Research Article
BibTex RIS Cite

Evaluation of Services in MRI Department of University Hospital with Discrete Event Simulation Technique: A Case Study

Year 2025, Volume: 10 Issue: 1, 40 - 51, 30.04.2025

Abstract

With the advancement of technology, radiological imaging examinations are vital in clinical diagnosis and treatment processes. Patients with chronic conditions often require diagnostic imaging procedures such as MRI, X-ray, CT scans and Ultrasound. Timely access to these services is critical, especially in situations requiring urgent medical attention. Assessing and improving the performance of radiology departments is critical to optimize patient care. Simulation techniques, especially discrete event simulation, have emerged as an effective tool for optimizing workflow, resource allocation and patient flow in MR departments. This study aims to contribute to strategic planning and operational decision processes in radiology departments to ensure more efficient use of resources. Using Arena Simulation, recommendations for efficient use of resources and balancing patient flows were developed and modeled. The main bottlenecks identified in the current situation analysis require strategic measures to be taken to improve the efficiency of MR service processes. The recommended steps, such as procurement of new MR equipment and staffing, are critical to meet the increasing demand for services in the future. As a result, this study provides concrete recommendations to increase the effectiveness of MR service processes of the university hospital and serves as a guide to improve operational performance.

References

  • Atalan, A., Dönmez, C. Ç., & Atalan, Y. A. (2018). Yüksek-eğitimli uzman hemşire istihdamı ile acil servis kalitesinin yükseltilmesi için simülasyon uygulaması: Türkiye sağlık sistemi. Marmara Fen Bilimleri Dergisi, 30(4), 318-338. https://doi.org/10.7240/marufbd.395255
  • Bahadori, M., Teymourzadeh, E., Hosseini, S. H., & Ravangard, R. (2017). Optimizing the performance of magnetic resonance imaging department using queuing theory and simulation. Shiraz E Medical Journal, 18(1 https://doi.org/10.17795/semj43958
  • Cihangir, E., Keskin, F. D., Çiçekli, U. G., & Yakan, G. (2021). Bir Üretim İşletmesinde Simülasyon Yöntemi ile Darboğaz Analizi ve Sistem İyileştirmesi. Avrupa Bilim ve Teknoloji Dergisi, (28), 917-923. https://doi.org/10.31590/ejosat.1012214
  • Duguay, C., & Chetouane, F. (2007). Modeling and improving emergency department systems using discrete event simulation. Simulation, 83(4), 311-320. https://doi.org/10.1177/00375497070831
  • Durmuş, A., & Özdemir, A. (2023). Yoğun bakim ünitelerinde hasta akişinin değerlendirmesi: 3. Basamak hastaneler için simülasyon modellemesi. Hacettepe Sağlık İdaresi Dergisi, 26(4), 1009-1032. https://doi.org/10.61859/hacettepesid.1314024
  • Durmuş, A. Yoğun bakim ünitelerinde kapasite yönetimi: ara servis oluşturma ve bir uygulama. SDÜ Sağlık Yönetimi Dergisi, 6(2), 181-197.
  • European Society of Radiology (ESR). The future role of radiology in healthcare. Insights Imaging. 2010; 1 (1): 2-11.
  • Idigo, F. U., Agwu, K. K., Onwujekwe, O. E., Okeji, M. C., & Anakwue, A. M. C. (2021). Improving patient flows: a case study of a tertiary hospital radiology department. International Journal of Healthcare Management, 14(1), 153-161. https://doi.org/10.1080/20479700.2019.1620476
  • Fernández-Gutiérrez, F., Wolska-Krawczyk, M., Buecker, A., Houston, J. G., & Melzer, A. (2017). Workflow optimisation for multimodal imaging procedures: a case of combined X-ray and MRI-guided TACE. Minimally Invasive Therapy & Allied Technologies, 26(1), 31-38. https://doi.org/10.1080/13645706.2016.1217887
  • Ghanes, K., Jouini, O., Jemai, Z., Wargon, M., Hellmann, R., Thomas, V., & Koole, G. (2014, December). A comprehensive simulation modeling of an emergency department: A case study for simulation optimization of staffing levels. In Proceedings of the Winter Simulation Conference 2014 (pp. 1421-1432). IEEE. https://doi.org/10.1109/WSC.2014.7019996
  • Gong, T., Wang, Y., Pu, H., Yin, L., & Zhou, M. (2022). Study on the application effect of the case teaching method based on primary teaching principle in Clinical Teaching of Radiology. Computational Intelligence and Neuroscience, 2022(1), 3448182. https://doi.org/10.1155/2022/6808648
  • Granja, C., Almada-Lobo, B., Janela, F., Seabra, J., & Mendes, A. (2014). An optimization based on simulation approach to the patient admission scheduling problem: diagnostic imaging department case study. Journal of digital imaging, 27, 33-40. https://doi.org/10.1016/j.jbi.2014.08.007
  • Günal, M. M., & Pidd, M. (2010). Discrete event simulation for performance modelling in health care: a review of the literature. Journal of Simulation, 4(1), 42-51. https://doi.org/10.1057/jos.2009.25
  • Hoot, N. R., LeBlanc, L. J., Jones, I., Levin, S. R., Zhou, C., Gadd, C. S., & Aronsky, D. (2008). Forecasting emergency department crowding: a discrete event simulation. Annals of emergency medicine, 52(2), 116-125. https://doi.org/10.1016/j.annemergmed.2007.12.011
  • Idigo, F., Idigo, V., Agwu, K., Onwujekwe, O., Okeji, M., Anakwue, A. M., & Nwogu, U. (2020). Workflow estimation of a radiology department using modelling and simulation. International Journal of Advanced Operations Management, 12(2), 122-141. https://doi.org/10.1504/IJAOM.2020.108261
  • Johnston, M. J., Samaranayake, P., Dadich, A., & Fitzgerald, J. A. (2009, July). Modelling radiology department operation using discrete event simulation. In MODSIM, International Congress on Modelling and Simulation (pp. 678-684).
  • Jun, J. B., Jacobson, S. H., & Swisher, J. R. (1999). Application of discrete-event simulation in health care clinics: A survey. Journal of the operational research society, 50(2), 109-123. https://doi.org/10.1057/palgrave.jors.2600669
  • Karnon, J., Stahl, J., Brennan, A., Caro, J. J., Mar, J., & Möller, J. (2012). Modeling using discrete event simulation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force–4. Medical decision making, 32(5), 701-711. https://doi.org/10.1177/0272989X12455462
  • Koçyiğit, H., & Yıldırım, G. (2022). Türkiye’de hemşirelikte klinik uygulama alanında uzmanlaşmada ilk: Nazmiye Kocaman Yıldırım. Mersin Üniversitesi Tıp Fakültesi Lokman Hekim Tıp Tarihi ve Folklorik Tıp Dergisi, 12(2), 228-237. https://doi.org/10.31020/mutftd.999252
  • Landa, P., Tànfani, E., & Testi, A. (2013, July). Simulation and optimization for bed re-organization at a surgery department. In Special Session on Health Applications (Vol. 2, pp. 584-594). SCITEPRESS. https://doi.org/10.5220/0004635805840594
  • Luo, L., Zhang, Y., Qing, F., Ding, H., Shi, Y., & Guo, H. (2018). A discrete event simulation approach for reserving capacity for emergency patients in the radiology department. BMC health services research, 18, 1-11. https://doi.org/10.1186/s12913-018-3282-8
  • Marshall, D. A., Burgos-Liz, L., IJzerman, M. J., Osgood, N. D., Padula, W. V., Higashi, M. K., ... & Crown, W. (2015). Applying dynamic simulation modeling methods in health care delivery research—the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force. Value in health, 18(1), 5-16. https://doi.org/10.1016/j.jval.2014.12.001
  • Moretto, N., Comans, T. A., Chang, A. T., O’Leary, S. P., Osborne, S., Carter, H. E., ... & Raymer, M. (2019). Implementation of simulation modelling to improve service planning in specialist orthopaedic and neurosurgical outpatient services. Implementation Science, 14, 1-11. https://doi.org/10.1186/s13012-019-0923-1
  • Muroff, L. R. (2004). Implementing an effective organization and governance structure for a radiology practice. Journal of the American College of Radiology, 1(1), 26-32. https://doi.org/10.1016/S1546-1440(03)00015-2
  • Nickel, S., & Schmidt, U. A. (2009). Process improvement in hospitals: a case study in a radiology department. Quality Management in Healthcare, 18(4), 326-338. https://doi.org/10.1097/QMH.0b013e3181bee127
  • Oh, H. C., Toh, H. G., & Giap Cheong, E. S. (2011). Realization of process improvement at a diagnostic radiology department with aid of simulation modeling. Journal for Healthcare Quality, 33(6), 40-47. https://doi.org/10.1111/j.1945-1474.2011.00133.x
  • Ondategui-Parra, S., Gill, I. E., Bhagwat, J. G., Intrieri, L. A., Gogate, A., Zou, K. H., ... & Ros, P. R. (2004). Clinical operations management in radiology. Journal of the American College of Radiology, 1(9), 632-640. https://doi.org/10.1016/j.jacr.2004.04.015
  • Durmuş, A., Özdemir, A., & Gökmen, N. (2023). Yoğun bakim ünitelerinde kapasite değerlendirmesi ve planlamasi: 3. Basamak hastaneler için simülasyon modellemesi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(2), 599-620.. https://doi.org/10.16953/deusosbil.1254173
  • Pendharkar, S. R., Bischak, D. P., Rogers, P., Flemons, W., & Noseworthy, T. W. (2015). Using patient flow simulation to improve access at a multidisciplinary sleep centre. Journal of sleep research, 24(3), 320-327. https://doi.org/10.1111/jsr.12257
  • Pongjetanapong, K., Walker, C., O'Sullivan, M., Lovell‐Smith, M., & Furian, N. (2019). Exploring trade‐offs between staffing levels and turnaround time in a pathology laboratory using discrete event simulation. The International Journal of Health Planning and Management, 34(2), e1119-e1134. https://doi.org/10.1002/hpm.2748
  • Raunak, M., Osterweil, L., Wise, A., Clarke, L., & Henneman, P. (2009, May). Simulating patient flow through an emergency department using process-driven discrete event simulation. In 2009 ICSE Workshop on Software Engineering in Health Care (pp. 73-83). IEEE. https://doi.org/10.1109/SEHC.2009.5069608
  • Salleh, S., Thokala, P., Brennan, A., Hughes, R., & Dixon, S. (2017). Discrete event simulation-based resource modelling in health technology assessment. Pharmacoeconomics, 35, 989-1006. https://doi.org/10.1007/s40273-017-0533-1
  • Shakoor, M. (2015). Using discrete event simulation approach to reduce waiting times in computed tomography radiology department. Int Scholarly Sci Res Innovat, 9, 177-81. https://doi.org/10.5281/zenodo.1338044
  • Shakoor, M., Al-Nasra, M., Abu Jadayil, W., Jaber, N., & Abu Jadayil, S. (2017). Evaluation of provided services at MRI department in a public hospital using discrete event simulation technique: A case study. Cogent Engineering, 4(1), 1403539. https://doi.org/10.1080/23311916.2017.1403539
  • Singla, S. (2020). Demand and capacity modelling in healthcare using discrete event simulation. Open Journal of Modelling and Simulation, 8(04), 88. https://doi.org/10.4236/ojmsi.2020.84007
  • Su, S., & Shih, C. L. (2003). Managing a mixed-registration-type appointment system in outpatient clinics. International journal of medical informatics, 70(1), 31-40. https://doi.org/10.1016/S1386-5056(03)00008-X
  • Sun, Y. C., Wu, H. M., Guo, W. Y., Ou, Y. Y., Yao, M. J., & Lee, L. H. (2023). Simulation and evaluation of increased imaging service capacity at the MRI department using reduced coil-setting times. Plos one, 18(7), e0288546. https://doi.org/10.1371/journal.pone.0288546
  • Suthihono, Y. A., & Kusumastuti, R. D. (2021, August). A simulation of patient queuing system on MRI system at tertiary referral hospital in Indonesia. In 2021 6th International Conference on Management in Emerging Markets (ICMEM) (pp. 1-6). IEEE. https://doi.org/10.1109/ICMEM53145.2021.9869416
  • Teichgräber, U. K. M., Gillessen, C., & Neumann, F. (2003, December). Methoden des Prozessmanagements in der Radiologie. In RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Vol. 175, No. 12, pp. 1627-1633). © Georg Thieme Verlag Stuttgart· New York. https://doi.org/10.1055/s-2003-45331
  • Torabigoudarzi, H. Modeling and simulation of emergency radiology unit at St. Paul’s Hospital (T). (Yüksek Lisans Tezi), British Columbia: University of British Columbia.2019.
  • Uncu, N. (2017). Isınma Periyodu Belirleme Yöntemlerinin Etkinliklerinin Analizi. Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 32(4), 201-210. https://doi.org/10.21605/cukurovaummfd.383428
  • Vázquez-Serrano, J. I., Peimbert-García, R. E., & Cárdenas-Barrón, L. E. (2021). Discrete-event simulation modeling in healthcare: a comprehensive review. International journal of environmental research and public health, 18(22), 12262. https://doi.org/10.3390/ijerph182212262
  • Vieira, B., Demirtas, D., B van de Kamer, J., Hans, E. W., & van Harten, W. (2019). Improving workflow control in radiotherapy using discrete-event simulation. BMC medical informatics and decision making, 19, 1-13. https://doi.org/10.1186/s12911-019-0910-0
  • Woodall, J. C., Gosselin, T., Boswell, A., Murr, M., & Denton, B. T. (2013). Improving patient access to chemotherapy treatment at Duke Cancer Institute. Interfaces, 43(5), 449-461. https://doi.org/10.1287/inte.2013.0695
  • Yıldırım, M. S., Gökkuş, Ü., & Karasahin, M. (2021). Ayrılmış Demiryolu Hatlarında Mekik Trenler İçin Mikro-Simülasyon Tabanlı Taşımacılık Kapasitesi Analizi. Demiryolu Mühendisliği, (14), 202-216. https://doi.org/10.47072/demiryolu.935335
  • Younes, H. L., & Simmons, R. G. (2002). Probabilistic verification of discrete event systems using acceptance sampling. In Computer Aided Verification: 14th International Conference, CAV 2002 Copenhagen, Denmark, July 27–31, 2002 Proceedings 14 (pp. 223-235). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45657-0_17
  • Zhang, X. (2018). Application of discrete event simulation in health care: a systematic review. BMC health services research, 18, 1-11. https://doi.org/10.1186/s12913-018-3456-4
  • Zouri, M., Cumpat, C., Zouri, N., Maria-Magdalena, L. E. O. N., Mastaleru, A., & Ferworn, A. (2019). Decision support for resource optimization using discrete event simulation in rehabilitation hospitals. Revista de Cercetare si Interventie Sociala, 65, 82-96. https://doi.org/10.33788/rcis.65.6
There are 48 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Research Article
Authors

Alkan Durmuş 0000-0002-5806-9962

Abdurrahman İskender 0000-0001-8055-7869

Publication Date April 30, 2025
Submission Date January 8, 2025
Acceptance Date March 26, 2025
Published in Issue Year 2025Volume: 10 Issue: 1

Cite

Vancouver Durmuş A, İskender A. Evaluation of Services in MRI Department of University Hospital with Discrete Event Simulation Technique: A Case Study. J Cumhuriyet Univ Health Sci Inst. 2025;10(1):40-51.

The Journal of Sivas Cumhuriyet University Institute of Health Sciences is an international, peer-reviewed scientific journal published by Sivas Cumhuriyet University, Institute of Health Sciences.