Personalized Decision-Making in Type 2 Diabetes Treatment:A Porter's Value Chain-Based Model with a Case Study from a Public Hospital
Ali Kahramfar
1
(
Department of Industrial Engineering, Iran University of Science and Technology, Narmak, 16844, Tehran, Iran.
)
Abdollah Jassbi
2
(
Department of Industrial Engineering, Iran University of Science and Technology, Narmak, 16844, Tehran, Iran.
)
javad jassbi
3
(
UNINOVA-CTS, NOVA University of Lisboa, 2829-516 Monte Caparica, Portugal
)
Ebrahim Teimoury
4
(
Department of Industrial Engineering, Iran University of Science and Technology, Narmak, 16844, Tehran, Iran.
)
الکلمات المفتاحية: Value chain, Healthcare decision, Diabetes, Costs, UML Modeling ,
ملخص المقالة :
Addressing rising healthcare costs and improving patient outcomes, especially in diabetes care, is a significant challenge. Various decision-making techniques have been applied to make optimal treatment choices for diabetes. This study employs value-based healthcare, which links costs and outcomes to specific treatment activities. The introduction of the value strategy into diabetes decision-making resulted in a theoretical framework that defined elements of the decision process and formed a modeling framework. This modeling framework assembles a personalized Care Delivery Value Chain and ranks treatment actions based on each patient's preferences and conditions for Type II diabetes mellitus. To achieve the results, a value chain for diabetes care delivery was developed through a case study at Hamedan Beheshti Hospital, utilizing a system modeling approach. Data and information for the case were collected from an internal medicine reference book and through interviews with internists. The expandability, reliability, and validity of the diabetes care delivery value chain were improved and verified through diverse sources, including questionnaires and interviews. A comprehensive, personalized care delivery value chain for diabetes was developed, providing a structured framework for improving treatment outcomes based on Porter's Value Chain model. The diabetes care delivery value chain, tailored to specific conditions, offers a detailed overview of treatment activities. It enables associating these activities with costs and outcomes, laying the foundation for measuring healthcare value. Additionally, The framework supports the standardization and digitalization of personalized treatments for Type 2 diabetes, ensuring repeatability despite underlying dynamics.
Afuah, A. (2004). Business Models: A Strategic Management Approach. McGraw-Hill, Irwin.
Aldaghi, T., & Muzik, J. (2024). Multicriteria Decision-Making in Diabetes Management and Decision Support: Systematic Review. JMIR Med Inform, 12, e47701.
Areewong, K., Rattanawiboonsom, V., & Meer, R. V. D. (2024). The survey of lean implementation maturity level of hospitals in Thailand: Does the hospital type matter? Journal of Optimization in Industrial Engineering, 1(17), 171-174.
Berhan, E., Yibeltal, S., & Geremew, S. (2018). Service Performance Improvement Model: The Case of Teklehaymanot General Hospital. Journal of Optimization in Industrial Engineering, 11(1), 23-33.
Berry, L., & Seltman, K. (2008). Management Lessons from Mayo Clinic: Inside One of the World’s Most Admired Service Organizations. Mcgraw-hill, New York.
Chai, S., Yu, S., Liu, F., Liu, Z., Yang, Q., Sun, F., & Ni, J. (2023). Benefit-risk assessment of incretin and other anti-diabetic agents in type 2 diabetes using a stochastic multicriteria acceptability analysis model. Chinese Medical Journal, 136(01), 102-104.
Chan, J. C. N., Lim, L.-L., Wareham, N. J., Shaw, J. E., Orchard, T. J., Zhang, P., Lau, E. S. H., Eliasson, B., Kong, A. P. S., Ezzati, M., Aguilar-Salinas, C. A., Mcgill, M., Levitt, N. S., Ning, G., So, W.-Y., Adams, J., Bracco, P., Forouhi, N. G., Gregory, G. A., Guo, J., Hua, X., Klatman, E. L., Magliano, D. J., Ng, B.-P., Ogilvie, D., Panter, J., Pavkov, M., Shao, H., Unwin, N., White, M., Wou, C., Ma, R. C. W., Schmidt, M. I., Ramachandran, A., Seino, Y., Bennett, P. H., Oldenburg, B., Gagliardino, J. J., Luk, A. O. Y., Clarke, P. M., Ogle, G. D., Davies, M. J., Holman, R. R., & Gregg, E. W. (2020). The Lancet Commission on diabetes: using data to transform diabetes care and patient lives. The Lancet, 396(10267), 2019-2082.
Chunsong, B., Khalid, U., Binyamin, M. A., & Ali, J. (2024). Revolutionizing diabetes care with innovative decision-making using cubic intuitionistic fuzzy Schweizer and Sklar power aggregation operators. Heliyon, 10(12), 1-17.
Cruz, I. A., Silva, A. G., Soares, P., Oliveira, I., Serrano, J. a. V., & Cunha, J. P. (2002). Modelling the hospital into the future with UML. International journal of healthcare technology and management, 4(3-4), 193-204.
Feeley, T., Landman, Z., & Porter, M. (2020). The Agenda for the Next Generation of Health Care Information Technology. NEJM Catalyst, 1, 14-19.
Fowler, M. (2004). UML distilled: a brief guide to the standard object modeling language. Addison-Wesley, New York.
Gerwer, J. E., Bacani, G., Juang, P. S., & Kulasa, K. (2022). Electronic Health Record–Based Decision-Making Support in Inpatient Diabetes Management. Curr Diab Rep, 22(9), 433-440.
Ghiasi, Y., Seifbarghy, M., & Pishva, D. (2024). Diabetes detection via machine learning using four implemented spanning tree algorithms. Journal of Optimization in Industrial Engineering, 17(1), 1-16.
Gray, J. A. (2007). Better value healthcare--the 21st century agenda. Z Arztl Fortbild Qualitatssich, 101(5), 344-346.
Harris, S. B., Cheng, A. Y. Y., Davies, M. J., Gerstein, H. C., Green, J. B., & Skolnik, N. (2020). Person-Centered, Outcomes-Driven Treatment: A New Paradigm for Type 2 Diabetes in Primary Care. ADA Clinical Compendia, 2-4.
Huang, X., Piao, S., Rong, X., Zhu, Q., Zhan, H., Jin, Y., & Guo, J. (2023). Comparative Diagnosis Test Accuracy of Five Weighting Methods for Type 2 Diabetes Mellitus with Dampness-heat Syndrome. Journal of Traditional Chinese Medicine, 1981-1987.
Iom (2009). Leadership Commitments to Improve Value in Health Care: Finding Common Ground: Workshop Summary. The National Academies Press, Washington, DC.
Ispor1 (2016). Multiple Criteria Decision Analysis for Health Care Decision Making--An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force. Value Health, 19(1), 1-13.
Ispor2 (2016). Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force. Value Health, 19(2), 37-125.
Kahramfar, A., Baradaran Kazemzadeh, R., & Kahramfar, Z. (2014). Application of Porter's value analysis model for Diabetes Mellitus patients: Case Hamedan Beheshti hospital RJMS, 21(121), 18-29.
Kasper, D. L., Editor (2015). Harrison's principles of internal medicine. 19th, McGraw Hill Education Medical, New York
Ke, X., Maria, A. G., Julien, D., Natalja, E., Chandika, I., Joseph, K., Dongxue, W. L., Lachlan, M., Laura, R., Andrew, S., Hapsatou, T., Ningze, X., & Eva, Z. (2022). Global spending on health Rising to the pandemic’s challenges. World Health Organization, Switzerland.
Keehan, S. P., Fiore, J. A., Poisal, J. A., Cuckler, G. A., Sisko, A. M., Smith, S. D., Madison, A. J., & Rennie, K. E. (2023). National Health Expenditure Projections, 2022–31: Growth To Stabilize Once The COVID-19 Public Health Emergency Ends. Health Affairs, 42(7), 886-898.
Khalil, H., Ameen, M., Davies, C., & Liu, C. (2025). Implementing value-based healthcare: a scoping review of key elements, outcomes, and challenges for sustainable healthcare systems. Frontiers in Public Health, 13, 1-11.
Loftus, S., Higgs, J., Jensen, G., & Christensen, N. (2021). Clinical reasoning in the health professions. 4th, Elsevier, New York
Lopez, D. M., & Blobel, B. (2009). Enhanced semantic interoperability by profiling health informatics standards. Methods of information in medicine, 48(02), 170-177.
Magliano, D. J., Boyko, E. J., & Idf (2021). Diabetes Atlas 10th edition scientific committee. 10th, International Diabetes Federation, Brussels, Belgium.
Marrero, D. G., Parkin, C. G., Aleppo, G., Hirsch, I. B., Mcgill, J., Galindo, R. J., Kruger, D. F., Levy, C. J., Carlson, A. L., & Umpierrez, G. E. (2025). The role of advanced technologies in improving diabetes outcomes. Am J Manag Care, 31(4), e102-e112.
Martin, M., Champion, R., Kinsman, L., & Masman, K. (2011). Mapping patient flow in a regional Australian emergency department: A model driven approach. International Emergency Nursing, 19(2), 75-85.
Mintzberg, H. (1987). The Strategy Concept I: Five Ps for Strategy. California Management Review, 30(1), 4-5.
Mintzberg, H., Raisinghani, D., & Théorêt, A. (1976). The Structure of "Unstructured" Decision Processes. Administrative Science Quarterly, 21(2), 246-275.
O'hara, N. N., & Mwayafu, D. (2021). Evidence‐Based Orthopedics. 2nd Edition, Wiley-Blackwell (Verlag), Germany.
Ofstad, E. H., Frich, J. C., Schei, E., Frankel, R. M., & Gulbrandsen, P. (2016). What is a medical decision? A taxonomy based on physician statements in hospital encounters: a qualitative study. BMJ Open, 6(2), 3-4.
Oh, S.-H., Lee, S. J., Noh, J., & Mo, J. (2021). Optimal treatment recommendations for diabetes patients using the Markov decision process along with the South Korean electronic health records. Sci Rep, 11(1), 6920.
Porter , M. E. (2010). What Is Value in Health Care? New England Journal of Medicine, 363(26), 2477-2481.
Porter Michael, E., & Lee Thomas, H. (2020). Integrated Practice Units: A Playbook for Health Care Leaders. NEJM Catalyst, 2(1), 5-7.
Raghupathi, W., & Umar, A. (2008). Exploring a model-driven architecture (MDA) approach to health care information systems development. International journal of medical informatics, 77(5), 305-314.
Sahoo, P. M., Rout, H. S., & Jakovljevic, M. (2023). Future health expenditure in the BRICS countries: a forecasting analysis for 2035. Globalization and Health, 19(1), 49.
Sarani Rad, F., Amiri, M., & Li, J. (2024). Optimizing Nutritional Decisions: A Particle Swarm Optimization–Simulated Annealing-Enhanced Analytic Hierarchy Process Approach for Personalized Meal Planning. Nutrients, 16(18), 3117.
Shomali, M., Mora, P., Aleppo, G., Peeples, M., Kumbara, A., Macleod, J., & Iyer, A. (2024). The critical elements of digital health in diabetes and cardiometabolic care. Frontiers in Endocrinology, 15, 1-10.
Sox, H. C., Higgins, M. C., & Owens, D. K. (2013). Medical Decision Making. 2nd edition, John Wiley & Sons, Ltd, West Sussex, UK.
Stewart, M., Brown, J. B., Weston, W. W., Ryan, B. L., Mcwhinney, I. R., Mcwilliam, C. L., & Freeman, T. R. (2024). Patient-centered medicine: Transforming the clinical method. 4th edition, CRC Press, New York.
Unhelkar, B. (2017). Software Engineering with UML. 1st edition, Auerbach Publications., New York.
Van Der Poort, E. K. J., Kidanemariam, M., Moriates, C., Rakers, M. M., Tsevat, J., Schroijen, M., Atsma, D. E., Van Den Akker-Van Marle, M. E., Bos, W. J. W., & Van Den Hout, W. B. (2024). How to Use Costs in Value-Based Healthcare: Learning from Real-life Examples. J Gen Intern Med, 39(4), 683-689.
Vukobrat, N., Rukavina, D., Pavelić, K., & Sander, G. (2019). Personalized Medicine in Healthcare Systems Legal, Medical and Economic Implications. Springer, Cham, Switzerland.
Xu, K. (2023). Global spending on health: coping with the pandemic. World Health Organization, Geneva.
Yin, R. K. (2018). Case Study Research and Applications: Design and Methods. Sixth Edition, SAGE Publications, London.
