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Determination of the Most Appropriate Ultrasound Device in Healthcare Institutions with the Critic-GRA Hybrid Method

Yıl 2023, Cilt: 5 Sayı: 3, 541 - 8, 18.09.2023

Hakan Murat Arslan

https://doi.org/10.37990/medr.1300002

Öz

Aim: Medical devices used in health institutions are quite costly and many criteria such as the selection process, efficiency and ease of use of these devices should be taken into account. Careful selection of these devices is in the class of difficult problems as it involves the evaluation of various criteria. This study is to determine the selection process of the same type of medical devices and the most appropriate device of the relevant health institution, especially when alternatives are available.
Material and Methods: The solution of the problem is modeled by using the Critic and Gray Relational Analysis (GRA) methods in an integrated structure. The basis of the study is the applicability of Multi criteria decision making (MCDM) methods. The criteria and alternatives of the created decision making model were determined by using the opinions of physicians working in the field and the literature. A case study was conducted on a decision problem of determining the most suitable ultrasound device for a healthcare institution in Düzce.
Results: According to the analysis results obtained, it was determined that the most suitable device was A3 (GE) and the most inappropriate ultrasound device was A4 (MN). In addition, the most effective criterion was K1 (Price), while the least effect was K5 (Durability).
Conclusion: It has been determined that the findings obtained are consistent with the literature. In addition, the results of the study were shared with the relevant physicians and managers.

Anahtar Kelimeler

MCDM methods Critic method Gray Relation Analysis Method Medical Devices Health Sector

Kaynakça

  • 1. Marsh K, Goetghebeur M, Thokala P, Baltussen R. Multi-criteria decision analysis to support healthcare decisions. 1st edition. Springer Cham, 2017;1.
  • 2. Shbool MA. Essays in physicians preference items and inventory management within the healthcare supply Chain. Graduate thesis and dissertations, University of Arkansas, Fayetteville, 2016.
  • 3. Shbool MA, Rossetti MD. Physician preference items a decision making framework. In: IIE Annual Conference. Proceedings, Pittsburgh, PA. March 14, 2017.
  • 4. Glaize A, Duenas A, Martinelly CD, Fagnot I. Healthcare decision making applications using multi criteria decision analysis: A scoping review. Journal of Multi criteria decision Analysis. 2019;26:62-83.
  • 5. Ivlev I, Vacek J, Kneppo P. Multi criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research. 2015;247:216-28.
  • 6. Frazão TDC, Camilo DGG, Cabral ELS, Souza RP. Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps. BMC Med Inform Decis Mak. 2018;18:90.
  • 7. Büyüközkan G, Göçer F. Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Computing. 2019:23:10085–103.
  • 8. Carnero MC, Gomez A. Optimization of decision making in the supply of medicinal gases used in health care. Sustainability. 2019;11:2952.
  • 9. Tadic D, Stefanovic M, Aleksic A. The evaluation and ranking of medical device suppliers by using fuzzy topsis methodology. Journal of Intelligent & Fuzzy Systems. 2014;27:2091–101.
  • 10. Abdel-Basset M, Manogaran G, Gamal A, Smarandache F. A group decision making framework based on neutrosophic TOPSIS approach for smart medical device selection. J Med Syst. 2019;43:38.
  • 11. Ivlev I, Jablonsky J, Kneppo P. Multiple criteria comparative analysis of magnetic resonance imaging systems. Int. J. Medical Engineering and Informatics. 2016;8:124–41.
  • 12. Ivlev AV, Zhdanov SK, Khrapak SA, Morfill GE. Ion drag force in dusty plasmas Plasma Phys Control Fusion. 2004;46:B267.
  • 13. Carnero MC, Gómez A. Optimization of decision making in the supply of medicinal gases used in health care. Sustainability. 2019;11:2952.
  • 14. Emec S, Turanoglu B, Oztas S, Akkaya G. An integarted MCDM for a medical company selection in health sector. International Journal of Scientific and Technological Research. 2019;5:77–89.
  • 15. Liu HC, Wu J, Li P. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method. Waste Manag. 2013;33:2744-51.
  • 16. Lee YC, Chung P-H, Shyu JZ. Performance evaluation of medical device manufacturers using a hybrid fuzzy MCDM. Journal of Scientific and Industrial Research. 2017;76,28-31.
  • 17. Goh M, Zhong S, De Souza R. Operational framework for healthcare supplier selection under a fuzzy Multi criteria environment. 23rd International Symposium on Logistics (ISL 2018), 8 – 11 July 2018. Bali, Indonesia, 25.
  • 18. Hodgett, R.E. Comparison of multi-criteria decision-making methods for equipment selection. Int J Adv Manuf Technol. 2016;85:1145–57.
  • 19. Budak A, Ustundag A, Oztaysi B, Cevikcan E. A multi criteria intuitionistic fuzzy group decision making model for real time location system integration: An application from healthcare system. 12th International Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS), 24-26 August 2016, Roubaix, France, 580–7
  • 20. Willemé P, Dumont M. Machines that go ‘Ping’: Medical technology and health expenditures in OECD countries. Health Economics. 2015;24:1027–41. 21. Barrios MA, Felice FD, Negrete KP, et al. An AHP-topsis integrated model for selecting the most appropriate tomography equipment. International Journal of Information Technology & Decision Making. 2016;15:861–85.
  • 22. Akcan S, Güldeş M. Integrated multicriteria decision making methods to solve supplier selection problem: A case study in a hospital. Journal of Healthcare Engineering. 2019:1–10.
  • 23. Arslan HM. Evaluation of the financial performance of the enterprises operating in technoparks with critic-topsis method. Duzce University Journal of Social Sciences. 2019;9:144-53.
  • 24. Üstünışık NZ. Türkiye'deki iller ve bölgeler bazında sosyo-ekonomik gelişmişlik sıralaması araştırması: gri ilişkisel analiz yöntemi ve uygulaması. M.Sc. Thesis. Gazi Universitiy, Ankara. 2007.

Yıl 2023, Cilt: 5 Sayı: 3, 541 - 8, 18.09.2023

Hakan Murat Arslan

https://doi.org/10.37990/medr.1300002

Öz

Kaynakça

  • 1. Marsh K, Goetghebeur M, Thokala P, Baltussen R. Multi-criteria decision analysis to support healthcare decisions. 1st edition. Springer Cham, 2017;1.
  • 2. Shbool MA. Essays in physicians preference items and inventory management within the healthcare supply Chain. Graduate thesis and dissertations, University of Arkansas, Fayetteville, 2016.
  • 3. Shbool MA, Rossetti MD. Physician preference items a decision making framework. In: IIE Annual Conference. Proceedings, Pittsburgh, PA. March 14, 2017.
  • 4. Glaize A, Duenas A, Martinelly CD, Fagnot I. Healthcare decision making applications using multi criteria decision analysis: A scoping review. Journal of Multi criteria decision Analysis. 2019;26:62-83.
  • 5. Ivlev I, Vacek J, Kneppo P. Multi criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research. 2015;247:216-28.
  • 6. Frazão TDC, Camilo DGG, Cabral ELS, Souza RP. Multicriteria decision analysis (MCDA) in health care: a systematic review of the main characteristics and methodological steps. BMC Med Inform Decis Mak. 2018;18:90.
  • 7. Büyüközkan G, Göçer F. Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Computing. 2019:23:10085–103.
  • 8. Carnero MC, Gomez A. Optimization of decision making in the supply of medicinal gases used in health care. Sustainability. 2019;11:2952.
  • 9. Tadic D, Stefanovic M, Aleksic A. The evaluation and ranking of medical device suppliers by using fuzzy topsis methodology. Journal of Intelligent & Fuzzy Systems. 2014;27:2091–101.
  • 10. Abdel-Basset M, Manogaran G, Gamal A, Smarandache F. A group decision making framework based on neutrosophic TOPSIS approach for smart medical device selection. J Med Syst. 2019;43:38.
  • 11. Ivlev I, Jablonsky J, Kneppo P. Multiple criteria comparative analysis of magnetic resonance imaging systems. Int. J. Medical Engineering and Informatics. 2016;8:124–41.
  • 12. Ivlev AV, Zhdanov SK, Khrapak SA, Morfill GE. Ion drag force in dusty plasmas Plasma Phys Control Fusion. 2004;46:B267.
  • 13. Carnero MC, Gómez A. Optimization of decision making in the supply of medicinal gases used in health care. Sustainability. 2019;11:2952.
  • 14. Emec S, Turanoglu B, Oztas S, Akkaya G. An integarted MCDM for a medical company selection in health sector. International Journal of Scientific and Technological Research. 2019;5:77–89.
  • 15. Liu HC, Wu J, Li P. Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method. Waste Manag. 2013;33:2744-51.
  • 16. Lee YC, Chung P-H, Shyu JZ. Performance evaluation of medical device manufacturers using a hybrid fuzzy MCDM. Journal of Scientific and Industrial Research. 2017;76,28-31.
  • 17. Goh M, Zhong S, De Souza R. Operational framework for healthcare supplier selection under a fuzzy Multi criteria environment. 23rd International Symposium on Logistics (ISL 2018), 8 – 11 July 2018. Bali, Indonesia, 25.
  • 18. Hodgett, R.E. Comparison of multi-criteria decision-making methods for equipment selection. Int J Adv Manuf Technol. 2016;85:1145–57.
  • 19. Budak A, Ustundag A, Oztaysi B, Cevikcan E. A multi criteria intuitionistic fuzzy group decision making model for real time location system integration: An application from healthcare system. 12th International Conference on Uncertainty Modelling in Knowledge Engineering and Decision Making (FLINS), 24-26 August 2016, Roubaix, France, 580–7
  • 20. Willemé P, Dumont M. Machines that go ‘Ping’: Medical technology and health expenditures in OECD countries. Health Economics. 2015;24:1027–41. 21. Barrios MA, Felice FD, Negrete KP, et al. An AHP-topsis integrated model for selecting the most appropriate tomography equipment. International Journal of Information Technology & Decision Making. 2016;15:861–85.
  • 22. Akcan S, Güldeş M. Integrated multicriteria decision making methods to solve supplier selection problem: A case study in a hospital. Journal of Healthcare Engineering. 2019:1–10.
  • 23. Arslan HM. Evaluation of the financial performance of the enterprises operating in technoparks with critic-topsis method. Duzce University Journal of Social Sciences. 2019;9:144-53.
  • 24. Üstünışık NZ. Türkiye'deki iller ve bölgeler bazında sosyo-ekonomik gelişmişlik sıralaması araştırması: gri ilişkisel analiz yöntemi ve uygulaması. M.Sc. Thesis. Gazi Universitiy, Ankara. 2007.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İç Hastalıkları
Bölüm Özgün Makaleler
Yazarlar

Hakan Murat Arslan 0000-0002-3515-5358

Erken Görünüm Tarihi 9 Ağustos 2023
Yayımlanma Tarihi 18 Eylül 2023
Kabul Tarihi 19 Haziran 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 3

Kaynak Göster

AMA Arslan HM. Determination of the Most Appropriate Ultrasound Device in Healthcare Institutions with the Critic-GRA Hybrid Method. Med Records. Eylül 2023;5(3):541-8. doi:10.37990/medr.1300002
 Kapak Resmi İndir

         

Chief Editors
Assoc. Prof. Zülal Öner
Address: İzmir Bakırçay University, Department of Anatomy, İzmir, Turkey

Assoc. Prof. Deniz Şenol
Address: Düzce University, Department of Anatomy, Düzce, Turkey

E-mail: medrecsjournal@gmail.com

Publisher:
Medical Records Association (Tıbbi Kayıtlar Derneği)
Address: Düzce / Türkiye


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