ESTIMATING OPTIMAL RESOURCE ALLOCATION IN THE INPATIENT DEPARTMENT USING SIMULATION AND DATA ENVELOPMENT ANALYSIS; [Menganggar Peruntukan Sumber yang Optimal di Jabatan Pesakit dalam Menggunakan Simulasi dan Analisis Pembangunan Data]

• Published in: Journal of Quality Measurement and Analysis
• Main Author: Rasidi N.F.B.; Yusoff N.S.M.; Shuib A.; Noh A.M.; Adna N.
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202509760&doi=10.17576%2fjqma.2002.2024.06&partnerID=40&md5=40864b82bfb00e9c67cb915eb672ef7c

The inpatient department is one of the important departments at Universiti Sains Malaysia Hospital (HUSM) which ensures that the patients will get their first checkup by the nurse within 15 minutes after getting bed. The inpatient department encounters problems as it wrestles with the long waiting time for patients getting first checkup, and the shortage of nurses and beds in the management of patients. This study demonstrate the application of hybrid method of Discrete Event Simulation (DES) and two types of Data Envelopment Analysis (DEA) specifically the Bi-Objective MCDEA BCC model and the Cross-Efficiency model to determine the most effective resource allocation in the inpatient department. The result of the simulation model has shown that the utilization of nurses per day exceeds 100% and the utilization of beds is relatively higher. Besides, the waiting times for patients to get their checkups are too long that exceeds 15 minutes in the inpatient department. The findings of the research show the number of nurses used in the inpatient department increased from 16 to 18, and the number of beds also increased from 36 to 38. The waiting time for patients to get their first checkup has been reduced to under 15 minutes. These additions and reductions can restore the problems faced by the inpatient department. Lastly, the optimum resource identified will enhance the quality of nurses, beds, and the flow of patients in the inpatient department to meet the Key Performance Indicators (KPI) of HUSM. © 2024, Penerbit Universiti Kebangsaan Malaysia. All rights reserved.