A TOPSIS AND FUZZY QFD BASED APPROACH TO THE EVALUATION OF PATIENT SATISFACTION

Öz

Technology advancements and shifting living standards are causing rapid changes in the health sector. Service providers aim to ensure the continuity of institutions by adapting to these rapid changes in an intensely competitive environment. The sustainability of institutions depends on ensuring the satisfaction of the patients they serve and creating the intention to receive service again. The concept of satisfaction is seen as the output of the technical and service dimension evaluations of service recipients. With this motivation, the aim of the research is to examine patient satisfaction on a foundation university hospital sample. In order to analyze the service provided by the hospital from the perspective of the service recipients, the expectations of the patients and their opinions about the service quality were defined as Patient Voice (PV) through satisfaction surveys. Patient voice was prioritized using the TOPSIS method. Technical Requirements (TR) were reached within the framework of literature review, expert opinions, and legislation. Quality Function Deployment (QFD) was used based on the information obtained to examine the process holistically. Thus, the uncertainty brought by the human factor and perception was integrated into the fuzzy decision-making method by considering it. Separate evaluation results were obtained for each patient group receiving emergency, outpatient and inpatient treatment.

Anahtar Kelimeler

• Patient Satisfaction
• TOPSIS
• QFD
• Fuzzy Logic

HASTA MEMNUNİYETİNİN DEĞERLENDİRİLMESİNE TOPSIS ve BULANIK KFG TEMELLİ BİR YAKLAŞIM

Öz

Sağlık sektörü teknolojik gelişmeler ve değişen yaşam şartlarına bağlı olarak hızlı değişimler göstermektedir. Hizmet sağlayıcılar yoğun rekabet ortamında bu hızlı değişimlere uyum sağlayarak kurumların devamlılıklarını sağlamayı amaçlamaktadır. Kurumların sürdürülebilirlikleri, hizmet verdikleri hastaların memnuniyetlerini sağlamaları ve tekrar hizmet alma niyeti oluşturmalarına bağlıdır. Memnuniyet kavramı hizmet alıcıların teknik boyut ve hizmet boyutu değerlendirmelerinin çıktısı olarak görülmektedir. Bu motivasyonla araştırmada bir vakıf üniversitesi hastanesi örneklemi üzerinde hasta memnuniyetinin incelenmesi amaçlanmaktadır. Hastane tarafından sunulan hizmeti hizmet alanların gözünden analiz etmek için hastaların beklentileri ve hizmet kalitesi hakkındaki görüşleri memnuniyet anketleri aracılığıyla hasta sesi (HS) olarak tanımlanmıştır. Hasta sesi TOPSIS yöntemi kullanılarak önceliklendirilmiştir. Literatür taraması, uzman görüşleri ve mevzuatlar çerçevesinde teknik gereksinimlere (TG) ulaşılmıştır. Süreci bütüncül incelemek için elde edilen bilgiler temel alınarak kalite fonksiyon göçerimi (KFG) kullanılmıştır. Böylece insan faktörü ve algısının getirdiği belirsizlik göz önünde bulundurularak bulanık karar verme yönteme entegre edilmiştir. Acil, ayaktan ve yatarak tedavi alan her bir hasta grubu için ayrı değerlendirme sonuçları elde edilmiştir.

Anahtar Kelimeler

• Hasta Memnuniyeti
• TOPSIS
• KFG
• Bulanık Mantık

Kaynakça

1. Abdelwahed, N. A. A., & Zehri, A. W. (2024). Health service quality and patients’ satisfaction among hospitals: the cohesive care of human beings and accomplishment of human rights. International Journal of Human Rights in Healthcare
2. Akın, S., & Kurutkan, M. N. (2021). Hasta memnuniyeti kavramının bibliyometrik analiz yöntemi ile incelenmesi. Sağlık Akademisyenleri Dergisi, 8(1), 71-84.
3. Al Awadh, M. (2022). Utilizing Multi-Criteria decision making to evaluate the quality of healthcare services. Sustainability, 14(19), 12745.
4. Benitez, J. M., Martín, J. C., & Román, C. (2007). Using fuzzy number for measuring quality of service in the hotel industry. Tourism management, 28(2), 544-555.
5. Bevilacqua, M., Ciarapica, FE, & Giacchetta, G. (2006). Tedarikçi seçimine yönelik bulanık- QFD yaklaşımı. Satınalma ve Tedarik Yönetimi Dergisi, 12 (1), 14-27.
6. Beyhan, T. E. (2021). Sağlık Kurumlarında Kalite Fonksiyon Göçerimi: Bir Literatür Tarama Çalışması. Türkiye Sağlık Enstitüleri Başkanlığı Dergisi, 4(1), 10-24.
7. Chan, L. K., Kao, H. P., & Wu, M. L. (1999). Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods. International journal of production research, 37(11), 2499-2518.
8. Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114(1), 1-9.

9. Cheng, S., Chan, C. W., ve Huang, G. H. (2002). Using multiple criteria decision analysis for supporting decisions of solid waste management. Journal of Environmental Science and Health, Part A, 37(6), 975-990.
10. Cho, I. J., Kim, Y. J., & Kwak, C. (2016). Application of SERVQUAL and fuzzy quality function deployment to service improvement in service centres of electronics companies. Total Quality Management & Business Excellence, 27(3-4), 368-381.
11. Ghavami, V., Ghiyasi, K. A., Kokabi-Saghi, F., & Shabanikiya, H. (2024). Patients’ Satisfaction With Physiotherapy Services of Red Cross Physical Rehabilitation Services and Related Factors: A Case Study of Afghanistan. Journal of Patient Experience, 11, 23743735241241182.
12. Gonzalez, M. E. (2019). Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking: An International Journal, 26(3), 854-870.
13. Han, T., Li, S., Li, X., Yu, C., Li, J., Jing, T., ... & Zhang, Z. (2022). Patient-centered care and patient satisfaction: Validating the patient-professional interaction questionnaire in China. Frontiers in Public Health, 10, 990620.
14. Hauser, J. R., ve Clausing, D. (1988). The house of quality.
15. Hasibuan, A., Parinduri, L., Sulaiman, O. K., Suleman, A. R., Harahap, A. K. Z., Hasibuan, M., ve Daengs, G. A. (2019, November). Service quality improvement by using the quality function deployment (KFG) method at the government general hospital. In Journal of Physics: Conference Series (Vol. 1363, No. 1, p. 012095). IOP Publishing.
16. Huang, J., Mao, L. X., Liu, H. C., ve Song, M. S. (2022). Quality function deployment improvement: A bibliometric analysis and literature review. quality ve quantity, 56(3), 1347-1366.
17. Junior, J. B. G., Hékis, H. R., Costa, J. A. F., de Andrade, Í. G. M., dos Santos Cabral, E. L., Castro, W. R. S., ... & da Costa Júnior, J. F. (2022). Application of the KFG-fuzzy-
18. SERVQUAL methodology as a quality planning tool at the surgical centre of a public teaching hospital. BMC Medical Informatics and Decision Making, 22(1), 8.
19. Kaufmann, A. (1988). Theory of expertons and fuzzy logic. Fuzzy Sets and Systems, 28(3), 295-304.
20. Klir, G., & Yuan, B. (1995). Fuzzy sets and fuzzy logic (Vol. 4, pp. 1-12). New Jersey: Prentice hall.
21. Kohn, L., Corrigan, J., & Donaldson, M. (2001). To err is human: building a safer health system. IOM, editor.
22. Kurtulmuşoğlu, F. B., Pakdil, F., & Atalay, K. D. (2016). Quality improvement strategies of highway bus service based on a fuzzy quality function deployment approach. Transportmetrica A: Transport Science, 12(2), 175-202.
23. Kutlu, M. B. (2023). Türkiye’de Gerçekleştirilen Kalite Fonksiyonu Göçerimi Araştırmalarının Müşteri Sesi Açısından İncelenmesi. Sosyal, İnsan ve İdari Bilimlerde Yenilikçi Çalışmalar, 643-672.
24. Kwong, C. K., & Bai, H. (2002). A fuzzy AHP approach to the determination of importance weights of customer requirements in quality function deployment. Journal of intelligent manufacturing, 13, 367-377.
25. Lee, C.K.M.; Ru, Chloe Tan Ying; Yeung, C.L.; Choy, K.L.; Ip, W.H. (2015). Analyze the healthcare service requirement using fuzzy KFG. Computers in Industry, 74(), 1–15. doi:10.1016/j.compind.2015.08.005
26. Lin, M. C., Tsai, C. Y., Cheng, C. C., & Chang, C. A. (2004). Using fuzzy QFD for design of low-end digital camera. International journal of applied science and engineering, 2(3), 222-233.
27. Mauri, A. G., Minazzi, R., & Muccio, S. (2013). A review of literature on the gaps model on service quality: A 3-decades period: 1985–2013. International Business Research, 6(12), 134-144.
28. Nikolaeva, A., Demyanova, O., ve Pugacheva, M. (2020). The applying of KFG-Analysis to increase patient satisfaction in helthcare organisations. AVFT–Archivos Venezolanos de Farmacología y Terapéutica, 39(7).
29. Rivers, P. A., & Glover, S. H. (2008). Health care competition, strategic mission, and patient satisfaction: research model and propositions. Journal of health organization and management, 22(6), 627-641.
30. Shen, X. X., Tan, K. C., & Xie, M. (2001). The implementation of quality function deployment based on linguistic data. Journal of Intelligent Manufacturing, 12, 65-75.
31. Türkiye İstatistik Kurumu. (2021). Yaşam Memnuniyeti Araştırması. Chrome extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.tuik.gov.tr/media/announ cements/yasam_memnuniyeti_arastirmasi_2021.pdf
32. Tzeng, G. H., ve Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
33. Yücesan, M., & Gül, M. (2020). Hospital service quality evaluation: an integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Computing, 24(5), 3237-3255. Zadeh, L. A. (1965). Fuzzy sets. Information and Control.
34. Zhao, R., & Govind, R. (1991). Defuzzification of fuzzy intervals. Fuzzy sets and systems, 43(1), 45-55.
35. Zimmermann, H. J. (1992). Methods and applications of fuzzy mathematical programming. In An introduction to fuzzy logic applications in intelligent systems (pp. 97-120). Boston, MA: Springer US.