Neuro-critical Care Unit Bed Allocation Optimization based on Hybrid Approach: Designing of Experiments and Simulation

سابقه و هدف: واحد مراقبت‌های ویژه مغز و اعصاب به مراقبت از بیماران دچار شرایط بحرانی و تهدید کننده حیات در زمینه بیماری های مغز و اعصاب اختصاص دارد و از آنجایی‌که با محدودیت منابع جهت افزایش تخت های مراقبت های ویژه و همچنین افزایش زمان انتظار بیماران در این بخش رو به رو می باشیم نیازمند دستیابی به بهینه ترین ترکیب ممکن برای تخصیص تخت ها به هر نوع از بیماران و تعداد تخت در بخش مراقبت های ویژه می باشیم. لذا در این مطالعه برای استفاده بهینه از تخت ها و نیز به منظور کاهش متوسط زمان انتظار بیماران در بخش مراقبت‌های ویژه مغز و اعصاب مرکز پزشکی، آموزشی درمانی لقمان حکیم وابسته به دانشگاه علوم پزشکی شهید بهشتی به شبیه سازی بخش مورد نظر پرداخته تا ترکیب بهینه تخت های موجود در این بخش حاصل شود. روش بررسی: در این مطالعه ابتدا ترکیب تخصیص تخت های بخش مراقبت های ویژه مغز و اعصاب بیمارستان لقمان حکیم به هر دسته از بیماری ها مشخص شد و با استفاده از نرم افزار طراحی آزمایشات بهینه ترین ترکیب های ممکن بدست آمد. سپس ترکیب های بدست آمده شبیه سازی شده و دو معیار میانگین زمان انتظار در صف برای بیماران و میزان بهره وری (اشغال تخت) برای هر یک از ترکیب ها محاسبه شد. پس از آن مدل ریاضی شامل اهداف کمینه سازی متوسط ​​زمان انتظار بیماران در صف و همچنین میانگین بهره وری تخت ها با استفاده از روش پاسخ خطی ارائه شد. نتایج: بر اساس نتایج، تعداد بهینه انواع تخت های مورد استفاده در این بخش به ترتیب برابر با شش، دو، سه، سه و دو تخت برآورد شدند که منجر به متوسط زمان انتظار 1.4 ساعتی بیماران و نیز متوسط بهره وری 34.5 درصدی مجموع تخت ها شد. نتیجه‌گیری: نتایج مطالعه حاضر بیانگر این واقعیت است که بهینه سازی تخصیص تخت در بخش مراقبت‌های ویژه مغز و اعصاب با بکارگیری رویکرد ترکیبی شبیه سازی و طراحی آزمایشات ، باعث کاهش متوسط زمان انتظار بیماران و به تبع آن افزایش بهره وری (درصد اشتغال به کار) تخت ها می شود. How to cite this article: Goharani R, Shafagh-sorkh O, Nateghinia S, Hajiesmaeili M, Alibabaei A, Shafigh N. Neuro-critical Care Unit Bed Allocation Optimization based on Hybrid Approach: Designing of Experiments and Simulation. J Saf Promot Inj Prev. 2021; 9(1):9-17.Background & Objectives: Neurological Critical Care Unit is allocated for patients with critical conditions in the field of neurological diseases. ICU beds and their equipment are very expensive and there are some economic constraints for increasing the ICU beds. At the same time, the admission waiting time for patients in this unit is not favorable. Therefore, an initiative for better management of this ward was needed.  The objective of this study was to examine an optimal program for allocating beds to patients, based on their required length of stay in the unit. Methods and Materials: In this study, different categories of patients and their quantity was investigated in the Loghman Hakim hospital. Then, by using the design of experiments technique, optimal combinations were obtained. The obtained combinations were simulated for each of two criteria was calculated; patients' average waiting time and bed occupancy rate. Subsequently, a mathematical model with the objective function of minimizing the average waiting time for patients, as well as the average bed occupancy rate was presented using the linear response method. Results: According to the results of this study, an optimal combination of beds allocation to different categories of patients for the Neurological Critical Care Unit were respectively 6, 2, 3, 3, and 2 beds, and average waiting time was 1.4 hours and an average bed occupancy rate was 34.5%. Conclusion: The present study demonstrated that optimization of bed allocation in ICU by using a combined approach of simulation and design of experiments, resulted in a decrease in average waiting time and increase in bed occupancy rate (bed productivity). How to cite this article: Goharani R, Shafagh-sorkh O, Nateghinia S, Hajiesmaeili M, Alibabaei A, Shafigh N. Neuro-critical Care Unit Bed Allocation Optimization based on Hybrid Approach: Designing of Experiments and Simulation. J Saf Promot Inj Prev. 2021; 9(1):9-17. &nbsp

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Visualizing the demand for various resources as a function of the master surgery schedule: A case study.

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