Multi-Criteria Decision Making (MCDM) Applications in Military Healthcare Field

Öz

          Military decision-making is a critical process in which all environmental factors need to be assessed in detail in a risky environment. Due to the risky situation in this field, the decision-making process becomes more serious. Important developments and changes have been also experienced in the healthcare field worldwide. Over the past few years, the limited and even insufficient resources in the face of these developments and changes increase the importance of the studies in the healthcare field. Therefore, when all existing situations, constraints and risks are considered in the field of military and healthcare systems, a decision process is required in the field of military healthcare in which many criteria are considered and evaluated from various aspects. At this point, Multi-Criteria Decision Making (MCDM) methods are systematic, consistent and powerful approaches to respond to this need. Although a large amount of research has been done in the past on healthcare and military field using different methodological approaches, it is observed that there is a shortage in the application of MCDM methods in the field of military healthcare. Therefore, an encouraging study is needed to increase the number of studies in this field. The main purpose of this study is to emphasize the importance and development of MCDM methods in military healthcare by considering how MCDM methods are applied separately in the military and healthcare fields in the literature. In this context, the basic concept of MCDM methodologies is introduced and the studies that applied MCDM methods in healthcare and military are analyzed. This study is expected to bring insights to further studies in the military healthcare field.

Anahtar Kelimeler

• Decision-making,Healthcare,Military Healthcare,Military Decision Making,Multi-Criteria Decision Making (MCDM)

Kaynakça

1. Aberdeen, D., Thiébaux, S., Zhang, L. (2004). Decision-theoretic Military Operations Planning. 2004 14th International Conference on Automated Planning and Scheduling. (ICAPS) (pp. 402–411).
2. Adalı, E. A., Tuş, A. (2019). Hospital Site Selection with Distance-based Multi-criteria Decision-making Methods. International Journal of Healthcare Management, 1–11.
3. Arıkan, F., Yağlı, U. (2018). Hava Kuvvetleri Komutanlığı Malzeme İhtiyaç Planlaması Tedarik Tavsiye Listesinin ÇKKV Yöntemleri İle Analizi. Journal of Defense Sciences/Savunma Bilmleri Dergisi,17.
4. Aplak, H. S. (2018). Karar VermeYöntemleri̇ Ve Askerî Muharebe Fonksi̇yonları AlanlarınaYönelık Uygulamaları. Güvenlik Bilimleri Dergisi, 7,87–110.
5. Bahadori, M., Hosseini, S. M., Teymourzadeh, E., Ravangard, R., Raadabadi, M., Alimohammadzadeh, K. (2017). A supplier selection model for hospitals using a combination of artificial neural network and fuzzy VIKOR. International Journal of Healthcare Management, 1–9.
6. Balmat, J.-F., Lafont, F., Maifret, R., Pessel, N. (2011). A Decision-making System to Maritime Risk Assessment. Ocean Engineering, 38,171–176.
7. Barrios, M. A. O., De Felice, F., Negrete, K. P., Romero, B. A., Arenas, A. Y., Petrillo, A. (2016). An AHP-TOPSIS Integrated Model for Selecting the Most Appropriate Tomography Equipment. International Journal of Information Technology and Decision Making, 15,861–885.
8. Behzadian, M., Kazemzadeh, R. B., Albadvi, A., Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200,198–215.

9. Belton, V., Stewart, T. (2002). Multiple criteria decision analysis: an integrated approach. USA: Springer Science & Business Media.
10. Büyükselçuk, E. Ç. (2017). Green and Innovative Supplier Selection Model via MCDM Techniques and a Case Study in Automotive Industry. Marmara University, Department of Engineering Management, Istanbul.
11. Broekhuizen, H., Groothuis-Oudshoorn, C. G. M., Van Til, J. A., Hummel, J. M., Ijzerman, M. J. (2015). A Review and Classification of Approaches for Dealing with Uncertainty in Multi-Criteria Decision Analysis for Healthcare Decisions. Pharmaco Economics, 33,445–455.
12. Chretien, J. P., Blazes, D. L., Coldren, R. L., Lewis, M. D., Gaywee, J., Kana, K., Sirisopana N., Vallejos V., Mundaca CC, Montano S., Martin GJ., Gaydos, J. C. (2007). The importance of militaries from developing countries in global infectious disease surveillance. World Hospitals and Health Services: The Official Journal of the International Hospital Federation, 43,32–37.
13. 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, 6717-6727.
14. De Leeneer, I., Pastijn, H. (2002). Selecting land mine detection strategies by means of outranking MCDM techniques. European Journal of Operational Research, 139,327–338.
15. Drake, J. I., de Hart, J. C. T., Monleón, C., Toro, W., Valentim, J. (2017). Utilization of multiple-criteria decision analysis (MCDA) to support healthcare decision-making FIFARMA, 2016. Journal of Market Access & Health Policy, 5,1360545.
16. Düzcü, T, Yildirim, O, Zülfikar, H, Yilmaz Alarçin, E, Sezginer, B, Tozan, H. (2019). The Perceived Service Quality on Patient: Evidence from University Hospital. Journal of Health Systems and Policies, 1 ,90-100.
17. Ersöz, F. (2010). Savunma Sanayi̇ Uygulamalarinda Çok Kri̇terli̇ Karar Verme Yöntemleri̇ni̇n Li̇teratür Araştırması. Savunma Bilimleri Dergisi, 9,97-125.
18. Fashoto, S. G., Akinnuwesi, B., Owolabi, O., Adelekan, D. (2016). Decision support model for supplier selection in healthcare service delivery using analytical hierarchy process and artificial neural network. African Journal of Business Management, 10, 209–232.
19. Gılıç, F., Çelikten, M., Çelikten, Y., Yıldırım, A. (2019). Örgüt Yönetiminde Karar Verme Süreci: Bitmeyen Bir Tartışma. Mersin University Journal of the Faculty of Education, 15, 581-592.
20. Göleç, A., Gürbüz, F., Şenyiğit, E. (2016). Determination of Best Military Cargo Aircraft with Multi-Criteria Decision-Making Techniques. MANAS Journal of Social Studies, 5,87-101.
21. Goztepe, K., C.Kahraman. (2015). A New Approach to Military Decision Making Process: Suggestions from MCDM Point of View. 2015 International Conference on Military and Security Studies. (ICMSS) (pp.118–122).
22. Green, B., Majerol, M. and Rosendale, D. (2019, November 15). Innovation in the Military Health System. https://www2.deloitte.com/us/en/insights/industry/public-sector/top-10-military-health-system-innovations.html
23. Gyarmati, J., Zentay, P. (2013). Comparing Military Technology Devices with Multi-Criteria Decision Making and Solving Group Decision Problems. Economics and Management, 2,30-36.
24. Improta, G., Russo, M. A., Triassi, M., Converso, G., Murino, T., Santillo, L. C. (2018). Use of the AHP methodology in system dynamics: Modelling and simulation for health technology assessments to determine the correct prosthesis choice for hernia diseases. Mathematical Biosciences, 299, 19–27.
25. Ivlev, I., Vacek, J., Kneppo, P. (2015). Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research, 247,216-228.
26. József, G. (2015). Military Application of Multi-Criteria Decision Making. Academic and Applied Research in Military and Public Management Science, 14,291–297.
27. Kalanlar, B. (2018). Türkiye’nin Yüzüncü Yılında Sağlık Sektörü, Mevcut Durum ve Öngörüler. Hacettepe Sağlık İdaresi Dergisi, 21,495-510.
28. Karacan, D. (2015). A New Hybrid Decision Support Tool and an Application to Health Technology Selection. Turkish Naval Academy, Naval Science and Engineering Institute, İstanbul.
29. Karadayı, M. A., Karsak, E. E. (2014). Fuzzy MCDM approach for health-care performance assessment in Istanbul. 2014 The 18th World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI) (pp. 228-233).
30. Karadayi, M. A., Ekinci, Y., Tozan, H. (2019). A Fuzzy MCDM Framework for Weapon Systems Selection. Operations Research for Military Organizations, 185–204.
31. Kuo, R. J., Wu, Y. H., Hsu, T. S. (2012). Integration of fuzzy set theory and TOPSIS into HFMEA to improve outpatient service for elderly patients in Taiwan. Journal of the Chinese Medical Association, 75,341–348.
32. Köksalan, M., Wallenius, J., Zionts, S. (2013). An early history of multiple criteria decision making. Journal of Multi‐Criteria Decision Analysis, 20,87-94.
33. Lee, J., Kang, S. H., Rosenberger, J., Kim, S. B. (2010). A hybrid approach of goal programming for weapon systems selection. Computers and Industrial Engineering, 58,521–527.
34. Lin, K. P., Hung, K. C. (2011). An efficient fuzzy weighted average algorithm for the military UAV selecting under group decision-making. Knowledge-Based Systems, 24,877–889.
35. Magnezi, R., Dankner, R., Shani, M., Levy, Y., Ashkenazi, I., Reuveni, H. (2005). Comparison of Health Care Services for Career Soldiers Throughout the World. Military Medicine, 170,995–998.
36. Montazer, G. A., Saremi, H. Q.,Ramezani, M. (2009). Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Systems with Applications, 36,10837-10847.
37. Miç, P., Antmen, Z. F. (2019). Sağlık Hizmeti Tesis Yerleşimi Probleminin Değerlendirilmesine Çok Kriterli Bulanık Bir Yaklaşım. European Journal of Science and Technology, 750–757.
38. Organ, A., Tekin, B. (2017). Şehir Hastanesi Kuruluş Yeri Seçimi İçin Gri İlişkisel Analiz Yaklaşımı: Denizli İli Örneği. Adnan Menderes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 4,256-278.
39. Öztürk, N., Tozan, H. (2015). A fuzzy-based decision support model for selecting the best dialyser flux in haemodialysis. Journal of Healthcare Engineering, 6,303–324.
40. Peregrin, S., Jablonsky, J. (2016). Analytic hierarchy process as a tool for group evaluation of healthcare equipment. International Journal of Business and Systems Research, 10,124–141.
41. Rao, R. V. (2007). Decision making in the manufacturing environment: using graph theory and fuzzy multiple attribute decision making methods. Springer Science & Business Media
42. Rizzo, A., Parsons, T. D., Lange, B., Kenny, P., Buckwalter, J. G., Rothbaum, B., Difede J., Frazier J., Newman B., Williams J., Reger, G. (2011). Virtual reality goes to war: A brief review of the future of military behavioral healthcare. Journal of Clinical Psychology in Medical Settings, 18,176–187.
43. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International journal of services sciences, 1,83-98.
44. Sadeghzadeh, K., Salehi, M. B. (2011). Mathematical analysis of fuel cell strategic technologies development solutions in the automotive industry by the TOPSIS multi-criteria decision making method. International Journal of Hydrogen Energy, 36,13272-13280.
45. Sennaroglu, B., Celebi, G. V. (2018). A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment, 59,160-173.
46. Senvar, O., Otay, I., Bolturk, E. (2016). Hospital Site Selection via Hesitant Fuzzy TOPSIS. IFAC-PapersOnLine, 49, 1140–1145.
47. Singh, A., Prasher, A. (2019). Measuring healthcare service quality from patients’ perspective: using Fuzzy AHP application. Total Quality Management & Business Excellence, 30,284-300.
48. Schubert, J., Hörling, P. (2014). Preference-based Monte Carlo weight assignment for multiple-criteria decision making in defense planning. In 17th International Conference on Information Fusion (FUSION) (pp. 1-8). IEEE.
49. Tavana, M., Mavi, R. K., Santos-Arteaga, F. J., Doust, E. R. (2016). An extended VIKOR method using stochastic data and subjective judgments. Computers & Industrial Engineering, 97,240-247.
50. Temuçin, T., Tozan, H., Vayvay, Ö., Harničárová, M., Valíček, J. (2014). A fuzzy based decision model for nontraditional machining process selection. International Journal of Advanced Manufacturing Technology, 70,2275–2282.
51. Toker, D., Tozan, H., & Vayvai, O. (2013). A Decision Model for Pharmaceutical Marketing and a Case Study in Turkey. Economic Research-Ekonomska Istraživanja, 26, 101–114.
52. Tozan, H (2011). Fuzzy AHP based decision support system for technology selection in abrasive water jet cutting processes. Tech Gazette, 18,187–191
53. Tozan, H., Donmez, S. (2015). A Genetic Algorithm Based Approach to Provide Solutions for Emergency Aid Stations Location Problem and a Case Study for Pendik/Istanbul. Journal of Homeland Security and Emergency Management, 12,915–940.
54. Tsai, H. Y., Chang, C. W., Lin, H. L. (2010). Fuzzy hierarchy sensitive with Delphi method to evaluate hospital organization performance. Expert Systems with Applications, 37,5533-5541.
55. Turǧut, B. T., Taş, G., Herekoǧlu, A., Tozan, H., Vayvay, O. (2011). A fuzzy AHP based decision support system for disaster center location selection and a case study for Istanbul. Disaster Prevention and Management, 20,499–520.
56. Uçar, M., Deniz, S. (2012). Türk Tarihinde Askeri Sağlık Hizmetleri. TAF Preventive Medicine Bulletin, 11, 103-118.
57. Uğur, L. O. (2017). Yapı Makinesi Satın Alımında VIKOR Çok Kriterli Karar Verme Yönteminin Uygulanması. Journal of Polytechnic, 20, 879–885.
58. Unspecified (2019, December 10). Elements of MHS. https://www.health.mil/About-MHS/MHS-Elements
59. Unspecified (2019, December 11). Staff Organizations and Operations. https://www.globalsecurity.org/military/library/policy/army/fm/101-5/f540.pdf
60. Wibowo, A. S., Permanasari, A. E., Fauziati, S. (2016). Combat aircraft effectiveness assessment using hybrid multi-criteria decision making methodology. 2016 2nd International Conference on Science and Technology-Computer. (ICST) (pp. 112-117).