Author : Ahmad Azhar Misran, Wan Muhamad Amir W Ahmad, Nor Farid Mohd Noor, Wan Mohd Nazlee Wan Zainon, Nor Azlida Aleng, Farah Muna Mohamad Ghazali, Nuzlinda Abdul Rahman, Norsamsu Arni Samsudin, Mohd Nasarudin Adnan,

Abstract : The present study aims to determine the trend of patient attendance pre- and post-COVID-19 pandemic at the outpatient dental clinic of Hospital Universiti Sains Malaysia (Hospital USM), Kelantan, Malaysia. This is a retrospective study. This paper, in retrospect, reviews the total number of patients seeking treatment at the dental outpatient clinic, Hospital USM, with interest in the trends of patient attendance from 2017 (pre-pandemic) to 2020 (post-pandemic of COVID-19). Data were collected from the monthly total patient registry from the dental services department of Hospital USM. The IBM SPSS Version 26.0 was used for trend analysis. Meanwhile, the Minitab software determines the trendline of patient attendance and the Seasonal ARIMA analysis predicts the patient attendance for the following year. The analysis found that the year 2020 decreased in trend due to the global coronavirus pandemic. According to the seasonal trend from 2017 to 2020, the SARIMA (0,0,0) (1,1,1)12 model was selected. For 2021, the prediction value is performed monthly. This 30-day period is essential for further preliminary actions by the Hospital USM in planning the strategy to handle patients efficiently during the COVID-19 post-pandemic. The patient attendance is represented in the Seasonal Autoregressive Integrated Moving Averages (SARIMA). The coefficient for SARIMA was significant, indicating that this proposed model is a superior method.

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