Hastanelerde Çok Kriterli Karar Verme Uygulamalarının Sistematik Derlemesi

Yıl 2020, Cilt: 22 Sayı: 2, 612 - 645, 19.08.2020

Elif Erbay , Çağdaş Erkan Akyürek

Öz

Bireysel ve örgütsel
düzeylerde, karar verme süreçlerinin karmaşıklığının ve beşeri faktörlerden
kaynaklı belirsizliklerin etkili bir şekilde yönetilmesinde Çok Kriterli Karar
Verme Yöntemleri’ne başvurulmaktadır. Çeşitli sektörlerde uygulama alanı bulan
bu yöntemlerin sağlık kurumlarında uygulama örnekleri oldukça çeşitlidir. Bu
çalışmada, hastanelerde çok kriterli karar verme uygulamalarının hangi konularda, hangi yöntemlerle ve kriterlerle yapıldığının,
kriter seçim yönteminin, karar vericilerin dağılımının incelenmesi amaçlanmıştır.
PRISMA protokolü kapsamında yürütülen çalışmada, 01.01.2019-31.01.2019
tarihleri arasında 9 farklı veri tabanı taranmış, elde edilen 55 çalışma
incelemeye dahil edilmiştir. Hastanelerde Çok Kriterli Karar Verme
uygulamaları; kalite ve performans değerlendirme, tıbbi atık yönetimi ve
kuruluş yeri seçimi konularında
yoğunlaşmış, en çok Analitik Hiyerarşi Prosesi ve TOPSIS yöntemleri tercih
edilmiştir. Çalışma başına ortalama yaklaşık 5 kriter kullanılmış, çalışmanın
konusuna göre çeşitlenen bu kriterlerin seçiminde çoğunlukla literatür taraması
ve uzman görüşleri esas alınmıştır. Karar vericilerin genellikle alanında uzman
kişilerden, hekimlerden ve yöneticilerden oluştuğu ve çeşitli paydaşların karar
verme süreçlerine dahil edildiği belirlenmiştir. Çalışma sonuçlarında; üst yönetim
desteği, personelin süreçlere entegre edilmesi, karar verme süreçlerine farklı
paydaşların dahil edilerek sonuçların iyileştirilmesi hususlarına dikkat
çekilmiş, çalışma sonuçlarının politika yapıcılara hizmet sunumunun planlanması
ve iyileştirilmesinde önemli bilgiler sunduğu ifade edilmiştir. Sayısal
temellere dayandırılarak alınan kararlarda üst yönetim desteği daha kolay
sağlandığından, hastanelerde farklı hizmet süreçlerinde daha fazla Çok Kriterli
Karar Verme Yöntemleri uygulamalarına başvurulması önerilmektedir. 

Anahtar Kelimeler

çok kriterli karar verme, AHP, hastane, sağlık, sistematik derleme

Kaynakça

• Adebanjo, D., Laosirihongthong, T., & Samaranayake, P. (2016). Prioritizing lean supply chain management initiatives in healthcare service operations: a fuzzy AHP approach. Production Planning & Control, 27(12), 953-966.
• Ağaç, G., Baki, B. (2016). Sağlık Alanında Çok Kriterli Karar Verme Teknikleri Kullanımı: Literatür İncelemesi. Hacettepe Sağlık İdaresi Dergisi, 19(3). 343.
• Ahmadi, H., Nilashi, M., & Ibrahim, O. (2015). Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals. International journal of medical informatics, 84(3), 166-188.
• Ahmadi, H., Rad, M. S., Nazari, M., Nilashi, M., & Ibrahim, O. (2014). Evaluating the factors affecting the implementation of hospital information system (HIS) using AHP method. Life Science Journal, 11(3), 202-207.
• Ahsan, K., & Rahman, S. (2017). Green public procurement implementation challenges in Australian public healthcare sector. Journal of Cleaner Production, 152, 181-197.
• Aidemark, L.G., Funck, E.K. (2009). Measurement and Health Care Management. Financial Accountability & Management, 25: 253-276.
• Akdağ, H., Kalaycı, T., Karagöz, S., Zülfikar, H., & Giz, D. (2014). The evaluation of hospital service quality by fuzzy MCDM. Applied Soft Computing, 23, 239-248.
• Aktaş, A., Cebi, S., & Temiz, I. (2015). A new evaluation model for service quality of health care systems based on AHP and information axiom. Journal of Intelligent & Fuzzy Systems, 28(3), 1009-1021.
• Alharthi, H., Sultana, N., Al-amoudi, A., & Basudan, A. (2015). An Analytic Hierarchy Process–based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System. Perspectives in health information management, 12.
• Alimohammadzadeh, K., Bahadori, M., & Hassani, F. (2016). Application of analytical hierarchy process approach for service quality evaluation in radiology departments: A cross-sectional study. Iranian Journal of Radiology, 13(1).
• Amaral, T. M., & Costa, A. P. (2014). Improving decision-making and management of hospital resources: An application of the PROMETHEE II method in an Emergency Department. Operations Research for Health Care, 3(1), 1-6.
• Assis, M. C., Gomes, V. A., Balista, W. C., & Freitas, R. R. (2017). Use of performance indicators to assess the solid waste management of health services. Anais da Academia Brasileira de Ciências, 89(3), 2445-2460.
• Beheshtifar, S., & Alimoahmmadi, A. (2015). A multiobjective optimization approach for location‐allocation of clinics. International Transactions in Operational Research, 22(2), 313-328.
• Bronson, D. E., & Davis, T. S. (2012). Finding and evaluating evidence: Systematic reviews and evidence-based practice. Oxford University Press, 38-40.
• Budak, A., & Ustundag, A. (2015). Fuzzy decision making model for selection of real time location systems. Applied Soft Computing, 36, 177-184.
• Carnero, M. (2015). Assessment of environmental sustainability in health care organizations. Sustainability, 7(7), 8270-8291.
• Chanamool, N., & Naenna, T. (2016). Fuzzy FMEA application to improve decision-making process in an emergency department. Applied Soft Computing, 43, 441-453.
• Chang, T. H. (2014). Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Information Sciences, 271, 196-212.
• Chen, P. S., Lin, Y. J., & Peng, N. C. (2016). A two-stage method to determine the allocation and scheduling of medical staff in uncertain environments. Computers & Industrial Engineering, 99, 174-188.
• Dehe, B., & Bamford, D. (2015). Development, test and comparison of two Multiple Criteria Decision Analysis (MCDA) models: A case of healthcare infrastructure location. Expert Systems with Applications, 42(19), 6717-6727.
• Dell’Ovo, M., Frej, E. A., Oppio, A., Capolongo, S., Morais, D. C., & de Almeida, A. T. (2017). Multicriteria decision making for healthcare facilities location with visualization based on FITradeoff method. In International Conference on Decision Support System Technology (pp. 32-44). Springer, Cham.
• Eldemir, F., & Önden, I. (2016). Geographical information systems and multicriteria decisions integration approach for hospital location selection. International Journal of Information Technology & Decision Making, 15(05), 975-997.
• Gharahighehi, A., Kheirkhah, A. S., Bagheri, A., & Rashidi, E. (2016). Improving performances of the emergency department using discrete event simulation, DEA and the MADM methods. Digital health, 2, 2055207616664619.
• Gómez, A., & Carnero, M. C. (2016). Decision Support System for maintenance policy optimization in medicinal gases subsystems. IFAC-PapersOnLine, 49(28), 268-273.
• Guba, E.G. ve Lincoln, Y.S. (1989). Fourth Generation Evaluation. Newbury Park, CA:Sage.
• Gül, M., Ak, M. F., & Güneri, A. F. (2017). Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi-criteria approach. Human and Ecological Risk Assessment: An International Journal, 23(2), 187-202.
• Gül, M., Çelik, E., Gümüş, A. T., & Güneri, A. F. (2016). Emergency department performance evaluation by an integrated simulation and interval type-2 fuzzy MCDM-based scenario analysis. European Journal of Industrial Engineering, 10(2), 196-223.
• Honarbakhsh, M., Jahangiri, M., & Farhadi, P. (2017). Effective factors on not using the N95 respirators among health care workers: Application of Fuzzy Delphi and Fuzzy Analytic Hierarchy Process (FAHP). Journal of Healthcare Risk Management, 37(2), 36-46.
• Houria Z.B., Masmoudi, M., Al Hanbali, A., Khatrouch, I., Masmoudi, F. (2016). Quantitative techniques for medical equipment maintenance management. European Journal Industrial Engineering, 703-723.
• Hussain, M., & Malik, M. (2016). Prioritizing lean management practices in public and private hospitals. Journal of Health Organization and Management, 30(3), 457-474.
• Hussain, M., Malik, M., & Al Neyadi, H. S. (2016). AHP framework to assist lean deployment in Abu Dhabi public healthcare delivery system. Business Process Management Journal, 22(3), 546-565.
• Jeng, D.J.F., Tzeng, G.H. (2012). Social influence on the use of clinical decision support systems: revisiting the unified theory of acceptance and use of technology by the fuzzy DEMATEL technique. Computers & Industrial Engineering, 62(3):819-28. DOI:10.1016/j.cie.2011.12.016
• Karaçam, Z. (2013), Sistematik Derleme Metodolojisi: Sistematik Derleme Hazırlamak İçin Bir Rehber. Dokuz Eylül Üniversitesi Hemşirelik Yüksekokulu Elektronik Dergisi. 6(1):26-33
• Khanjankhani, K., Rafiei, S., Ezzatabadi, M. R., Askari, R., Abooee, F., & Shafii, M. (2016). Evaluation and Prioritization of Service Quality Dimensions Using Dematel and Topsis (A Case Study in Iran). Bali Medical Journal, 5(2), 118-123.
• Kıdak, L. B., Arslan, E. T., & Burmaoğlu, S. (2016). Hastanın Sesi Duyuluyor Mu? Bir Devlet Hastanesinde Bulanık AHP ile Ağırlıklandırılmış Kalite Fonksiyon Göçerimi Uygulaması. Journal of Alanya Faculty of Business/Alanya Isletme Fakültesi Dergisi, 8(2).
• Kulak, O., Goren, H. G., & Supciller, A. A. (2015). A new multi criteria decision making approach for medical imaging systems considering risk factors. Applied Soft Computing, 35, 931-941.
• Lee, C. W., & Kwak, N. K. (2011). Strategic enterprise resource planning in a health-care system using a multicriteria decision-making model. Journal of medical systems, 35(2), 265-275.
• Lee, S., Vaccari, M., & Tudor, T. (2016). Considerations for choosing appropriate healthcare waste management treatment technologies: A case study from an East Midlands NHS Trust, in England. Journal of Cleaner Production, 135, 139-147.
• Liao, W. H., & Qiu, W. L. (2016). Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems. SpringerPlus, 5(1), 1030.
• Liou, J., Lu, M. T., Hu, S. K., Cheng, C. H., & Chuang, Y. C. (2017). A hybrid MCDM model for improving the electronic health record to better serve client needs. Sustainability, 9(10), 1819.
• Liu, H. C., You, J. X., Lu, C., & Chen, Y. Z. (2015). Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model. Renewable and Sustainable Energy Reviews, 41, 932-942.
• Liu, H. C., You, J. X., Lu, C., & Shan, M. M. (2014). Application of interval 2-tuple linguistic MULTIMOORA method for health-care waste treatment technology evaluation and selection. Waste Management, 34(11), 2355-2364.
• Liu, L., Wu, A., Yu, H., Wang, N., & Li, H. (2014). Comprehensive Evaluation of Operations Management of a Hospital by TOPSIS and GRA. Chinese Medical Record English Edition, 2(8), 351-354.
• Lu, C., You, J. X., Liu, H. C., & Li, P. (2016). Health-care waste treatment technology selection using the interval 2-tuple induced TOPSIS method. International journal of environmental research and public health, 13(6), 562.
• Lupo, T. (2016). A fuzzy framework to evaluate service quality in the healthcare industry: An empirical case of public hospital service evaluation in Sicily. Applied Soft Computing, 40, 468-478.
• Martelli, N., Hansen, P., van den Brink, H., Boudard, A., Cordonnier, A. L., Devaux, C., ... & Borget, I. (2016). Combining multi-criteria decision analysis and mini-health technology assessment: a funding decision-support tool for medical devices in a university hospital setting. Journal of biomedical informatics, 59, 201-208.
• Merola, E., Padoano, E., & Zuliani, V. (2016). An analytic hierarchy process-based framework to support outsourcing decisions on hospital sterilisation. Int J Bus Sys Res, 10(2-4), 142-61.
• Mirzaei, A., Tabibi, S. J., Nasiripour, A. A., & Riahi, L. (2016). Evaluating the Feasibility of Financial Variables of Health: A Hospital Administrator’s Viewpoint. Galen Medical Journal, 5(1), 25-30.
• Moher, D., Liberati, A., Tetzlaff, J. ve Altman, D.G. The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med 6(7): e1000097.
• Mustaffa, N., and A. Potter. 2009. “Healthcare Supply Chain Management in Malaysia: A Case Study.” Supply Chain Management: An International Journal 14 (3): 234–243.
• Nilashi, M., Ahmadi, H., Ahani, A., Ravangard, R., & bin Ibrahim, O. (2016). Determining the importance of hospital information system adoption factors using fuzzy analytic network process (ANP). Technological Forecasting and Social Change, 111, 244-264.
• Nojedeh, H. S. (2015). Identifying and prioritizing the indicators of talent management in recruiting radiology technicians.
• Ortiz‐Barrios, M. A., Aleman‐Romero, B. A., Rebolledo‐Rudas, J., Maldonado‐Mestre, H., Montes‐Villa, L., De Felice, F., & Petrillo, A. (2017). The analytic decision‐making preference model to evaluate the disaster readiness in emergency departments: The ADT model. Journal of Multi‐Criteria Decision Analysis, 24(5-6), 204-226.
• Pekkaya, M., & Pulat İmamoğlu, Ö. (2017). Hastane Hizmet Kalitesinde Servqual Boyutlarinin Önem Derecelerinin Belirlenmesi. Uluslararası Yönetim İktisat ve İşletme Dergisi, 13(5), 607-616.
• Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons, 102-143.
• Pomerol, J. C. ve Barbara-Romero, S., (2000). “Multicriterion Decision in Management Principles and Practice”, Springer Scinece and Business Media.
• Ritrovato, M., Faggiano, F. C., Tedesco, G., & Derrico, P. (2015). Decision-oriented health technology assessment: one step forward in supporting the decision-making process in hospitals. Value in Health, 18(4), 505-511.
• Senvar, O., Otay, I., & Bolturk, E. (2016). Hospital site selection via hesitant fuzzy TOPSIS. IFAC-PapersOnLine, 49(12), 1140-1145.
• Shafii, M., Hosseini, S. M., Arab, M., Asgharizadeh, E., & Farzianpour, F. (2015). Performance analysis of hospital managers using fuzzy AHP and fuzzy TOPSIS: Iranian experience. Global journal of health science, 8(2), 137.
• Shafii, M., Rafiei, S., Abooee, F., Bahrami, M. A., Nouhi, M., Lotfi, F., & Khanjankhani, K. (2016). Assessment of service quality in teaching hospitals of Yazd University of Medical Sciences: Using multi-criteria decision making techniques. Osong public health and research perspectives, 7(4), 239-247.
• Shahbod, N., Mansouri, N., Bayat, M., Nouri, J., & Ghoddousi, J. (2017). A fuzzy analytic hierarchy process approach to identify and prioritize environmental performance indicators in hospitals. International Journal of Occupational Hygiene, 9(2), 66-77.
• Si, S. L., You, X. Y., Liu, H. C., & Huang, J. (2017). Identifying key performance indicators for holistic hospital management with a modified DEMATEL approach. International journal of environmental research and public health, 14(8), 934.
• Tanios N, Wagner M, Tony M, Baltussen R, van Til J, Rindress D, Kind P, Goetghebeur MM. Which Criteria Are Considered in Healthcare Decisions? Insights From an International Survey of Policy and Clinical Decision Makers. Int J Technol Assess Health Care. 2013;29(4):456–65. https://doi.org/10.1017/S0266462313000573.
• Taşabat, S. E., Cinemre, N., & Şen, S. (2015). Farklı Ağırlıklandırma Tekniklerinin Denendiği Çok Kriterli Karar Verme Yöntemleri İle Türkiye’deki Mevduat Bankalarının Mali Performanslarının Değerlendirilmesi. Sosyal Bilimler Araştırma Dergisi, 4(2), 96-110.
• Thakur, V., & Ramesh, A. (2017). Healthcare waste disposal strategy selection using grey-AHP approach. Benchmarking: An International Journal, 24(3), 735-749.
• Torgerson, C. (2003). Systematic Reviews. Bodmin: Bloomsbury Publishing.
• Tourani, S., Hassani, M., Ayoubian, A., Habibi, M., & Zaboli, R. (2015). Analyzing and prioritizing the dimensions of patient safety culture in emergency wards using the TOPSIS technique. Global journal of health science, 7(4), 143.
• Turan, G. (2015). Çok Kriterli Karar Verme içinde İşletmeciler, Mühendisler ve Yöneticiler için Operasyonel, Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri. Bursa:Dora. s.21-61.
• Voudrias, E. A. (2016). Technology selection for infectious medical waste treatment using the analytic hierarchy process. Journal of the Air & Waste Management Association, 66(7), 663-672.
• Yıldırım, B. F. ve Önder, E. (2014). İşletmeciler, Mühendisler ve Yöneticiler için Operasyonel, Yönetsel ve Stratejik Problemlerin Çözümünde Çok Kriterli Karar Verme Yöntemleri. Bursa: Dora Yayınları.
• Zavadskas, E. K. ve Turskis, Z., “A New Additive Ratio Assessment (ARAS) Method in Multicriteria Desicion-Making”, Technological and Economic Development of Economy, C.16, S.2, s.159-172, 2010.