Abstract




 
   

IJE TRANSACTIONS C: Aspects Vol. 30, No. 9 (August 2017) 1290-1299    Article in Press

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  CASE MIX PLANNING USING TOPSIS AND ROBUST ESTIMATION: A CASE STUDY
 
R. Shafaei and A. Mozdgir
 
( Received: December 27, 2016 – Accepted: July 07, 2017 )
 
 

Abstract    Management of surgery units and operating room (OR) play key roles in optimizing the utilization of hospitals. On this line Case Mix Planning (CMP) is normally applied to long term planning of OR. This refers to allocating OR time to each patient’s group. In this paper a mathematical model is applied to optimize the allocation of OR time among surgical groups. In addition another technique is applied to provide an Order of Preference by Similarity to Ideal Solution (TOPSIS) considering different hospital performance measures. Furthermore, robust estimation approach is used to estimate of the models\\\' parameters using real data. The proposed model is solved using GAMS software. The results of the study performed in this paper reveal that the proposed methods results in an increase in total hospital operated “value of patients” by 21.5%. This value is defined according to hospital priority and is include moral and ethical considerations. In addition, for each resource, a sensitivity analysis of the findings to the changes is conducted. The results of the performed sensitivity analysis indicated that the value of the objective function significantly increased via reallocating OR time to surgical groups and/or enhancing the OR facilities to support more surgical specialties.

 

Keywords    Case mix planning problem, Mathematical programming, TOPSIS, Sensitivity analysis, Robust estimation.

 

چکیده    مدیریت بخش‌های جراحی و اتاق‌های عمل نقشی کلیدی در استفاده بهینه از بیمارستان‌ها دارد. در این حوزه مساله “تعیین ترکیب بیماران” معمولا در برنامه ریزی بلند مدت اتاق‌های عمل مورد بررسی قرار می‌گیرد. این مساله عبارتست از تخصیص ظرفیت اتاق‌های عمل به گروه‌های مختلف بیماران. در این مقاله از یک مدل برنامه‌ریزی ریاضی جهت تخصیص بهینه ظرفیت اتاق‌های عمل به گروه‌های مختلف جراحی استفاده شده است. بعلاوه از روش رتبه بندی TOPSIS به منظور رتبه بندی گروه‌های مختلف جراحی بر اساس شاخص‌های مختلف عملکردی بیمارستان استفاده گردیده است. هچنین رویکرد برآورد کننده‌های استوار جهت برآورد پارامترهای مساله بر اساس داده‌های واقعی مورد استفاده قرار گرفته است. سپس مدل توسعه داده شده توسط نرم افزار GAMS حل گردیده است. نتایج بدست آمده حاصل از حل مدل آشکار می‌سازد که شاخص ارزش بیماران جراحی شده نسبت به وضعیت فعلی بیمارستان 21.5% افزایش می یابد. این شاخص بر اساس الویت‌های بیمارستان تعریف گردیده است و شامل ملاحظات اخلاقی می‌باشد. بعلاوه جهت بررسی حساسیت مدل به تغییر در منابع در دسترس، به تحلیل حساسیت مدل پرداخته شده است. نتایج حاصل از تحلیل حساسیت صورت گرفته نشان می‌دهد که میزان تابع هدف مساله بطور قابل ملاحظه‌ای با افزایش قابلیت اتاق‌های عمل جهت پشتیبانی گروه‌های مختلف جراحی بهبود می‌یابد.

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