1. YOĞUN BAKIM ÜNİTELERİNDE KAPASİTE DEĞERLENDİRMESİ VE PLANLAMASI: 3. BASAMAK HASTANELER İÇİN SİMÜLASYON MODELLEMESİ.
- Author
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DURMUŞ, Alkan, ÖZDEMİR, Ali, and GÖKMEN, Necati
- Subjects
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INTENSIVE care units , *MEDICAL care wait times , *CAPACITY requirements planning , *RESOURCE allocation , *MEDICAL care , *OPTICAL pattern recognition - Abstract
Health systems are human based systems comprising a high number of stakeholders who interact with each other in complex ways. Due to the stochastic nature of health systems and the complex dynamics and interactions of their inputs, processes and outputs; providers of health services require tools tat allow them to comprehend the said complexity and improve system performance. Intensive care units (ICUs) may fall short in treating patients due to insufficient capacity and patients may be transferred to other hospitals under certain circumstances, and waiting times can get longer. Efficient use and management of a scarce resource such as the ICU is of critical importance for trouble-free operation of a hospital. Capacity planning, in other words, determination of optical bed configuration based on current knowledge of future demand and capacity, is very difficult due to high uncertainty in both bed capacity and demand. The paper at hand proposes a simulation model to allow an easier decision-making process in the planning of bed capacity in ICU. The study focuses on improving the capacity planning of a level III university hospital in Turkey that specializes in education and research. The objective of the study is to determine optimal bed requirement by matching the resources of the ICU with demand. We provide forecasts of ICU capacity by evaluating the simulation models based on patient waiting times and bed quantity. Considered in the context of the vital importance of intensive care units and the uncertainties in their management, it is thought that the use of simulation modeling in the making of capacity decisions can prove useful for decision makers in assessing their resource allocation strategies under different regional and hospital conditions. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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