Introduction

The focus of the article is on the healthcare sector and how to make it more efficient using simulation modelling. By addressing the medical staff workload, the article hopes to enhance patients’ service management and improve the entire process from reception to discharge. The main agenda that the simulation model intends to meet is to identify optimal number of medical staff required per day, deliver the medical care in shortest time possible, and increase the overall efficiency of the institution’s operation.

Description of Real-Life Problem

The problem that is being addressed is a need to improve the efficiency in a clinic where patient service management is somewhat flawed. At present, the system used in the clinic is fairly simple. It includes an introduction of the patient to the clinic system, matching of the patient to their data and information, classification of their health problem, matching them to a doctor (sometimes requiring specialized care), and a monitoring system for the entire process. However, the problem is that at times there can be refusals or delays to patient care depending on the availability of the doctors. Availability depends on the number of patients available, the level of specialization required, and the number of doctors available. Service refusals may emerge if these factors do not align to the incoming number of patients. Therefore, a need to analyse the reasons for refusal of service is required and an understanding of the probability of this aspect emerging. The overall aim is to determine the dependency amongst all of these factors including a need to improve overall patient satisfaction.

Strengths of the Paper

One of the most important and strong points of the paper is that it has a very clear and logical structure that flows very well into each other. It is very easy to follow and each section builds and connects from the preceding part. In the introduction section, the authors begin by giving a relevant background to introduce the research problem. The section ends in a clear description of the purpose statement, allowing the reader to have a better grasp of all the paper is about.

In the materials and methods section, the use of charts and tables is very important in the facilitation of a better understanding of the content. For example, the use of a flow diagram to summarize the clinic’s queuing system sheds light on exactly how the author interprets the system that is already in place and allows the reader to see why improvements are necessary. The objective description is a major component of the paper. It has a detailed description of how the article will convey ideas and concepts to solve the issue proposed in the introduction. It also drives into the interpretation of the said concepts and shows the relationships, dependencies, variables, and how these elements merge to create or solve the problem.

In the critical evaluation, the authors assess the overall ability of the proposed solutions to accomplish its goal methodically and precisely through the many components of the work. For instance, the narrative structure and the development of ideas, the subject selection, the experiment design used, analysis of data, and the conclusions made are all aimed at providing a solution to the identified problem.

Weaknesses of the Paper

One of the notable weaknesses of the paper is that it lacks a section that appreciates extant literature on the subject matter. While this is not important for a primary study, it denies the reader an opportunity to reference what is presented to verifiable data from previous literature. An inclusion of a literature review section would compare the results obtained to what has already been accepted in literature bodies. Another issue is that the discussion section is a bit too broad and the topic sentences are unfocused and inadequate. The conclusion is also very brief and does not capture every aspect of the paper. Overall, the paper passes the message effectively. Another major weakness is that the article’s validity and reliability cannot be proven. While the paper claims that more than 1000 simulation experiments were conducted to ensure validity, the results obtained have not been pegged to previous research or referenced peer-reviewed articles.