Statistical analysis of waiting time of patients by queuing techniques: case study of large hospital in Pakistan

Abstract

<p class="JARTEAbstractHeader">The purpose of this empirical research was to analyze the comfortable waiting time (CWT) of patients at the outpatient department (OPD) of Gastrology of ABC hospital of Karachi. It is based on the analysis of CWT of patients who were being served at the OPD of Gastrology of ABC hospital of Karachi. The data was collected by the help of questionnaire. Altogether 250 questionnaires were distributed among the patients, 210 of them were collected back and 10 of them were incompletely filled. Data was analysed in the statistical package for social sciences (SPSS) version 22. Data analysis included frequency distribution of various demographics;stratification tables were made for the comparison of CWT across various demographics. Results indicated that more females (old aged) had greater CWT in the comparison of males. It is found that the mean CWT of patients decreased with decreasing age, increasing OPD visiting time and increasing income. It is also found that he mean CWT for the patients from Afghanistan was greater than the patients from other regions i.e. Baluchistan, interior Sindh and Karachi. The authors highlighted that when patients arrive at the hospital and wait for their service, in this scenario, waiting cost is associated with their waiting time; since it is the matter of cost, thus it should be known to the hospital that if patients are made to wait longer, it can lead to the customer dissatisfaction. In this regard, analysis of comfortable waiting time of patients was extremely needed. Since, Karachi is the biggest city of Pakistan and targeted hospital is one the biggest private hospitals of Karachi and in the analysis of this paper. Only 200 patients were approached for data collection which is the main limitation of the paper. In future, the researchers should also focus on the same OPD for more responses and at the same time, other departments can also be targeted for conclude better and precise results. The authors have tried to focus on the CWT of patients so that the waiting capacity of patients could be highlighted. At the same time, detailed analysis was conducted across demographics so that their influence on CWT could be analysed.</p><p class="JARTEKeywords"> </p>

Development of linear programming model for optimization of product mix and maximization of profit: case of leather industry

“…Still, the percent of land use might boost up to 30.7% when the most affordable and also the highest diversification scenarios were contrasted (Woubante, 2017). The queue is prevalent in day to day life (Kalwar et al, 2018;Kalwar, Mari, et al, 2020;Kalwar, Memon, et al, 2021;Khan, Khaskheli, et al, 2021b, 2021aKhaskheli et al, 2020). Solaja et al, (2019) conducted their research in feed production mills; he suggested that choice makers ought to not base their decision on experience and intuition, yet on the analytical and also technical approach.…”

“…In operations research, different techniques are used for simplification of industrial issues i.e. management of the queuing system by use of queuing theory (Kalwar, Khaskheli, Khan, Siddiqui, & Gopang, 2018;Kalwar, Mari, Memon, Tanwari, & Siddiqui, 2020;Kalwar, Marri, Khan, & Khaskheli, 2021;Kalwar, Memon, Khan, & Tanwari, 2021;Khan, Khaskheli, et al, 2021a, 2021bKhaskheli, Marri, Nebhwani, Khan, & Ahmed, 2020), efficient allocation of resources by use of linear programming (Addy, 2014;Akpan & Iwok, 2016;Alvfors & Björelind, 2015;Aregawi, 2018;Gameiro, Rocco, & Caixeta Filho, 2016;Jain, Bhardwaj, Saxena, & Choubey, 2019;Jyothi, Rao, & Sivasundari, 2019;Maurya, Misra, Anderson, & Shukla, 2015;Tesfaye, Berhane, Zenebe, & Asmelash, 2016;Workie, Alemu A, & Asmelash, 2016;Woubante, 2017;Yoanita, 2016;Yu, 2015;Yue, 2013), and so on. Optimization and Operational research methods are thoroughly used to acquire better options and decisions to industrial issues (Jyothi et al, 2019;Nawrocki, 2013).The industrial development strategy is identified by the reliable use of resources at every production stage.…”

Automation of order costing analysis by using Visual Basic for applications in Microsoft Excel

“…Because of manual reporting in Microsoft Excel, a lot of time was used to be spent on the formation of reports, and the purchasing department used to wait because of many order costing reports in the queue. Since, waiting cost is associated with queues (Kalwar et al, 2018;Kalwar, Mari, et al, 2020;Kalwar, Memon, et al, 2021;Khan, Khaskheli, et al, 2021a, 2021bKhaskheli et al, 2020), thus it was decided to automate the order costing report. The procedure to make an order costing report was manual e.g.…”