A cost analysis with the discrete-event simulation application in nurse and doctor employment management


Atalan A.

Journal of Nursing Management, vol.30, no.3, pp.733-741, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30 Issue: 3
  • Publication Date: 2022
  • Doi Number: 10.1111/jonm.13547
  • Journal Name: Journal of Nursing Management
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, CINAHL, EMBASE, MEDLINE, Psycinfo, Public Affairs Index
  • Page Numbers: pp.733-741
  • Keywords: discrete event simulation, doctors, emergency department, nurses, treatment cost
  • Çanakkale Onsekiz Mart University Affiliated: No

Abstract

Aim: This study aimed to analyse the treatment cost of a patient, depending on the number of patients treated, patient waiting times, and the number of nurses and doctors employed in an emergency department of a private hospital. Background: Within health systems, changes in health care resources can be very costly, especially if these changes are long-term. The discrete-event simulation method described in this paper allows for the monitoring and analysis of complicated changes in real systems by using computer-based modelling. Method: The discrete event simulation model was derived from nine scenarios according to the number of nurses and doctors, and a comparison was made between the results of the scenarios and the actual results. Results: Among the scenarios, scenario 6 provided the lowest treatment cost for a patient by employing three doctors and two nurses with the best performance. The cost of treatment for a patient varies between ŧ9.00 and ŧ11.00 depending on the value of δ, and the daily cost of these resources to the hospital is ŧ1300.77. Conclusions: This study provides a clear picture of a cost analysis comparison based on changes made about the actual health system in the computer-based simulated environment. Implications for Nursing Management: The workforce data of nurses and doctors offers enough detail for cost analysis in health care settings to calculate the cost of treatment for a patient.