زمانبندی بیماران همودیالیز با درنظر گرفتن ترجیحات بیمار
نویسندگان
دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه صنعتی اصفهان
چکیده
امروزه ارائه‌دهندگان خدمات به بیماران سرپایی با فشار برای کاهش هزینه‌های جاری و افزایش کیفیت خدمات رو‌به‌رو هستند. یکی از بخش‌های ارائه‌دهنده خدمات به بیماران سرپایی، بخش همودیالیز است که با منابع و تجهیزات گران‌‌قیمتی رو‌به‌رو است. لذا در مقاله حاضر، زمانبندی بیماران همودیالیز با درنظر گرفتن ترجیحات آنها مورد بررسی قرار گرفته است. هدف از زمانبندی بیماران همودیالیز در این پژوهش، کمینه‌سازی مجموع وزنی نرمال شده انحراف از ترجیحات بیماران و مجموع زمان تکمیل آنها است. لازم به‌ذکر است که ترجیحات بیمار شامل تخت، ترکیب روزهای درمانی و نوبت آنها می‌شود. برای حل مسئله، دو مدل ریاضی ارائه شده است. کارایی مدل‌های ارائه شده با توجه به اطلاعات واقعی که از بخش همودیالیز بیمارستان امام خمینی(ره) کرمانشاه گرفته شده، بررسی شده است. نتایج گویای کارایی روش‌های ارائه شده در رعایت کردن ترجیحات عنوان شده از بیماران بوده اما رعایت ترجیحات بیماران در برنامه بیمارستان به‌صورت موردی و در‌صورت امکان لحاظ کردن ترجیحات، انجام شده است. به‌طوری که می‌توان گفت این ترجیحات در برنامه‌ریزی بیمارستان در اولویت قرار نداشته است. این در‌حالی است که علاوه بر رعایت ترجیحات، در جواب مدل‌ها، مجموع زمان تکمیل درمان بیماران نیز کاهش یافته است. همچنین یکی از مدل‌های ارائه شده در این مقاله قادر است مسائل با ابعاد حدود سه برابر بیمارستان مورد مطالعه را در مدت‌زمان کمی به‌طور بهینه حل کند.
کلیدواژه‌ها
عنوان مقاله [English]
Scheduling Hemodialysis Patients with Patient Preferences
نویسندگان [English]
- S. M. Navabi
- M. Reisi-Nafchi
- Gh. Moslehi
Nowadays, outpatient providers are struggling to reduce the current costs and improve the service quality. A part of the outpatient service provider is a hemodialysis department with expensive supplies and equipment. Therefore, in the present paper, the scheduling of hemodialysis patients with their preferences has been studied. The aim of scheduling hemodialysis patients in this study is to minimize the normalized weighted sum of deviations from the patients' preferences and the total completion time. It should be noted that the patient's preferences include beds, treatment combination of days and their turn. To solve the problem, two mathematical models have been presented. Performence of the models in solving the real data of the hemodyalisis department of Imam Khomeini Hospital, in Kermanshah, was investigated. The results showed the efficiency of the proposed models in considering the preferences of patients; however, these preferences in the hospital schedule were considered in few cases, as far as it was possible. So, these preferences has no priority in the hospital schedule. In addition to considering the patients’ preferences, the solution of models reduced the total completion time of the pationts treatment. Also, one of the proposed models in this papercould optimally solve the instances three times larger than the hospital cases
کلیدواژه‌ها [English]
- Scheduling
- Appointment
- Hemodialysis
- mathematical model
- Patient preferences
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12. Azadeh, A., Baghersad, M., Farahani, M. H., and Zarrin, M., “Semi-Online Patient Scheduling in Pathology Laboratories”, Artificial Intelligence in Medicine, Vol. 64, pp. 217-226, 2015.
13. Ogulata, S. N., Cetik, M. O., Koyuncu, E., and Koyuncu, M., “A Simulation Approach for Scheduling Patients in the Department of Radiation Oncology”, Journal of Medical Systems, Vol. 33, pp. 233, 2009.
14. Condotta, A., and Shakhlevich, N., “Scheduling Patient Appointments via Multilevel Template: A Case Study in Chemotherapy”, Operations Research for Health Care, Vol. 3, pp. 129-144, 2014.
15. Castro, E., and Petrovic, S., “Combined Mathematical Programming and Heuristics for a Radiotherapy Pre-Treatment Scheduling Problem”, Journal of Scheduling, Vol. 15, pp. 333-346, 2012.
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25. Holland, J., “Scheduling Patients in Hemodialysis Centers”, Production and Inventory Management Journal, Vol. 35, p. 76, 1994.
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28. Shateri, M., “Resource Allocation and Risk Analysis of Dialysis Centres”, PhD Thesis Department of Mechanical and Industrial Engineering, University of Toronto, 2015
2. Petrovic, S., Leung, W., Song, X., and Sundar, S., “Algorithms for Radiotherapy Treatment Booking”, Proceedings of the 25th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG’2006), Nottingham, UK, pp. 105-112, 2006.
3. Zhong, L., Luo, S., Wu, L., Xu, L., Yang, J., and Tang, G., “A Two-Stage Approach for Surgery Scheduling”, Journal of Combinatorial Optimization, Vol. 27, pp. 545-556, 2014.
4. Jha, V., Garcia-Garcia, G., Iseki, K., Li, Z., Naicker, S., Plattner, B., Saran, R., Wang, A. Y. -M., and Yang, C. -W., “Chronic Kidney Disease: Global Dimension and Perspectives”, The Lancet, Vol. 382, pp. 260-272, 2013.
5. Wetmore, J. B., and Collins, A. J., “Global Challenges Posed by the Growth of End-Stage Renal Disease”, Renal Replacement Therapy, Vol. 2, p. 15, 2016.
6. Power, A., Duncan, N., and Goodlad, C., “Management of the Dialysis Patient for the Hospital Physician”, Postgraduate Medical Journal, Vol. 85, pp. 376-381, 2009.
7. Klassen, K. J., and Rohleder, T. R., “Scheduling Outpatient Appointments in a Dynamic Environment”, Journal of Operations Management, Vol. 14, pp. 83-101, 1996.
8. Ahmadi-Javid, A., Jalali, Z., and Klassen, K. J., “Outpatient Appointment Systems in Healthcare: A Review of Optimization Studies”, European Journal of Operational Research, Vol. 258, pp. 3-34, 2017.
9. Cayirli, T., and Veral, E., “Outpatient Scheduling in Health Care: A Review of Literature”, Production and Operations Management, Vol. 12, pp. 519-549, 2003.
10. Gupta, D., and Denton, B., “Appointment Scheduling in Health Care: Challenges and Opportunities”, IIE Transactions (Institute of Industrial Engineers), Vol. 40, pp. 800-819, 2008.
11. Saremi, A., Jula, P., ElMekkawy, T., and Wang, G. G., “Appointment Scheduling of Outpatient Surgical Services in a Multistage Operating Room Department”, International Journal of Production Economics, Vol. 141, pp. 646-658, 2013.
12. Azadeh, A., Baghersad, M., Farahani, M. H., and Zarrin, M., “Semi-Online Patient Scheduling in Pathology Laboratories”, Artificial Intelligence in Medicine, Vol. 64, pp. 217-226, 2015.
13. Ogulata, S. N., Cetik, M. O., Koyuncu, E., and Koyuncu, M., “A Simulation Approach for Scheduling Patients in the Department of Radiation Oncology”, Journal of Medical Systems, Vol. 33, pp. 233, 2009.
14. Condotta, A., and Shakhlevich, N., “Scheduling Patient Appointments via Multilevel Template: A Case Study in Chemotherapy”, Operations Research for Health Care, Vol. 3, pp. 129-144, 2014.
15. Castro, E., and Petrovic, S., “Combined Mathematical Programming and Heuristics for a Radiotherapy Pre-Treatment Scheduling Problem”, Journal of Scheduling, Vol. 15, pp. 333-346, 2012.
16. Conforti, D., Guerriero, F., and Guido, R., “Optimization Models for Radiotherapy Patient Scheduling”, 4OR, Vol. 6, pp. 263-278, 2008.
17. Conforti, D., Guerriero, F., and Guido, R., “Non-Block Scheduling with Priority for Radiotherapy Treatments”, European Journal of Operational Research, Vol. 201, pp. 289-296, 2010.
18. Sevinc, S., Sanli, U. A., and Goker, E., “Algorithms for Scheduling of Chemotherapy Plans”, Computers in Biology and Medicine, Vol. 43, pp. 2103-2109, 2013.
19. Liang, B., and Turkcan, A., “Acuity-Based Nurse Assignment and Patient Scheduling in Oncology Clinics”, Health Care Management Science, Vol. 19, pp. 207-226, 2016.
20. Van de Vrugt, N., Luen-English, S., Bastiaansen, W., Kleinluchtenbeld, S., Lardinois, W., Pots, M., Schoonbergen, D., Hans, E. W., Hurink, J. L., and Boucherie, R. J., “Integrated Scheduling of Tasks and Gynecologists to Improve Patient Appointment Scheduling; a Case Study”, Operations Research for Health Care, Vol. 16, pp. 10-19, 2018.
21. Qu, X., Peng, Y., Kong, N., and Shi, J., “A Two-Phase Approach to Scheduling Multi-Category Outpatient Appointments-A Case Study of a Women’s Clinic”, Health Care Management Science, Vol. 16, pp. 197-216, 2013.
22. Savelsbergh, M., and Smilowitz, K., “Stratified Patient Appointment Scheduling for Mobile Community-Based Chronic Disease Management Programs”, IIE Transactions on Healthcare Systems Engineering, Vol. 6, pp. 65-78, 2016.
23. Hulshof, P. J., Boucherie, R. J., Hans, E. W., and Hurink, J. L., “Tactical Resource Allocation and Elective Patient Admission Planning in Care Processes”, Health Care Management Science, Vol. 16, pp. 152-166, 2013.
24. Bikker, I. A., Kortbeek, N., van Os, R. M., and Boucherie, R. J., “Reducing Access Times for Radiation Treatment by Aligning the Doctor’s Schemes”, Operations Research for Health Care, Vol. 7, pp. 111-121, 2015.
25. Holland, J., “Scheduling Patients in Hemodialysis Centers”, Production and Inventory Management Journal, Vol. 35, p. 76, 1994.
26. Tolentino Peña, M., “Optimization of Inpatient Hemodialysis Scheduling Considering Efficiency and Treatment Delays to Minimize Length of Stay”, MSc Thesis, Department of Industrial & Systems Engineering, Kate Gleason College of Engineering, 2013.
27. Vanquickenborne, N., “Analysis, Redesign and Implementation of a Dialysis Process”, MSc Thesis Department of Industrial & Economic Engineering, Ghent University, 2015
28. Shateri, M., “Resource Allocation and Risk Analysis of Dialysis Centres”, PhD Thesis Department of Mechanical and Industrial Engineering, University of Toronto, 2015
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