Araştırma Makalesi
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Yoğun Bakım Ünitelerinde Mekanik Ventilatör Seçimi: Çok Kriterli Karar Verme Perspektifi

Yıl 2025, Cilt: 18 Sayı: 1, 263 - 292, 15.01.2025
https://doi.org/10.35674/kent.1479086

Öz

Tıbbi ekipmanın hasta sağlığıyla doğrudan bağlantılı olduğu düşünüldüğünde, güvenilir bir tedarikçinin titizlikle seçilmesi büyük önem taşımaktadır. Yoğun bakım üniteleri bağlamında, sağlık teknolojisi değerlendirmesi ve sağlık hizmeti kararları alma süreci çeşitli kriterlere dayanmakta, kanıtlarla desteklenmekte ve ilgili paydaşların farklı bakış açılarından etkilenmektedir. Çok kriterli karar analizi (ÇKKV), bu prosedürü düzenlemek ve bir dizi bakış açısını dikkate almak için umut verici bir çerçeve sağlar. Bu araştırmanın temel amacı, yoğun bakım ünitelerindeki paydaşların sağlık müdahalelerini değerlendirirken bakış açılarını ve tercihlerini araştırmaktır. Bu incelemede, bir vaka çalışması olarak mekanik ventilatörü değerlendirmek için çok kriterli bir yaklaşım kullanılmıştır. 3. Basamak Eğitim ve Araştırma Hastanesi için ventilasyon cihazı tedarik problemi üzerine yapılan araştırmada, bulanık VIKOR ve bulanık EDAS yöntemleri kullanılarak 44 kriterle değerlendirilen 4 alternatif firma arasından en uygun olanın seçilmiştir. Sonuçlara göre, her iki yöntem de alternatif 3'ü en iyi seçenek olarak belirlemiş ve literatüre çift kriterli karmaşık varsayımlı karar verme tekniklerinin uygulanması konusunda bir katkı sunmuştur.

Kaynakça

  • Abdel-Basset, M., Manogaran, G., Gamal, A., & Smarandache, F. (2019). A group decision making framework based on neutrosophic TOPSIS approach for smart medical device selection. Journal of medical systems, 43, 1-13.
  • Açu, M. ve Ocak, Ö. Ö. (2019). Gıdalarda aflatoksin düzeylerinin belirlenmesinde kullanılan analiz yöntemleri. Sinop Üniversitesi Fen Bilimleri Dergisi, 4(2), 168-181. HYPERLINK https://doi.org/10.33484/sinopfbd.537820, Doi.org/10.33484/sinopfbd.537820
  • Ağaoğlu, S. (1999). Van ilinde açıkta satılan kırmızı pul biberlerde aflatoksin B1 varlığının araştırılması. Van Tıp Dergisi, 6(4), 28-30.
  • Alsohime, F., Temsah, M. H., Al-Eyadhy, A., Ghulman, S., Mosleh, H., & Alsohime, O. (2021). Technical Aspects of Intensive Care Unit Management: A Single-Center Experience at a Tertiary Academic Hospital. J Multidiscip Healthc., 14, 869-875.
  • Alsohime, F., Temsah, M.-H., Al-Eyadhy, A., Ghulman, S., Mosleh, H., & Alsohime, O. (2022). Technical Aspects of Intensive Care Unit Management: A Single-Center Experience at a Tertiary Academic Hospital. Journal of Multidisciplinary Healthcare, 14, 869-875.
  • Alyazji, Q. A., Ozsahin, D. U., Uzun, B., & Ozsahin, I. (2022). Evaluating electronic blood pressure measurement devices with fuzzy TOPSIS technique. 2022 Advances in Science and Engineering Technology International Conferences (ASET) (s. 1-5). Dubai: IEEE.
  • Antmen, Z. F., & Miç, P. (2018). Çocuk Yoğun Bakım Ünitesinde Çok Kriterli Karar Verme ile Mekanik Ventilatör Seçimi ve Bir Uygulama Örneği. Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33(4), 17-30.
  • Atasoy, A. F., Hayoğlu, İ., Korkmaz, A., Kara, E. ve Yıldırım, A. (2017). Geleneksel ev isot baharatının aflatoksin içeriğinin belirlenmesi üzerine bir araştırma. Harran Tarım ve Gıda Bilimleri Dergisi, 21 (1), 35-40.
  • Bahreini, R., Doshmangir, L., & Imani, A. (2018). Affecting Medical Equipment Maintenance Management: A Systematic Review. Journal of Clinical and Diagnostic Research, 12(4), 1-8.
  • Bayrakdaroğlu, F. K., & Kundakcı, N. (2019). Bulanık Edas Yöntemi ile Ar-Ge Projesi Seçimi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (24), 151-170.
  • Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Syst. Appl., 39(17), 13051-13069.
  • Biswas, S. (2020). Measuring performance of healthcare supply chains in India: A comparative analysis of multi-criteria decision making methods. Decision Making: Applications in Management and Engineering, 3(2), 162-189.
  • Brans, J. P., & B., M. (1986). How to select and how to rank projects: the Promethee method. Eur. J. Oper. Res., 24(2), 228–238.
  • Brauers, W. K., & Zavadskas, E. K. (2010). Project management by multimoora as an instrument for transition economies. Technol. Econ. Dev. Econ., 16(1), 5–24.
  • Büyüközkan, G., & Göçer, F. (2019). Smart medical device selection based on intuitionistic fuzzy choquet integral. Soft Comput., 23, 10085-10103.
  • Ceballos, B., Lamata, M. T., & Pelta, D. A. (2016). A comparative analysis of multi-criteria decision-making methods. Prog Artif Intell, 5, 315–322.
  • Delice, E., Tozan, H., Karadayi, M. A., Harnicarova, M., & Turan, B. (2022). An integrated framework for non-traditional machining process technology selection in healthcare applications. Teh. Vjesn., 29, 2137-2146.
  • Deniz, N., & Orhan, E. O. (2022). Development of a multi-criteria decision-making-based assessment model for dental material selection: Engine-driven nickel-titanium instruments case study. Clin. Oral Investig., 26, 2645-2659.
  • Farghaly, M. N., Al Dallal, S. A., Fasseeh, A. N., Monsef, N. A., Suliman, E. A., Tahoun, M. A., . . . Kaló, Z. (2021). Recommendation for a pilot MCDA tool to support the value-based purchasing of generic medicines in the UAE. Front. Pharmacol., 12, 1-5.
  • Girginer, N., Uçkun, N., & Çelik, A. E. (2008). Bir Üniversite Hastanesinde Tıbbi Cihaz Satın Alma Karar Süreci. Elektronik Sosyal Bilimler Dergisi, 7(26), 138-153.
  • Haas, C. F., & Bauser, K. A. (2012). Advanced Ventilator Modes and Techniques. Critical Care Nursing Quarterly, 35(1), 27-38.
  • Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Sci. Total Environ., 409(19), 3578-3594.
  • Hulstaert, P. F., Kox, W., Miranda, D. R., Williams, A., & Loirat, M. D. (1990). Management of Intensive Care: Guidelines for Better Use of Resources. Norwell: Springer Netherlands.
  • Imhoff, M., Kuhls, S., Gather, U., & Fried, R. (2009). Smart alarms from medical devices in the OR and ICU. Best Practice & Research Clinical Anaesthesiology, 1, 39-50.
  • Ivlev, I., Kneppo, P., & Bartak, M. (2014). Multicriteria decision analysis: a multifaceted approach to medical equipment management. Technological and Economic Development of Economy, 20(3), 576–589.
  • Karakaşoğlu, N. (2018). Bulanık Çok Kriterli Karar Verme Teknikleri ve Uygulama. (Yayınlanmış Yüksek Lisans Tezi). Pamukkale Üniversitesi, Sosyal Bilimler Enstitüsü, Denizli.
  • Keleş, M. K., Özdağoğlu, A., & Eren, F. Y. (2019). Bir Laboratuvarda Tam Kan Sayım Cihazı Alternatiflerinin SWARA, WPM, TODIM ve AHS Yöntemleri ile Değerlendirilmesi. İzmir İktisat Dergisi, 511-526.
  • Kundu, P., Görçün, Ö. F., & Küçükönder, H. (2022). Medical device selection in private hospitals by integrated fuzzy MCGDM methods: a case study in choosing MRI (Magnetic Resonance Imaging) system. J. Oper. Res. Soc., 73, 2059-2079.
  • Leong, W. Y., Wong, K. Y., & Wong, W. P. (2022). A new integrated multi-criteria decision-making model for resilient supplier selection. Appl. Syst. Innov., 5, 1-18.
  • Majumder, M. (2015). Multi Criteria Decision Making. Singapore: Springer.
  • Marsh, K., Lanitis, T., Neasham, D., Orfanos, P., & Caro, J. (2014). Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature. Pharmacoeconomics, 32(4), 345-365.
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  • Moosivand, A., Rangchian, M., Zarei, L., Peiravian, F., Mehralian, G., & Sharifnia, H. (2021). An application of multi-criteria decision making approach to sustainable drug shortages management: evidence from a developing country. J. Pharma. Health Care Sci., 7, 1-14.
  • Motta, D., Amaral, L. T., Silva, B. D., Gomes, L. D., Barbosa, W. T., Coelho, R. S., & Machado, B. A. (2021). Collaborative and Structured Network for Maintenance of Mechanical Ventilators during the SARS-CoV-2 Pandemic. In Healthcare, 9(6), 754.
  • Mutlu, M., Tuzkaya, G., & Sennaroğlu, B. (2017). Multi-criteria decision making techniques for healthcare service quality evaluation: A literature review. Sigma Journal of Engineering and Natural Sciences, 35(3), 501-512.
  • Nimmo, G. R., & Singer, M. (2011). ABC of Intensive Care. West Sussex: Blackwell Publishing Ltd.
  • Novák, V. (2006). Which logic is the real fuzzy logic? Fuzzy Sets and Systems, 157(5,1), 635-641.
  • Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990.
  • Ottardi, C., Damonti, A., Porazzi, E., Foglia, E., Ferrario, L., Villa, T., . . . Galbusera, F. (2017). A comparative analysis of a disposable and a reusable pedicle screw instrument kit for lumbar arthrodesis: integrating HTA and MCDA. Health Research Policy and Systems, 13, 1-11.
  • Özçlik, G., & Nalkıran, M. (2021). An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system. Int. J. Fuzzy Syst., 23, 2348-2366.
  • Özdağoğlu, A., Keleş, M. K., & Yörük, E. F. (2019). Sağlık İşletmelerinde Nefelometre Cihazı Alternatiflerinin Değerlendirilmesi – Dematel -Multımoora Bütünleşik Yaklaşımı. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 20(2), 275-299.
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Utilization of Multi-Criteria Decision Making in the Selection of Mechanical Ventilators in Intensive Care Units: A Case Study

Yıl 2025, Cilt: 18 Sayı: 1, 263 - 292, 15.01.2025
https://doi.org/10.35674/kent.1479086

Öz

Given that medical equipment is directly linked to patient well-being, the meticulous choice of a reliable supplier is of paramount importance. Within the context of intensive care units, health technology assessment and the process of making healthcare decisions are grounded in various criteria, substantiated by evidence, and influenced by the diverse viewpoints of involved stakeholders. Multi-criteria decision analysis (MCDA) provides a promising framework for organizing this procedure and considering a range of perspectives. The primary goals of this research were to investigate the outlooks and preferences of stakeholders in intensive care units as they evaluate healthcare interventions. This examination utilized a multi-criteria approach to assess a mechanic ventilator as a case study. In the research on the ventilation device procurement problem for the 3rd Level Training and Research Hospital, fuzzy VIKOR and fuzzy EDAS methods were used to select the most suitable one among 4 alternative companies evaluated with 44 criteria. According to the results, both methods identified alternative 3 as the best option and made a contribution to the literature on the application of dual criteria complex assumption decision making techniques.

Kaynakça

  • Abdel-Basset, M., Manogaran, G., Gamal, A., & Smarandache, F. (2019). A group decision making framework based on neutrosophic TOPSIS approach for smart medical device selection. Journal of medical systems, 43, 1-13.
  • Açu, M. ve Ocak, Ö. Ö. (2019). Gıdalarda aflatoksin düzeylerinin belirlenmesinde kullanılan analiz yöntemleri. Sinop Üniversitesi Fen Bilimleri Dergisi, 4(2), 168-181. HYPERLINK https://doi.org/10.33484/sinopfbd.537820, Doi.org/10.33484/sinopfbd.537820
  • Ağaoğlu, S. (1999). Van ilinde açıkta satılan kırmızı pul biberlerde aflatoksin B1 varlığının araştırılması. Van Tıp Dergisi, 6(4), 28-30.
  • Alsohime, F., Temsah, M. H., Al-Eyadhy, A., Ghulman, S., Mosleh, H., & Alsohime, O. (2021). Technical Aspects of Intensive Care Unit Management: A Single-Center Experience at a Tertiary Academic Hospital. J Multidiscip Healthc., 14, 869-875.
  • Alsohime, F., Temsah, M.-H., Al-Eyadhy, A., Ghulman, S., Mosleh, H., & Alsohime, O. (2022). Technical Aspects of Intensive Care Unit Management: A Single-Center Experience at a Tertiary Academic Hospital. Journal of Multidisciplinary Healthcare, 14, 869-875.
  • Alyazji, Q. A., Ozsahin, D. U., Uzun, B., & Ozsahin, I. (2022). Evaluating electronic blood pressure measurement devices with fuzzy TOPSIS technique. 2022 Advances in Science and Engineering Technology International Conferences (ASET) (s. 1-5). Dubai: IEEE.
  • Antmen, Z. F., & Miç, P. (2018). Çocuk Yoğun Bakım Ünitesinde Çok Kriterli Karar Verme ile Mekanik Ventilatör Seçimi ve Bir Uygulama Örneği. Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33(4), 17-30.
  • Atasoy, A. F., Hayoğlu, İ., Korkmaz, A., Kara, E. ve Yıldırım, A. (2017). Geleneksel ev isot baharatının aflatoksin içeriğinin belirlenmesi üzerine bir araştırma. Harran Tarım ve Gıda Bilimleri Dergisi, 21 (1), 35-40.
  • Bahreini, R., Doshmangir, L., & Imani, A. (2018). Affecting Medical Equipment Maintenance Management: A Systematic Review. Journal of Clinical and Diagnostic Research, 12(4), 1-8.
  • Bayrakdaroğlu, F. K., & Kundakcı, N. (2019). Bulanık Edas Yöntemi ile Ar-Ge Projesi Seçimi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (24), 151-170.
  • Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Syst. Appl., 39(17), 13051-13069.
  • Biswas, S. (2020). Measuring performance of healthcare supply chains in India: A comparative analysis of multi-criteria decision making methods. Decision Making: Applications in Management and Engineering, 3(2), 162-189.
  • Brans, J. P., & B., M. (1986). How to select and how to rank projects: the Promethee method. Eur. J. Oper. Res., 24(2), 228–238.
  • Brauers, W. K., & Zavadskas, E. K. (2010). Project management by multimoora as an instrument for transition economies. Technol. Econ. Dev. Econ., 16(1), 5–24.
  • Büyüközkan, G., & Göçer, F. (2019). Smart medical device selection based on intuitionistic fuzzy choquet integral. Soft Comput., 23, 10085-10103.
  • Ceballos, B., Lamata, M. T., & Pelta, D. A. (2016). A comparative analysis of multi-criteria decision-making methods. Prog Artif Intell, 5, 315–322.
  • Delice, E., Tozan, H., Karadayi, M. A., Harnicarova, M., & Turan, B. (2022). An integrated framework for non-traditional machining process technology selection in healthcare applications. Teh. Vjesn., 29, 2137-2146.
  • Deniz, N., & Orhan, E. O. (2022). Development of a multi-criteria decision-making-based assessment model for dental material selection: Engine-driven nickel-titanium instruments case study. Clin. Oral Investig., 26, 2645-2659.
  • Farghaly, M. N., Al Dallal, S. A., Fasseeh, A. N., Monsef, N. A., Suliman, E. A., Tahoun, M. A., . . . Kaló, Z. (2021). Recommendation for a pilot MCDA tool to support the value-based purchasing of generic medicines in the UAE. Front. Pharmacol., 12, 1-5.
  • Girginer, N., Uçkun, N., & Çelik, A. E. (2008). Bir Üniversite Hastanesinde Tıbbi Cihaz Satın Alma Karar Süreci. Elektronik Sosyal Bilimler Dergisi, 7(26), 138-153.
  • Haas, C. F., & Bauser, K. A. (2012). Advanced Ventilator Modes and Techniques. Critical Care Nursing Quarterly, 35(1), 27-38.
  • Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Sci. Total Environ., 409(19), 3578-3594.
  • Hulstaert, P. F., Kox, W., Miranda, D. R., Williams, A., & Loirat, M. D. (1990). Management of Intensive Care: Guidelines for Better Use of Resources. Norwell: Springer Netherlands.
  • Imhoff, M., Kuhls, S., Gather, U., & Fried, R. (2009). Smart alarms from medical devices in the OR and ICU. Best Practice & Research Clinical Anaesthesiology, 1, 39-50.
  • Ivlev, I., Kneppo, P., & Bartak, M. (2014). Multicriteria decision analysis: a multifaceted approach to medical equipment management. Technological and Economic Development of Economy, 20(3), 576–589.
  • Karakaşoğlu, N. (2018). Bulanık Çok Kriterli Karar Verme Teknikleri ve Uygulama. (Yayınlanmış Yüksek Lisans Tezi). Pamukkale Üniversitesi, Sosyal Bilimler Enstitüsü, Denizli.
  • Keleş, M. K., Özdağoğlu, A., & Eren, F. Y. (2019). Bir Laboratuvarda Tam Kan Sayım Cihazı Alternatiflerinin SWARA, WPM, TODIM ve AHS Yöntemleri ile Değerlendirilmesi. İzmir İktisat Dergisi, 511-526.
  • Kundu, P., Görçün, Ö. F., & Küçükönder, H. (2022). Medical device selection in private hospitals by integrated fuzzy MCGDM methods: a case study in choosing MRI (Magnetic Resonance Imaging) system. J. Oper. Res. Soc., 73, 2059-2079.
  • Leong, W. Y., Wong, K. Y., & Wong, W. P. (2022). A new integrated multi-criteria decision-making model for resilient supplier selection. Appl. Syst. Innov., 5, 1-18.
  • Majumder, M. (2015). Multi Criteria Decision Making. Singapore: Springer.
  • Marsh, K., Lanitis, T., Neasham, D., Orfanos, P., & Caro, J. (2014). Assessing the value of healthcare interventions using multi-criteria decision analysis: a review of the literature. Pharmacoeconomics, 32(4), 345-365.
  • Miranda, D. R., Ryan , D. W., Schaufeli, W. B., & Fidler, V. (1998). Organisation and Management of Intensive Care. Griinstadt: Springer-Verlag Berlin Heidelberg.
  • Moosivand, A., Rangchian, M., Zarei, L., Peiravian, F., Mehralian, G., & Sharifnia, H. (2021). An application of multi-criteria decision making approach to sustainable drug shortages management: evidence from a developing country. J. Pharma. Health Care Sci., 7, 1-14.
  • Motta, D., Amaral, L. T., Silva, B. D., Gomes, L. D., Barbosa, W. T., Coelho, R. S., & Machado, B. A. (2021). Collaborative and Structured Network for Maintenance of Mechanical Ventilators during the SARS-CoV-2 Pandemic. In Healthcare, 9(6), 754.
  • Mutlu, M., Tuzkaya, G., & Sennaroğlu, B. (2017). Multi-criteria decision making techniques for healthcare service quality evaluation: A literature review. Sigma Journal of Engineering and Natural Sciences, 35(3), 501-512.
  • Nimmo, G. R., & Singer, M. (2011). ABC of Intensive Care. West Sussex: Blackwell Publishing Ltd.
  • Novák, V. (2006). Which logic is the real fuzzy logic? Fuzzy Sets and Systems, 157(5,1), 635-641.
  • Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990.
  • Ottardi, C., Damonti, A., Porazzi, E., Foglia, E., Ferrario, L., Villa, T., . . . Galbusera, F. (2017). A comparative analysis of a disposable and a reusable pedicle screw instrument kit for lumbar arthrodesis: integrating HTA and MCDA. Health Research Policy and Systems, 13, 1-11.
  • Özçlik, G., & Nalkıran, M. (2021). An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system. Int. J. Fuzzy Syst., 23, 2348-2366.
  • Özdağoğlu, A., Keleş, M. K., & Yörük, E. F. (2019). Sağlık İşletmelerinde Nefelometre Cihazı Alternatiflerinin Değerlendirilmesi – Dematel -Multımoora Bütünleşik Yaklaşımı. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 20(2), 275-299.
  • Özdağoğlu, A., Keleş, M. K., & Yörük, E. F. (2020). SWARA Tabanlı WSM ve CODAS Yöntemleri ile Biyokimya Hormon Cihazı Seçimi. Çankırı Karatekin Üniversitesi, İktisadi ve İdari Bilimler Fakültesi Dergisi, 10(1), 371-396.
  • Papathanasiou, J., & Ploskas, N. (2018). TOPSIS. Cham: Springer.
  • Ren, J., Ren, X., Liu, Y., Man, Y., & Toniolo, S. (2020). Multi-Criteria Decision Analysis for Sustainability Assessment and Ranking. London: Academic Press.
  • Roy, B., & Hugonnard, J. C. (1982). Ranking of suburban line extension projects on the Paris metro system by a multicriteria method. Transp. Res. A: Gen., 16(4), 301–312.
  • Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
  • Shamsan, A., & Aqlan, F. (2017). Selection of CT scanners using analytic hierarchy process and Monte Carlo simulation. IIE Annual Conference. Proceedings (s. 1997-2002). Institute of Industrial and Systems Engineers (IISE).
  • Shan, L. (2011). Research on Logistics Service Providers Selection Based on AHP and VIKOR. International Conference on Intelligent Computing and Information Science (s. 93–98). Berlin: Springer.
  • Shbool, M. A., Arabeyyat, O. S., Al-Bazi, A., & Al Alaween, W. H. (2021). An integrated multi-criteria decision-making framework for a medical device selection in the healthcare industry. Cogent Eng., 8, 1-18.
  • Shukla, K., & Muthal, S. (2017). Mishandling of Medical Devices in Hospital ICU: Analysis of Causes, Revenue Drains and Training Needs of ICU Staff. Indian Journal of Public Health Research & Development, 8(4), 751-755.
  • Sloane, E. B., Liberatore, M. J., Nydick, R. L., Luo, W., & Chung, Q. B. (2003). Using the analytic hierarchy process as a clinical engineering tool to facilitate an iterative, multidisciplinary, microeconomic health technology assessment. Computers & Operations Research, 30(10), 1447-1465.
  • Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & industrial engineering, 140, 1-15.
  • Sumrit, D. (2020). Supplier selection for vendor-managed inventory in healthcare using fuzzy multi-criteria decision-making approach. Decision Science Letters, 9(2), 233-256.
  • Sumrit, D. (2021). Understanding critical success factors of vendor-managed inventory in healthcare sector: A case study in Thailand. Int. J. Healthc. Manag., 14, 629-640.
  • Suzumura, E. A., Zazula, A. D., Moriya, H. T., Fais, C. Q., Alvarado, A. L., Cavalcanti, A. B., & Rodrigues, R. G. (2020). Challenges for the development of alternative low-cost ventilators during COVID-19 pandemic in Brazil. Revista Brasileira de Terapia Intensiva, 12(32), 444-57.
  • Tolga, A. C., Parlak, I. B., & Castillo, O. (2020). Finite-interval-valued type-2 Gaussian fuzzy numbers applied to fuzzy TODIM in a healthcare problem. Eng. Appl. Artif. Intell., 87, 1-13.
  • Torpy, J. M., Campbell, A. D., & Glass, R. M. (2010). Mechanical ventilation. JAMA, 303(9), 902-902.
  • Varon, J., & Acosta, P. (2010). Handbook of Critical and Intensive Care Medicine. New York: Springer Science+Business Media.
  • Wahlster, P., Goetghebeur, M., Schaller, S., Kriza, C., Kolominsky-Rabas, P., & National Leading-Edge Cluster Medical Technologies. (2015). Kolominsky-Rabas, P., & Exploring the perspectives and preferences for HTA across German healthcare stakeholders using a multi-criteria assessment of a pulmonary heart sensor as a case study. Health Research Policy and Systems, 13, 1-11.
  • Walter, K. (2021). Mechanical ventilation. JAMA, 326(14), 1452-1452.
  • Waydhas, C. (1999). Equipment review: Intrahospital transport of critically ill patients. Christian Waydhas, 3(5), 83-89.
  • Yazdani, M., Torkayesh, A. E., & Chatterjee, P. (2020). An integrated decision-making model for supplier evaluation in public healthcare system: the case study of a Spanish hospital. J. Enterp. Inf. Manag., 33, 965-989.
  • Yürüyen, A. A., & Ulutaş, A. (2020). Bulanık AHP ve bulanık EDAS yöntemleri ile üçüncü parti lojistik firması seçimi. Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(İktisadi ve İdari Bilimler), 283-294.
  • Zadeh, L. A. (1975). Fuzzy logic and approximate reasoning. Synthese, 30, 407-428.
  • Zadeh, L. A. (2008). Is there a need for fuzzy logic? Information Sciences, 178(13), 2751-2779.
Toplam 65 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ulaşım, Lojistik ve Tedarik Zincirleri (Diğer)
Bölüm Tüm Makaleler
Yazarlar

Alkan Durmuş 0000-0002-5806-9962

Abdurrahman İskender 0000-0001-8055-7869

Erken Görünüm Tarihi 15 Ocak 2025
Yayımlanma Tarihi 15 Ocak 2025
Gönderilme Tarihi 6 Mayıs 2024
Kabul Tarihi 28 Kasım 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 18 Sayı: 1

Kaynak Göster

APA Durmuş, A., & İskender, A. (2025). Yoğun Bakım Ünitelerinde Mekanik Ventilatör Seçimi: Çok Kriterli Karar Verme Perspektifi. Kent Akademisi, 18(1), 263-292. https://doi.org/10.35674/kent.1479086

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