR “Operating Room Efficiency” OR “surgical scheduling” OR “Operating Room Management”

São Paulo, SP, Brazil, 2025.

Results

The search strategy identified a total of 349 records. After duplicate removal and application of the eligibility criteria, 15 studies were included in the final sample. The study-selection process is illustrated in the PRISMA-ScR flow diagram (Figure 1).

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Figure 1

PRISMA-ScR flow diagram of the study-selection process

All included studies were published within the last 5 years and examined technologies aimed at improving operational efficiency in operating theatres. Most publications were scientific articles (n = 11; 73.3%), while four were dissertations or theses (n = 4; 26.7%).

Most of the studies were conducted in the United States (40%, n = 6). The remaining studies were conducted in Jordan, Australia, the Netherlands, Italy, Brazil, Romania, China, Japan and Canada (6.7%, n = 1 each), which indicated that research on operating theatre efficiency remains concentrated mainly in developed countries.

The technologies identified included surgical scheduling automation systems, Lean Six Sigma process-improvement strategies, digital communication platforms, real-time notification systems and AI applications, such as predictive algorithms and neural networks for estimating surgical procedure duration. Detailed characteristics of the included studies are presented in Table 2.

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Table 2

Characteristics of studies included in the scoping review regarding technologies and their impact on operational efficiency indicators

Author/Year	Method	Technology	Primary metric	Measurable reduction/Improvement
Atkins et al (2024)	Study case – throughput improvement	IEEE process cohesion	Room turnover time (RTAT)	Target reduction of 14% in turnover time
Onishi and Casanova (2024)	Algorithm development: automated numerical optimisation	Artificial intelligence/Mixed-integer programming	Monthly roster-creation time	Reduction from 150 min to 8.1 min
Kubala et al (2021)	Intervention study: Surgical Efficiency Model (SEM)	Lean Six Sigma restructuring	Room turnover time	53% reduction (from 24.4 to 11.4 min)
Slagerman (2021)	Lean Six Sigma	Predictive modelling (Random Forest/LME)	Overtime prediction error	49%–59% reduction in overtime prediction error
Chen et al (2024)	Interventional study – task-grabbing system (‘Uber-like’)	Mobile application/Bluetooth tracking	Preparation and turnover time	Preparation time reduced from 43.5 to 38.5 min; turnover time from 14.2 to 12.6 min
Vladu et al (2024)	System development: Organisational restructuring and computational algorithm	Resource scheduling algorithm	Operating block occupancy (09:00–11:00)	Occupancy increased from 87.53% to 98.07%
Mitchell et al (2025)	Lean Six Sigma (DMAIC)	Workflow redesign	First case on-time starts (FCOTS)	Punctuality increased from 30% to 79%
Singh et al (2023)	Multifactorial intervention – documentation-related delay targeting	Automated pre-op orders and EMR dot phrases	FCOTS	FCOTS improved from 36.7% to 52.7%; 55.63 h saved
Kravitz (2022)	Algorithm development – comparative methodological analysis	Machine learning (Random Forest)	Scheduling inaccuracy	70% improvement in scheduling accuracy
Michelin et al (2021)	Lean Six Sigma/standardisation	Similar case grouping	Under-utilisation time	Under-utilisation time reduced by half in long theatre room cases
Kane et al (2021)	Intervention study	SMS or ID badge communication system	First case punctuality (FCOTS)	5.3% increase in FCOTS
Fyntikis (2024)	KPI evaluation framework	Hospital operational analysis	Patient waiting time (WT)	Baseline of 92.05 min compared with a 30-min benchmark
Zadeh et al (2025)	Two-stage forecasting model	SARIMAX and Poisson models (deep learning)	Mean absolute error (MAE) of arrivals	MAE optimised to 1.01, indicating higher model reliability
Ramadan et al (2025)	Convolutional neural networks (CNNs)	Deep learning/laparoscopic video analysis	Patient waiting time	87.3% reduction in patient waiting time (from 103 to 13 min)
Rocha (2021)	Observational – turnover support team	Nursing workforce management	Surgical productivity	20% increase in surgical schedule capacity (1440 additional surgeries per year)

São Paulo, SP, Brazil, 2025.

Across the studies, technological and organisational interventions were associated with improvements in operational efficiency indicators. The most frequently reported outcomes included reductions in turnover time, surgical delays and operating theatre idle time, as well as improvements in scheduling accuracy. Reported improvements ranged from approximately 10% to 25%, depending on the intervention and outcome evaluated.

These findings demonstrate that a wide range of heterogeneous strategies are being applied to improve operational efficiency, targeting different components of perioperative workflow.

Discussion

Operational efficiency in operating theatres has gained increasing attention due to its direct impact on quality of care, patient safety and health care sustainability. However, the lack of a standardised definition of operational optimisation and the diversity of evaluation metrics limit comparisons between strategies implemented in surgical environments (Schouten et al 2023).

This review indicates that improving operational efficiency requires the combination of multiple approaches, including technological innovation, management methodologies and communication practices. Digital solutions such as AI-based prediction models, automated scheduling systems and workflow-management platforms have shown potential to reduce delays, optimise resource allocation and increase operating theatre utilisation (Bellini et al 2024, Onishi & Casanova 2024, Ramadan et al 2025, Vladu et al 2024). Similarly, automation systems and digital monitoring tools have contributed to improve workflow coordination and reducing operational waste (Chen et al 2024, Kravitz 2022, Ramadan et al 2025).

Alongside technological innovation, management methodologies such as Lean Six Sigma remain important strategies for improving operating theatre performance. These approaches have demonstrated consistent reductions in turnover time, improved utilisation rates and fewer delays in surgical start times (Michelin et al 2021, Mitchell et al 2025, Slagerman 2021). Efficient operating theatre preparation and coordinated multidisciplinary teamwork also play a crucial role in supporting surgical productivity (Rocha 2021).

Real-time monitoring technologies and digital communication platforms can further enhance coordination between surgical teams and improve patient flow management, helping to reduce communication failures that may compromise surgical safety (Chen et al 2024, Kane et al 2021).

Despite these advances, the findings of this review highlight that strategies are typically implemented and evaluated in isolation, targeting specific operational indicators rather than system-wide efficiency. This fragmented approach may limit the understanding of how different strategies interact within the complexity of perioperative workflows.

Variability in surgical duration estimation continues to affect scheduling accuracy and theatre utilisation, reinforcing the need for predictive models based on AI and machine learning (Espaillat 2024, Srinivas & Young 2023, Stucky et al 2024). Another challenge involves balancing surgical training with operational productivity, as efficiency pressures may limit learning opportunities for residents and trainees (Woelfel et al 2023).

Communication processes also play a critical role in both surgical safety and operational efficiency. Failures in team communication are recognised contributors to adverse events in operating theatres, and factors such as excessive noise may compromise team interaction and decision-making (Mcleod et al 2021). Digital communication platforms and real-time monitoring systems may therefore support better coordination among perioperative teams and improve patient flow. Although technological strategies show promising results, most studies still focus on operational indicators rather than clinical outcomes, patient experience or cost-effectiveness.

These findings reinforce the central role of perioperative nurses in coordinating workflow and managing the practical implementation of multiple efficiency strategies in real-world settings.

Digital transformation in health care, including AI and connected technologies, is expected to further influence perioperative management. However, interoperability, data governance and workforce training remain essential for sustainable implementation (Gazzarata et al 2024, Kelly et al 2020).

This review has limitations. Some studies could not be included because full-text access was unavailable, and language restrictions may have limited the identification of additional evidence. In addition, methodological quality assessment was not conducted, as recommended for scoping reviews.

Overall, improving operational efficiency in operating theatres requires a multifactorial approach combining technological innovation, structured management strategies and effective team communication. Investments in digital infrastructure, workforce training and data-driven decision-making may support more efficient surgical scheduling and safer perioperative care.

Recommendations for future research

Based on the gaps identified in this review, future research should prioritise several key areas. First, there is a need to develop and validate standardised metrics for assessing operational efficiency in operating theatres, enabling comparison across studies and settings.

Second, further research should move beyond isolated operational indicators to include clinical outcomes, patient-centred measures and economic evaluations, in order to better understand the broader impact of technological and organisational interventions.

Third, future studies should explore how different technological and process-based strategies can be applied and evaluated within real-world perioperative workflows, particularly considering their combined use in practice.

Fourth, there is a need to better understand the impact of these strategies on multidisciplinary team dynamics, particularly the role of nursing professionals in coordinating workflow and managing operational demands.

Finally, longitudinal studies are needed to assess the sustainability and scalability of these interventions across different health care contexts.

Conclusion

This scoping review identified a diverse range of technological and process-improvement strategies associated with improvements in specific operational efficiency indicators in operating theatres. Digital technologies, scheduling automation and Lean Six Sigma approaches were associated with reductions in turnover time, surgical delays and operating-room idle time. Future studies should further evaluate economic outcomes, patient-centred indicators and long-term sustainability of these interventions.