General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • APC: 800 USD
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Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2023 Vol.15(1): 10-37
DOI: 10.7763/IJCTE.2023.V15.1327

Hospital Bed-Capacity and Emergency-Physician Risk Management — Strategies to Design Pandemic Contingency Plans

Mehmet Sahinoglu* and Ferhat Zengul

Manuscript received April 11, 2022; revised August 29, 2022; accepted September 13, 2022.

Abstract—This article employs a discrete event simulator, CLOURAM (Cloud Risk Assessor and Manager), so to estimate risk indices in modern-day Cloud computing setting applicable to Hospital Healthcare Service Networks. This innovative approach has not been implemented earlier using a Cloud framework for digital queuing simulation. The article also innovatively examines emergency-physician management strategy through MCQS (Multi-Channel Queuing Simulation) and Hospital Scheduling. The macro-level goal is to assess and manage risk with tangible mitigation targets and to improve the operational quality of interconnected health care services for crucial needs such as improving the critical bed-count and dire physician-availability to meet growing demands towards designing pandemic contingency plans. The proposed methods are applied to five randomly selected States. The raw data originated from the national repository of States’ hospital networks. Such in-depth analyses not only assess the bed- and physician-inadequacy risk, but also foster feasibility plans by conducting cost and benefit analysis for future provisions of infrastructural needs to improve networked-healthcare services with cost-saving justifications. The results indicate that if physician-scarcities’ and bed-shortfalls’ admission and discharge input data can be traced to the States’ healthcare networks, the administrative and financial analysts can timely benefit from proactive digital simulations. JIT (Just-in-time) simulations would similarly help toward the States’ CON (Certificate of Need) laws, which require the capital expenditures’ approval by State health planning agencies to avoid unnecessary duplications of healthcare investment against wasteful practices.

Index Terms—Simulation software, hospitals national repository, cost and benefit, physician- and bed-capacity, emergency, risk

Mehmet Sahinoglu is with Computer Science Dept., Troy University, Troy, AL 36082, USA.
Ferhat Zengul is with Dept. of Health Admin. Health Care Management Program, the University of Alabama at Birmingham (UAB), Birmingham, AL 35294, USA.


Cite:Mehmet Sahinoglu and Ferhat Zengul, "Hospital Bed-Capacity and Emergency-Physician Risk Management — Strategies to Design Pandemic Contingency Plans ," International Journal of Computer Theory and Engineering vol. 15, no. 1, pp. 10-37, 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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