Next Article in Journal
Industry 5.0: Are We Going to Accept Robots as Co-Workers in Office Environments? An Empirical Analysis
Previous Article in Journal
Effect of OSEM Reconstruction Iteration Number and Monte Carlo Collimator Modeling on 166Ho Activity Quantification in SPECT/CT
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Traceability of Surgical Instruments: A Systematic Review

1
University of Franche-Comté, SINERGIES, F-25000 Besançon, France
2
Department of Pediatric Surgery, University of Franche-Comté, CHU Besançon, SINERGIES, F-25000 Besançon, France
3
Sterilization Functional Unit, Pharmaceutical Department, CHU Besançon, F-25000 Besançon, France
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2025, 15(3), 1592; https://doi.org/10.3390/app15031592
Submission received: 21 November 2024 / Revised: 24 January 2025 / Accepted: 28 January 2025 / Published: 5 February 2025
(This article belongs to the Section Electrical, Electronics and Communications Engineering)

Abstract

:
Objective: This study provides a comprehensive global overview of surgical instrument traceability systems and accentuates their growing importance in healthcare. Background: Surgical instruments pose risks to patient safety, economic costs, logistical challenges, and environmental impact. The increasing focus on instrument traceability reflects its potential to address these issues. Methods: We performed a systematic review using PRISMA guidelines, analyzing articles from 2000 to 2023 across five digital libraries (PubMed, Web of Science, IEEE, ACM, Google Scholar). Our review concentrated on traceability systems’ lifecycle for reusable and sterile surgical instruments. Results: Out of 7189 articles retrieved, 22 were selected for evaluation, and only 6 were considered relevant after a thorough examination. These studies mainly deployed Radio Frequency Identification (RFID) technology. They enhance patient safety, reduce environmental impact, improve economic efficiency, and optimize logistics. Additionally, these systems encourage more responsible surgical practices. Conclusions: Our study underscores the limited applied research in this field and discusses system architectures and performance metrics. It proposes future research directions, including the development of public databases, integration of automation, and investment in artificial intelligence (AI) and computer vision to improve traceability and risk analysis.

1. Introduction

According to the International Organization for Standardization (ISO), traceability consists of tracing a product’s history, application, use, location, and characteristics based on registered identification data (ISO, https://www.iso.org/obp/ui/#iso:std:iso:9000:ed-3:v1:en accessed on 30 January 2025). In the context of hospitals, traceability involves unambiguous identification of surgical instruments (surgical instruments, ranging from simple scalpels to sophisticated robotic systems, play a critical role in medical procedures [1]), including their “origin” (manufacturer) and “history of use.” The history of use includes sterilization and cleaning cycles, maintenance records, and usage data [2]. Figure 1 explores the key step in the lifecycle of surgical instrument use and sterilization.
The management of these numerous steps is marked by risks of errors involving multiple stakeholders from various departments within the hospital. Poor management of these steps can cause difficulties in identifying the root cause of issues such as nosocomial infections or incidents related to inadequate instrument maintenance (Figure 2). Implementing a surgical instrument traceability system is essential to address these challenges. The surgical instrument traceability system ensures each instrument’s complete and reliable history throughout its lifecycle. Identifying each device precisely is crucial to improving patient safety, maintaining instrument quality, and facilitating effective recalls in the event of identified defects.
Thanks to technological advancements, the traceability of surgical instruments has seen significant progress over the past decade, becoming a key focus in healthcare facilities [3]. Health authorities recognize its substantial benefits, particularly in patient safety, cost efficiency, logistics, and environmental sustainability [4].
To meet economic, health, logistical, and environmental challenges, scientists have contributed to developing traceability systems for surgical instruments, initially relying on collecting expert knowledge from health personnel and a large part of engineering knowledge. In this context, our study provides guidelines for researchers interested in developing traceability systems for surgical instruments. It focuses primarily on the instruments found in surgical trays. Specifically, we summarize and identify the existing approaches used for the traceability of surgical instruments, highlighting their benefits. Furthermore, we analyze the gaps in current research and propose future directions for advancement in this field.
The theme of traceability is applied in different fields, such as the agri-food industry [5,6,7], manufacturing [8], and the pharmaceutical industry [9]. To date, no study has conclusively offered an objective, complete, and critical view of surgical instrument traceability systems.
In the literature, the rationalization of surgical instruments has attracted the scientific community’s attention. Ahmadi et al. [10] presented a study on the management of stocks of surgical instruments and sterile instruments in hospitals. They deduced that exploiting advanced technologies such as barcodes and RFID facilitates data collection and is crucial in developing analytical methods. A qualitative systematic review conducted by Dekonenko et al. [11] focused on reducing surgical trays to generate savings, particularly in pediatric surgery. Their findings highlighted that moving away from disposable instruments and standardizing equipment reduces supply costs, with savings of up to 20% and a 40–70% removal of surgical instruments, without compromising time or safety in the operating room. Dos Santos et al. [12] reviewed approaches to rationalizing surgical instrument trays. They suggest that future work should focus on crucial aspects such as the traceability of surgical instruments and cross-sectional analysis of surgical tray contents. This perspective highlights promising research areas to optimize efficiency and resource management in surgery further. The literature result is summarized in Table 1.
To the best of the author’s knowledge, our systematic review is the first on the traceability of surgical instruments, providing an in-depth view of the systems linked to this traceability. Our study also provides guidelines for further research in this area. We organized our work around the following research questions:
  • What are the different levels of a traceability system?
  • What are the different techniques for identifying surgical instruments?
  • What are the benefits of a traceability system?
  • What are the recommendations for future traceability work?
The remainder of this paper is organized into six sections as follows. Section 2 details the typical architecture of the traceability system. In Section 3, we explain the methodology related to the bibliographic search. Section 4 and Section 5 cover the interpretation and the discussion of the relevant works to our review. Finally, Section 6 concludes the paper with perspectives for future work.

2. Traceability Surgical System Architecture Overview

We have examined several research studies relating to the traceability of surgical instruments. Generally, these systems have a typical architecture and share characteristics. The shared architecture includes instrument identification, coordinator, and services. These levels collaborate to collect and analyze data related to the traceability of surgical instruments. Figure 3 illustrates the components of each level and their interconnections. In this section, we describe the main components in each layer.

2.1. Layer 1

This layer aims to identify the instruments. The identification of surgical instruments is divided into two distinct parts. First of all, there is the unique identification of instruments. It is based on the use of several technologies (RFID, dots tag, micro-percussion, laser engraving) to assign a unique identifier to each instrument through (RFID tag, barcode, Datamatrix code, and specific visual characteristics) [13,14,15,16,17]. Then, each type of instrument registration is appropriate for a particular reading technology (RFID reader, barcode reader, and camera). Apart from RFID technology, registration is symbolized by 1D-2D barcodes, a datamatrix, and alphanumeric characters.
  • RFID: This wireless technology comprises an RFID tag, a reader, and an antenna [18]. It uses radio waves to transmit data from tagged objects to a reader, enabling automatic identification and real-time tracking [19]. This technology has advantages and disadvantages. Indeed, it does not disrupt workflow, which is crucial for maintaining the efficiency of medical procedures [18]. But RFID-tagged instruments may experience interference [20]. Also, RFID tags cannot be attached to all instruments, particularly those used in neurosurgery [21]. In addition, the integrated circuit chip of RFID tags is damaged after several washing cycles and sterilization at high temperatures, affecting the readability of crucial information [22]. Only a limited number of labeled instruments are identified simultaneously [23]. This can be restrictive in situations requiring the management of numerous surgical instruments.
  • Dots: are pre-printed adhesive dots with a unique DataMatrix code [24,25]. They can have different sizes, from 2 to 9.5 mm. The size versatility allows application on various instruments, including small ones such as microsurgery instruments. Additionally, the dots adhere strongly when exposed to heat during autoclave. However, these technologies may be subject to code alteration through deformation or fragmentation, which could affect the traceability process in the long term.
  • Micro-percussion: registration by micro-percussion consists of pressing the surface of surgical instruments. This mechanical process uses a fine tip that strikes the surface at high speed. Implementing micro-percussion marking requires several pieces of equipment, including a micro-percussion machine, a peripheral PC equipped with specialized software for registration management, and a controller responsible for encoding management [25]. Micro-percussion markings are less sensitive to corrosion but have poorer contrast [14].
  • Laser engraving: Laser marking is based on eliminating material through a laser beam directed toward the surface of the surgical instrument. Laser marks have excellent visibility but are quickly attacked by corrosion [14]. This technique also allows the registration of circular surface instruments.

2.2. Layer 2

This layer plays a crucial role in orchestrating information exchanges [26]. It acts as the system’s brain, facilitating the exchange of information between the different components of the traceability system. It ensures automated monitoring, precise recording, and dynamic data management associated with each instrument. It allows real-time tracking of surgical instruments, automatically records related events, and archives this information, including any modification or update, in a structured manner. The first step is to register each surgical instrument in the database. Each record includes relevant information such as the unique identifier (ID), specific instrument function, sterilization data, and, optionally, an image of the instrument for visual identification. Sophisticated algorithms are implemented with the centralized database for real-time monitoring, anomaly detection, and proactive problem management.

2.3. Layer 3

The third layer, the service, represents the bridge between the traceability system and end users. It ensures an optimal user experience by providing intuitive interface features for data visualization in an understandable-friendly manner and generating meaningful reports. Reports can include information on instrument usage, patient numbers, maintenance history, sterilization data, etc. It is closely linked to the data management layer to ensure transparent communication and real-time updates display. Several parameters can be displayed for effective decision-making:
  • The number of uses [21] indicates the total number of times an instrument has been used until a fault is observed. This parameter helps predict the lifespan of each instrument based on the number of uses.
  • Identification Accuracy [15]: Evaluates accuracy by reporting the system’s reliability in correctly identifying instruments.
  • The usage rate [21] and activity rate [27] calculate the ratio between the number of uses and the number of sterilizations of an instrument. This parameter makes it possible to understand the efficiency of the use of each instrument.
    u s a g e r a t e = n u m b e r o f u s e s n u m b e r o f s t e r i l i z a t i o n s
  • Usage Percentage [18]: Calculates the usage percentage of an instrument based on the total number of operations in which it has been recorded. This parameter is crucial in the process of rationalizing surgical platforms.
    U s a g e P e r c e n t a g e = n u m b e r o f o p e r a t i o n s i n c l u d i n g t h e i n s t r u m e n t s u s e d t o t a l o p e r a t i o n s × 100

3. Methodology

Our review process was carried out in accordance with PRISMA guidelines [28,29]. Figure 4 summarizes the flowchart of the research methodology.

3.1. Search Strategy

The main objective of our review is to provide a global view of traceability systems for reusable surgical instruments by offering readers a holistic understanding of the field. We defined the keywords alternatives to surgical instruments to carry out the article search process (Table 2). Then, the keywords are used as queries in the titles. We searched for scientific articles published between (2000 and 2023) in 5 digital libraries (Pubmed, Web of Science, IEEE, ACM, and Google Scholar) (Supplementary Materials). We adapted the query string to each search engine’s syntax.

3.2. Eligibility Criteria

We defined inclusion and exclusion criteria to ensure that the articles found provide a systematic understanding of the entire life cycle of a surgical instrument traceability system. The inclusion criteria are:
  • Relevance: We included articles that explicitly detail the various stages of the life cycle of surgical instrument traceability systems, including design, implementation, and evaluation.
  • Peer-reviewed sources: We prioritized articles published in peer-reviewed journals, conferences, or reputable academic sources to ensure quality and rigor.
  • Accessible Full Texts: We selected studies with full-text availability to enable thorough analysis and replication of findings.
The exclusion criterion is:
  • Lack of Specific Focus: We excluded studies in which surgical instrument traceability was not a central objective or in which study outcomes (such as patient safety, environmental impact, economic considerations, or logistical ergonomics) were ambiguous or poorly evaluated after real-time deployment.

3.3. Selection Process

Process selection is performed manually by both authors (M.F. and R.Y.). The titles and abstracts of articles written in English were screened according to the inclusion and exclusion criteria, and full texts of potentially eligible studies were obtained. Relevant articles were reviewed independently by the authors, and a full-text assessment of selected studies was conducted. Any discrepancies and biases were discussed and resolved by consensus. In total, we obtained 7189 articles from the five searched databases. Firstly, we conducted a preliminary analysis to sort the articles according to their relevance. We retained 22 articles for further evaluation. After a detailed analysis, only 6 articles were deemed relevant for our study.

4. Results

We have provided in Table 3 a detailed and quantitative summary of significant studies that met our inclusion criteria.
These significant studies, carried out between 2013 and 2023 in various countries such as Japan [22,27,30], Norway [15], and the United States, [18,31] cover a range of technological applications, from RFID [18,22,27,30,31] (high-frequency 13.5 MHz and ultrahigh-frequency 915 MHz) to computer vision [15]. They cover types of operations encompassing areas ranging from general surgery, ophthalmology, otolaryngology, and orthopedic surgery to more specific specialties such as pediatric cardiac surgery, neurosurgery, and plastic surgery [18,22,31]. The deployment periods also vary over particular periods (several years [22], months [31], or days [15]). Their nuanced scientific approaches offer benefits that combine patient safety, reduced environmental impact, economic rationalization, and improved ergonomics of logistics work. They also contribute to more efficient and responsible surgical practices. These benefits can be divided into short-term benefits (Patient Safety and Logistical Ergonomics) and medium- to long-term benefits (Economy and Environment).

4.1. Short-Term Benefits: Patient Safety and Logistical Ergonomics

4.1.1. Patient Safety

Traceability systems for surgical instruments significantly enhance patient safety by enabling precise tracking and monitoring of individual instruments. This reduces human error and ensures compliance with safety protocols. Surgical trays, containing up to 188 instruments per procedure, present substantial inefficiencies, as 78–87% of these instruments often go unused [18]. Large hospitals managing over 100,000 surgical trays and 2.6 million instruments annually [32] face amplified challenges in optimizing resources and improving patient safety. Addressing these inefficiencies through robust traceability systems can lead to safer and more efficient surgical environments.
  • At Shimane University Hospital in Japan (2013) [27,30], the implementation of an RFID system reduced the counting time for approximately 130 instruments by more than 50%, thereby minimizing the likelihood of errors caused by time pressure.
  • Similarly, Duke University Hospital (2022) [18] demonstrated high sensitivity (93.8%) and specificity (80.8%) in measuring surgical instrument usage, reducing risks associated with missing or defective tools.
  • Surgical instrument errors, such as forgotten instruments or use of unsterilized tools, can lead to severe outcomes, including post-operative infections or patient death [13,33,34]. According to Public Health France [35], nosocomial infections affect 1 in 18 patients, with an estimated 4200 deaths annually. Addressing these errors through traceability is critical to improving patient outcomes and strengthening health security.

4.1.2. Logistical Ergonomics

Enhanced traceability systems improve the ergonomic flow of surgical procedures by streamlining stock management and preparation processes.
  • At Davis Ambulatory Surgical Center (2021) [31], RFID technology reduced setup times from 23 min to 17 min, demonstrating the efficiency of real-time monitoring and automatic counting.
  • Shimane University Hospital (2013) [27,30] achieved better workflow by rationalizing instrument storage, reducing containers to 70 instruments, which simplified tool retrieval and minimized surgeon fatigue.

4.2. Medium-to-Long-Term Benefits: Economy and Environment

4.2.1. Economic Benefits

Optimizing resource use through traceability systems can significantly reduce healthcare costs by extending the lifespan of instruments and improving inventory management. This impact is crucial in the medium and long term, as surgical trays can hold up to 188 instruments per procedure [36].
  • At the Japanese Red Cross Wakayama Medical Center (2019) [22], traceability systems predicted instrument service life, enabling better resource planning and cost savings.
  • Duke University Hospital [18] reported that logistical improvements, such as reduced setup time, contributed to a more cost-effective workflow.

4.2.2. Environmental Benefits

Traceability systems promote environmental sustainability by reducing waste and energy consumption.
  • Rationalizing surgical tray contents ensures that only used instruments are sterilized, reducing unnecessary sterilization processes. For instance, the Davis Ambulatory Surgical Center (2021) [31] achieved a 40.3% reduction in tray size, leading to decreased sterilization needs and associated energy consumption.
  • Similarly, the Japanese Red Cross Wakayama Medical Center (2019) [22] reported sustainable waste management practices, where only necessary instruments were cleaned and reused, reducing overall waste.

5. Discussion

The traceability of surgical instruments is an evolving field aimed at ensuring patient safety and improving operational efficiency. This field impacts several critical sectors, including:
  • Health Security: By reducing the risk of surgical site infections through meticulous tracking and sterilization validation.
  • Sustainable Development: Promoting resource efficiency, reducing waste, and supporting eco-friendly practices in healthcare.
  • Professional Well-being: Enhancing ergonomics and reducing stress for healthcare professionals through streamlined workflows and error mitigation.
RFID technology has become the dominant solution in the field of surgical instrument traceability due to its ability to reliably identify tagged instruments. Studies demonstrate that RFID systems can reduce tray preparation times and improve consistency between automated and manual counting. However, RFID systems come with challenges, primarily the reliance on external tags, which can be lost, damaged, or contaminated during sterilization, potentially compromising the integrity of the system. As alternatives, emerging technologies, such as microscopic fingerprint imaging, provide promising solutions. These systems eliminate the need for external tags and can achieve accuracy rates above 99%. However, they require precise pattern recognition and can be influenced by factors such as instrument surface integrity, cleaning practices, and wear and tear, which can affect precision over time.
Each traceability technology has distinct strengths and limitations that must be considered when assessing its suitability for specific healthcare settings. RFID systems are cost-effective, scalable, and well-established, making them a viable choice for facilities looking to implement a proven solution. However, they necessitate regular maintenance of tags and readers. On the other hand, fingerprint imaging systems offer a tag-free solution, making them ideal for facilities seeking a more streamlined approach. Yet, their adoption may be hindered by the need for advanced infrastructure and staff training. RFID, while reliable, remains dependent on external tags that can fail or become contaminated. Fingerprint imaging, though innovative, has not yet been fully validated across diverse surgical environments, particularly in high-volume hospitals, where instrument cleaning and wear could affect performance.
As the field evolves, new technologies such as artificial intelligence (AI) and computer vision should be integrated into traceability systems. These technologies offer the potential to automate processes and enhance decision-making by enabling real-time identification and tracking of instruments. For example, artificial intelligence can be used to detect patterns, predict instrument wear, and optimize sterilization cycles, improving instrument management accuracy and efficiency. Additionally, blockchain technology is gaining traction for its ability to create immutable, transparent records of surgical instrument handling. This ensures accountability and compliance with stringent regulatory requirements while fostering collaboration and standardization across the healthcare industry.
The implementation of surgical instrument traceability systems has been shown to save an average of four minutes during logistical setup, leading to a more efficient workflow, reduced stress, fewer human errors, and a decrease in the number of instruments requiring sterilization. These improvements help minimize avoidable economic expenses and contribute to better operational efficiency. The global market for surgical instrument traceability systems is expected to grow significantly, from $294.77 million in 2023 to $810.65 million by 2031 (Verified Market Research, https://www.verifiedmarketresearch.com/product/surgical-instrument-tracking-system-market/ accessed on 30 January 2025). This growth highlights the increasing importance of investment and innovation in this field. With approximately 310 million major surgeries conducted annually worldwide—including 40 to 50 million in the United States and around 20 million in Europe [37]—enhancing surgical instrument traceability systems is crucial for ensuring patient safety and optimizing operational efficiency. While current technologies show promise, addressing their limitations and integrating them into broader hospital ecosystems will be key to maximizing their potential. Through continued innovation and research, the healthcare industry can establish new global standards, ensuring safer, more efficient, and sustainable surgical practices.

6. Conclusions

Individual traceability of surgical instruments represents an essential factor in the reprocessing of sterile and reusable medical instruments. The constant evolution of technologies, particularly with the development of miniature sensors and advanced computing, has projected this research theme towards new and exciting frontiers. The traceability system, by optimizing instrument management, has a significant positive impact on patient safety, the economy, the environment, and the ergonomics of healthcare personnel.
In the future, several areas of research deserve particular attention. These lines of research define a promising roadmap for the future of surgical instrument traceability systems, where technology, automation, AI, and proactive risk management combine to shape safer, more efficient medical practice over the long term.
  • Creation of public databases: The creation of public databases, rich in information on surgical instruments and details relating to maintenance and sterilization, has become necessary. This resource will serve as the basis for in-depth longitudinal studies, providing valuable information on the effectiveness and durability of the instruments.
  • Integration of automation into the traceability system: The future lies in the increased integration of automation to minimize human errors and improve ergonomics for healthcare workers. Automation of the assembly phase of the sterilization cycle, combined with automated instrument tracking and sorting, promises more efficient management. Considering factors such as priority of use and actuation scenarios is essential.
  • Investment in artificial intelligence and computer vision: Significant investment in artificial intelligence and computer vision is required for robust instrument identification with omnidirectional marking recognition. This technology also helps automatically detect faults, provide proactive maintenance, and generate daily reports.
  • Risk analysis in the traceability system: Risk analysis at all stages of the traceability system, assessing generic severity and consequences, is crucial. Defining reaction protocols adapted to each scenario will guarantee the robustness and performance of the system.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app15031592/s1.

Author Contributions

M.F. and R.Y. are the first and second authors who collected all the data, organized them, analyzed them, and wrote the original draft. F.A., H.P., O.H., F.P., G.H. and Y.C. suggested various edits to improve this paper. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by The Junior Professor Chair (CPJ) of Franche Comte University, Galaxie number 4718 ANR-23-CPJ1-0010-01.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

As this is a review paper, all of the data we used may be available in public research databases.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Bag, S. Overview of Surgical Instruments for the Operation Theatre. In Design and Development of Affordable Healthcare Technologies; IGI Global: Hershey, PA, USA, 2018; pp. 23–56. [Google Scholar]
  2. Vries, D. Aligning the Work Processes of the Medical Instrument Sterilization Cycle at the OLVG Hospital in Amsterdam: A Holistic Approach. Master’s Thesis, University of Twente, Enschede, The Netherlands, 2017. [Google Scholar]
  3. Zhu, X.; Yuan, L.; Li, T.; Cheng, P. Errors in packaging surgical instruments based on a surgical instrument tracking system: An observational study. BMC Health Serv. Res. 2019, 19, 176. [Google Scholar] [CrossRef] [PubMed]
  4. World Health Organization. WHO Global Model Regulatory Framework for Medical Devices Including In Vitro Diagnostic Medical Devices; World Health Organization: Geneva, Switzerland, 2017. [Google Scholar]
  5. Jaison, F.; Ramaiah, N.S. A survey on traceability in food safety system using blockchain. J. Discret. Math. Sci. Cryptogr. 2022, 25, 793–799. [Google Scholar] [CrossRef]
  6. Demestichas, K.; Peppes, N.; Alexakis, T.; Adamopoulou, E. Blockchain in agriculture traceability systems: A review. Appl. Sci. 2020, 10, 4113. [Google Scholar] [CrossRef]
  7. Costa, C.; Antonucci, F.; Pallottino, F.; Aguzzi, J.; Sarriá, D.; Menesatti, P. A review on agri-food supply chain traceability by means of RFID technology. Food Bioprocess Technol. 2013, 6, 353–366. [Google Scholar] [CrossRef]
  8. Schuitemaker, R.; Xu, X. Product traceability in manufacturing: A technical review. Procedia CIRP 2020, 93, 700–705. [Google Scholar] [CrossRef]
  9. Kumar, G. Pharmaceutical Drug Packaging and Traceability: A Comprehensive Review. Univers. J. Pharm. Pharmacol. 2023, 2, 19–25. [Google Scholar] [CrossRef]
  10. Ahmadi, E.; Masel, D.T.; Metcalf, A.Y.; Schuller, K. Inventory management of surgical supplies and sterile instruments in hospitals: A literature review. Health Syst. 2019, 8, 134–151. [Google Scholar] [CrossRef]
  11. Dekonenko, C.; Oyetunji, T.A.; Rentea, R.M. Surgical tray reduction for cost saving in pediatric surgical cases: A qualitative systematic review. J. Pediatr. Surg. 2020, 55, 2435–2441. [Google Scholar] [CrossRef]
  12. Dos Santos, B.M.; Fogliatto, F.S.; Zani, C.M.; Peres, F.A.P. Approaches to the rationalization of surgical instrument trays: Scoping review and research agenda. BMC Health Serv. Res. 2021, 21, 163. [Google Scholar] [CrossRef]
  13. Moatari-Kazerouni, A.; Bendavid, Y. Improving logistics processes of surgical instruments: Case of RFID technology. Bus. Process Manag. J. 2017, 23, 448–466. [Google Scholar] [CrossRef]
  14. Rioblanc, F.; Cambier, C.; Le Grand, J. Traçabilité individuelle à l’instrument: évolution des marquages laser et micropercussion au fil des cycles de stérilisation. In Proceedings of the Annales Pharmaceutiques Françaises; Elsevier: Paris, France, 2023. [Google Scholar]
  15. Ishiyama, R.; Frøiland, P.H.L.; Øvrebotn, S.A. Automated Identification of Surgical Instruments without Tagging: Implementation in Real Hospital Work Environment. In Proceedings of the 2023 18th International Conference on Machine Vision and Applications (MVA), Hamamatsu, Japan, 23–25 July 2023; pp. 1–4. [Google Scholar]
  16. Glaser, B.; Schellenberg, T.; Franke, S.; Dänzer, S.; Neumuth, T. Surgical instrument similarity metrics and tray analysis for multi-sensor instrument identification. In Proceedings of the Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling; SPIE: Bellingham, WA, USA, 2015; Volume 9415, pp. 534–541. [Google Scholar]
  17. Nicolaos, G.; Tournoud, M.; Hassani, Y.; Mignon, J.; Frémont, F.; Fabreguettes, A. Unique Device Identification of surgical instruments by DataMatrix 2D barcodes. In 2009/2010 GS1 Healthcare Reference Book; GS1: Brussels, Belgium, 2009. [Google Scholar]
  18. Hill, I.; Olivere, L.; Helmkamp, J.; Le, E.; Hill, W.; Wahlstedt, J.; Khoury, P.; Gloria, J.; Richard, M.J.; Rosenberger, L.H.; et al. Measuring intraoperative surgical instrument use with radio-frequency identification. JAMIA Open 2022, 5, ooac003. [Google Scholar] [CrossRef] [PubMed]
  19. Schwaitzberg, S. The emergence of radiofrequency identification tags: Applications in surgery. Surg. Endosc. Other Interv. Tech. 2006, 20, 1315–1319. [Google Scholar] [CrossRef] [PubMed]
  20. Kusuda, K.; Yamashita, K.; Ohnishi, A.; Tanaka, K.; Komino, M.; Honda, H.; Tanaka, S.; Okubo, T.; Tripette, J.; Ohta, Y. Management of surgical instruments with radio frequency identification tags: A 27-month in hospital trial. Int. J. Health Care Qual. Assur. 2016, 29, 236–247. [Google Scholar] [CrossRef] [PubMed]
  21. Yamashita, K.; Kusuda, K.; Ito, Y.; Komino, M.; Tanaka, K.; Kurokawa, S.; Ameya, M.; Eba, D.; Masamune, K.; Muragaki, Y.; et al. Evaluation of surgical instruments with radiofrequency identification tags in the operating room. Surg. Innov. 2018, 25, 374–379. [Google Scholar] [CrossRef]
  22. Yoshikawa, T.; Kimura, E.; Akama, E.; Nakao, H.; Yorozuya, T.; Ishihara, K. Prediction of the service life of surgical instruments from the surgical instrument management system log using radio frequency identification. BMC Health Serv. Res. 2019, 19, 695. [Google Scholar] [CrossRef]
  23. Hosaka, R.; Noji, R. Automatic identification for surgical instruments using UHF band passive RFID. In Proceedings of the EMBEC & NBC 2017: Joint Conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC), Tampere, Finland, 11-15 June 2017; Springer: Berlin/Heidelberg, Germany, 2018; pp. 1061–1064. [Google Scholar]
  24. Talon, D. Gestion des Risques dans une Stérilisation Centrale d’un Établissement Hospitalier: Apport de la Traçabilité à L’instrument. Ph.D. Thesis, Ecole Centrale Paris, Gif-sur-Yvette, France, 2011. [Google Scholar]
  25. Jouvien, A. Préparation de la Mise en Place D’une TraçAbilité Individuelle à L’instrument au CHU de Bordeaux. Master’s Thesis, Université de Bordeaux, Bordeaux, France, 2022. [Google Scholar]
  26. FAORO. Brigitte Traçabilité Individuelle des Instruments. 2011. Available online: https://www.sssh.ch/uploads/media/f0311_guide_F.pdf (accessed on 30 January 2025).
  27. Hanada, E.; Ohira, A.; Hayashi, M.; Sawa, T. Improving efficiency through analysis of data obtained from an RFID tag system for surgical instruments. In Proceedings of the 2015 IEEE 5th International Conference on Consumer Electronics-Berlin (ICCE-Berlin), Berlin, Germany, 6–9 September 2015; pp. 84–87. [Google Scholar]
  28. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Ann. Intern. Med. 2009, 151, 264–269. [Google Scholar] [CrossRef]
  29. Liberati, A.; Altman, D.G.; Tetzlaff, J.; Mulrow, C.; Gøtzsche, P.C.; Ioannidis, J.P.; Clarke, M.; Devereaux, P.J.; Kleijnen, J.; Moher, D. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Ann. Intern. Med. 2009, 151, W-65. [Google Scholar] [CrossRef]
  30. Sawa, T.; Komatsu, H. Shimane university hospital implements RFID technology to manage surgical instruments. In Proceedings of the 2013 7th International Symposium on Medical Information and Communication Technology (ISMICT), Tokyo, Japan, 6–8 March 2013; pp. 90–92. [Google Scholar]
  31. Olivere, L.A.; Hill, I.T.; Thomas, S.M.; Codd, P.J.; Rosenberger, L.H. Radiofrequency identification track for tray optimization: An instrument utilization pilot study in surgical oncology. J. Surg. Res. 2021, 264, 490–498. [Google Scholar] [CrossRef]
  32. Stockert, E.W.; Langerman, A. Assessing the magnitude and costs of intraoperative inefficiencies attributable to surgical instrument trays. J. Am. Coll. Surg. 2014, 219, 646–655. [Google Scholar] [CrossRef]
  33. Cheng, V.C.C.; Wong, S.C.Y.; Sridhar, S.; Chan, J.F.W.; Ng, M.L.M.; Lau, S.K.P.; Woo, P.C.Y.; Lo, E.C.M.; Chan, K.K.C.; Yuen, K.Y. Management of an incident of failed sterilization of surgical instruments in a dental clinic in Hong Kong. J. Formos. Med. Assoc. 2013, 112, 666–675. [Google Scholar] [CrossRef]
  34. Benamara, M. Traçabilité RFID à l’aide de Petites Antennes: Application au cas des Instruments Chirurgicaux: Étude et Validation d’une Solution Prototype. Ph.D. Thesis, Université Paris-Est, Créteil, Paris, 2017. [Google Scholar]
  35. SPF. Principaux Résultats de L’enquête Nationale de Prévalence 2022 des Infections Nosocomiales et des Traitements Anti-Infectieux En établissement de Santé. 2023. Available online: https://www.santepubliquefrance.fr/maladies-et-traumatismes/infections-associees-aux-soins-et-resistance-aux-antibiotiques/infections-associees-aux-soins/documents/enquetes-etudes/principaux-resultats-de-l-enquete-nationale-de-prevalence-2022-des-infections-nosocomiales-et-des-traitements-anti-infectieux-en-etablissement-de-s (accessed on 23 July 2024).
  36. Mhlaba, J.M.; Stockert, E.W.; Coronel, M.; Langerman, A.J. Surgical instrumentation: The true cost of instrument trays and a potential strategy for optimization. J. Hosp. Adm. 2015, 4, 82–88. [Google Scholar] [CrossRef]
  37. Dobson, G.P. Trauma of major surgery: A global problem that is not going away. Int. J. Surg. 2020, 81, 47–54. [Google Scholar] [CrossRef] [PubMed]
Figure 1. The lifecycle of surgical instrument use.
Figure 1. The lifecycle of surgical instrument use.
Applsci 15 01592 g001
Figure 2. The most common issues related to surgical instruments.
Figure 2. The most common issues related to surgical instruments.
Applsci 15 01592 g002
Figure 3. Architecture of a surgical instrument traceability system.
Figure 3. Architecture of a surgical instrument traceability system.
Applsci 15 01592 g003
Figure 4. Flowchart of the research methodology.
Figure 4. Flowchart of the research methodology.
Applsci 15 01592 g004
Table 1. Summary of related work.
Table 1. Summary of related work.
PaperYearType of Research PaperContentSummary of Results
Ahmadi et al. [10]2019Literature reviewEconomic(1) Economic Order Quantity, Simple rules, Constraint programming, Integer programming, Markov chain, Simulation and Semi-Markov process are the current methods and strategies used in the management of surgical supplies and sterile instruments inventory to achieve savings in operating rooms.
(2) Healthcare professionals highlight improving preference cards and quantifying usage/waste as key practices for reducing operating room expenses.
Dekonenko et al. [11]2020Qualitative systematic reviewEconomic(1) Doctor preference cards and individual feedback are the techniques deployed for standardization and cost effectiveness on pediatric surgical.
Dos Santos et al. [12]2021Scoping reviewEconomic(1) The majority of authors and publications discussing surgical tray rationalization (STR) originate from the United States.
(2) The primary methodologies and strategies mentioned for STR include checklists, focus groups, observation, and standardization.
(3) STR positively influences operational and economic performance, with its main impact observed in operating rooms and the sterilization process.
(4) Future research could focus on two promising areas: instrument traceability and cross-sectional analysis.
Ours Literature reviewEngineering(1) A traceability system operates across three distinct levels.
(2) Surgical instrument identification methods include unique instrument identification and general identification.
(3) The advantages of a traceability system are evident in enhanced patient safety, environmental improvements, economic benefits, and better logistical ergonomics in the workplace.
(4) Future research should prioritize developing public datasets, incorporating automation into traceability systems, utilizing artificial intelligence and computer vision techniques, and conducting risk analysis studies.
Table 2. The queries deployed in our study.
Table 2. The queries deployed in our study.
Query (Title)“surgical instrument” OR “surgical instruments” OR “surgical tool”
OR “surgical tools” OR “operating instruments” OR “operating instrument”
OR “operating tools” OR “operating tool” OR “surgical trays” OR “surgical tray”
Table 3. Summary table of the surgical instrument traceability system.
Table 3. Summary table of the surgical instrument traceability system.
PaperHanada et al. [27],
and Sawa et al. [30]
Yoshikawa et al. [22]Oliver et al. [31]Hill et al. [18]Ishiyama et al. [15]
Year20132019202120222023
CountryJapanJapanUSAUSANorway
Technology usedRFID (13.56 MHz)RFID (13.56 MHz)RFIDRFID (915 MHz)Microscopic image of fingerprint
Location deployementShimane University HospitalJapanese Red Cross Wakayama Medical CenterDavis Ambulatory Surgical CenterDuke University HospitalHaukeland University Hospita
Types of Operation-General surgery, ophthalmology,
otolaryngology, orthopedic surgery,
gynecology, cardiovascular surgery,
pediatric cardiac surgery, urology,
neurosurgery, thoracic surgery,
plastic surgery, pediatric surgery,
breast surgery, emergency department,
and dental and oral surgery
Lumpectomy and excisional
breast biopsies
Craniotomies, CMC
arthroplasties, and breast surgeries
-
Period-1 September 2013 to 30 April20172019 October to 2020 March-February to June 2022 for 160 h
Aim of studyInceases the safety of
surgical procedure
Predict the precise service of instrumentsDemonstrate the use of RFID
technology as a data-driven
method for instrument reduction
Develop and evaluate an
automated system for measuring
surgical instrument use
Present new solution to track
and trace surgical instruments
without tagging
Results(1) Reduction of counting time from 7 to 5 min for approximately 130 instruments.
(2) 50% reduction in container assembly time for general laparotomy (from 20 to 10 min).
(3) Rationalization of containers by reducing the storage of more than 70 instruments.
(1) Not all sterilized instruments were used during the operation.
(2) The probability of failure exceeded 80% when the number of uses exceeded 224 times.
(1) 40.3% reduction in tray size.
(2) Reduced setup time from 23 min to 17 min.
(3) Agreement between automatic and manual counting with a kappa value of 0.824.
(4) No instruments were added to the reduced trays in 10 additional cases.
(1) Sensitivity of 93.8% and specificity of 80.8%.
(2) Consistency between the RFID system and human ethnography with a Cohen’s kappa coefficient of 0.81.
(3) Average reduction of 50.8% in surgical plateaus in breast and orthopedic surgery.
(4) Logistical reduction of 6 min in preparation for breast surgery.
(1) Accuracy >99% in unique identification.
(2) Reduction of scanning time to approximately 1.5 to 2 min for 12 to 13 instruments.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fayad, M.; Yahiaoui, R.; Auber, F.; Pidoux, H.; Hild, O.; Picaud, F.; Herlem, G.; Chaussy, Y. Traceability of Surgical Instruments: A Systematic Review. Appl. Sci. 2025, 15, 1592. https://doi.org/10.3390/app15031592

AMA Style

Fayad M, Yahiaoui R, Auber F, Pidoux H, Hild O, Picaud F, Herlem G, Chaussy Y. Traceability of Surgical Instruments: A Systematic Review. Applied Sciences. 2025; 15(3):1592. https://doi.org/10.3390/app15031592

Chicago/Turabian Style

Fayad, Moustafa, Réda Yahiaoui, Frédéric Auber, Hervé Pidoux, Olivier Hild, Fabien Picaud, Guillaume Herlem, and Yann Chaussy. 2025. "Traceability of Surgical Instruments: A Systematic Review" Applied Sciences 15, no. 3: 1592. https://doi.org/10.3390/app15031592

APA Style

Fayad, M., Yahiaoui, R., Auber, F., Pidoux, H., Hild, O., Picaud, F., Herlem, G., & Chaussy, Y. (2025). Traceability of Surgical Instruments: A Systematic Review. Applied Sciences, 15(3), 1592. https://doi.org/10.3390/app15031592

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop