IoT-Enabled Smart Operating Rooms for Enhancing Surgical Efficiency
DOI:
https://doi.org/10.52783/jns.v13.1431Keywords:
IoT in Healthcare, Smart Operating Rooms, Surgical Efficiency, Real-Time Data Analysis, Automation in Surgery, Patient SafetyAbstract
The internet of things (IoT) is revolutionizing the healthcare enterprise, mainly in the enhancement of surgical environments through the development of IoT-enabled clever working rooms. these progressive systems combine a network of sensors, devices, and software solutions to optimize surgical workflows, enhance patient effects, and minimize human errors. The core of this change lies in the capability to gather and examine actual-time records, facilitating on the spot and knowledgeable choice-making for the duration of surgical methods. This paper explores the deployment of IoT technologies in running rooms and their impact on surgical efficiency and safety. We talk the integration of diverse IoT gadgets, such as computerized surgical tools, environmental sensors, and wearable devices for each patients and surgical body of workers. those factors work collectively to create a cohesive environment that complements the operational factors of surgery, which include instrument readiness, sterilization methods, and the monitoring of patient vitals and surgical progress. furthermore, we deal with the demanding situations and answers related to records security and privateness, that are paramount whilst managing sensitive health facts in actual-time. Implementation strategies that encompass technical, ethical, and regulatory issues are evaluated to make certain that these advanced systems can be appropriately and effectively integrated into cutting-edge healthcare practices. The capability of IoT-enabled clever running rooms to transform surgical practices is substantial. more desirable statistics-pushed insights and the automation of routine tasks free up scientific professionals to focus more on crucial surgical decisions and patient care, hence elevating the general performance and effectiveness of surgical interventions.
Downloads
Metrics
References
Zaha, D.C.; Jurca, M.C.; Daina, C.; Babeș, V.V.; Petcheși, C.D.; Jurca, A.D.; Vesa, C.; Codreanu, I.C.; Babeș, E.E. Current data about the aetiology and treatment of infective endocarditis. Farmacia 2022, 70, 837–849.
Hodoșan, V.; Daina, C.M.; Zaha, D.C.; Cotrău, P.; Vladu, A.; Pantiș, C.; Dorobanțu, F.R.; Negrău, M.; Maghiar, A.; Daina, L.G. Pattern of Antibiotic Use in the Perinatal Period in a Public University Hospital in Romania. Medicina 2022, 58, 772.
Ong, B.S.; Thomas, R.; Jenkins, S. Introducing the “Twilight” operating room concept: A feasibility study to improve operating room utilization. Patient Saf. Surg. 2022, 16, 23.
Meneveau, M.O.; Mehaffey, J.H.; Turrentine, F.E.; Shilling, A.M.; Showalter, S.L.; Schroen, A.T. Patient and personnel factors affect operating room start times. Surgery 2020, 167, 390–395.
Aljaffary, A.; AlAnsari, F.; Alatassi, A.; AlSuhaibani, M.; Alomran, A. Assessing the Precision of Surgery Duration Estimation: A Retrospective Study. J. Multidiscip. Healthc. 2023, 16, 1565–1576.
Spenkelink, I.M.; Heidkamp, J.; Futterer, J.J.; Rovers, M.M. Image-Guided Procedures in the Hybrid Operating Room: A Systematic Scoping Review. PLoS ONE 2022, 17, e0266341.
Fernandez, C.C.; Ruiz, M.G. Telesurgery and Telementoring. Cir. Esp. (Engl. Ed.) 2024, 102, S23–S29.
Nensi, A.; Palter, V.; Reed, C.; Schulthess, P.; McLoone, M.; Grantcharov, T.; Shore, E.M. Utilizing the Operating Room Black Box to Characterize Intraoperative Delays, Distractions, and Threats in the Gynecology Operating Room: A Pilot Study. Cureus 2021, 13, e16218.
Jung, J.J.; Juni, P.; Lebovic, G.; Grantcharov, T. First-Year Analysis of the Operating Room Black Box Study. Ann. Surg. 2020, 271, 122–127.
van Dalen, A.S.H.M.; Strandbygaard, J.; van Herzeele, I.; Boet, S.; Grantcharov, T.P.; Schijven, M.P. Six Sigma in Surgery: How to Create a Safer Culture in the Operating Theatre Using Innovative Technology. Br. J. Anaesth. 2021, 127, 817–820.
Levin, M.; McKechnie, T.; Kruse, C.C.; Aldrich, K.; Grantcharov, T.P.; Langerman, A. Surgical Data Recording in the Operating Room: A Systematic Review of Modalities and Metrics. Br. J. Surg. 2021, 108, 613–621.
Al Abbas, A.I.; Sankaranarayanan, G.; Polanco, P.M.; Cadeddu, J.A.; Daniel, W.; Palter, V.; Grantcharov, T.; Bartolome, S.; Dandekar, P.; Evans, K.; et al. The Operating Room Black Box: Understanding Adherence to Surgical Checklists. Ann. Surg. 2022, 276, 995–1001.
Riley, M.S.; Etheridge, J.; Palter, V.; Zeh, H., 3rd; Grantcharov, T.; Kaelberer, Z.; Sonnay, Y.; Smink, D.S.; Brindle, M.E.; Molina, G. Remote Assessment of Real-World Surgical Safety Checklist Performance Using the or Black Box: A Multi-Institutional Evaluation. J. Am. Coll. Surg. 2024, 238, 206–215.
van Dalen, A.S.H.M.; Jansen, M.; van Haperen, M.; van Dieren, S.; Buskens, C.J.; van Dijkum, E.J.M.N.; Bemelman, W.A.; Grantcharov, T.P.; Schijven, M.P. Implementing Structured Team Debriefing Using a Black Box in the Operating Room: Surveying Team Satisfaction. Surg. Endosc. 2021, 35, 1406–1419.
Doyen, B.; Gordon, L.; Soenens, G.; Bacher, K.; Vlerick, P.; Vermassen, F.; Grantcharov, T.; Van Herzeele, I. Introduction of a Surgical Black Box System in a Hybrid Angiosuite: Challenges and Opportunities. Phys. Med. 2020, 76, 77–84.
Doyen, B.; Soenens, G.; Maurel, B.; Hertault, A.; Gordon, L.; Vlerick, P.; Vermassen, F.; Grantcharov, T.; van Herzeele, I. Assessing Endovascular Team Performances in a Hybrid Room Using the Black Box System: A Prospective Cohort Study. J. Cardiovasc. Surg. 2023, 64, 82–92.
Lin, C.C.; Chen, Y.P.; Chiang, C.C.; Chang, M.C.; Lee, O.K. Real-Time Streaming of Surgery Performance and Intraoperative Imaging Data in the Hybrid Operating Room: Development and Usability Study. JMIR Med. Inform. 2020, 8, e18094.
Zhang, W.; Zhu, W.; Yang, J.; Xiang, N.; Zeng, N.; Hu, H.; Jia, F.; Fang, C. Augmented Reality Navigation for Stereoscopic Laparoscopic Anatomical Hepatectomy of Primary Liver Cancer: Preliminary Experience. Front. Oncol. 2021, 11, 663236.
Zhu, W.; Zeng, X.; Hu, H.; Xiang, N.; Zeng, N.; Wen, S.; Tian, J.; Yang, J.; Fang, C. Perioperative and Disease-Free Survival Outcomes after Hepatectomy for Centrally Located Hepatocellular Carcinoma Guided by Augmented Reality and Indocyanine Green Fluorescence Imaging: A Single-Center Experience. J. Am. Coll. Surg. 2023, 236, 328–337.
Hakoda, H.; Akamatsu, N.; Shibata, E.; Takao, H.; Ichida, A.; Kawaguchi, Y.; Kaneko, J.; Abe, O.; Hasegawa, K. Interventional Treatment for Portal Vein Complications Utilizing a Hybrid Operating Room after Liver Transplantation. HPB 2023, 25, 589–592.
Ishikawa, S.; Kuroda, S.; Chosa, K.; Okada, K.; Tanimine, N.; Tahara, H.; Ohira, M.; Ide, K.; Kobayashi, T.; Ohdan, H. Treatment of Multiple Huge Liver Cysts in a Hybrid Operating Room: A Case Report. Surg. Case Rep. 2021, 7, 232.
Nemade, B., & Shah, D. (2023). An IoT-Based Efficient Water Quality Prediction System for Aquaponics Farming. In Computational Intelligence: Select Proceedings of InCITe 2022 (pp. 311-323). Singapore: Springer Nature Singapore.
Bhola, A., & Gulhane, M. (2024). Revolutionizing Pneumonia Diagnosis and Prediction Through Deep Neural Networks. Optimized Predictive Models in Healthcare Using Machine Learning, 135-149.
Nemade, B., & Shah, D. (2022). An efficient IoT based prediction system for classification of water using novel adaptive incremental learning framework. Journal of King Saud University-Computer and Information Sciences, 34(8), 5121-5131.
M. Kumar, R. Sirohi, P. Kushwaha, M. Gulhane, M. Singh and K. Kumar, "Predicting Personality Traits of Introverts and Extroverts for Forensic Applications," 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE), Gautam Buddha Nagar, India, 2024, pp. 252-257, doi: 10.1109/IC3SE62002.2024.10593431.
M. Kumar, R. Sirohi, D. Kaushik, M. Gulhane, N. Khare and S. Vats, "Identifying Early Signs of Bipolar Disorder Risk by Food Habit Analysis in Forensic Using Machine Learning," 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE), Gautam Buddha Nagar, India, 2024, pp. 1-5, doi: 10.1109/IC3SE62002.2024.10593552.
J Satpathy, Navaneeta Rath . (2020). Voyage into Neuro – Absenteeism. International Journal on Research and Development - A Management Review, 9(2), 18 - 31.
D.Ravichandran, Ramesh Nimmatoori, Ashwin Dhivakar MR. (2016). A study on Image Statistics and Image Features on Coding Performance of Medical Images. International Journal on Advanced Computer Engineering and Communication Technology, 5(1), 1 - 6.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
