Time-series forecasting analysis on the major treatment need among patients referred for periodontal and conservative treatments in IIUM dental outpatient clinic

• Main Authors: Ismail, Azlini, Abllah, Zurainie, Muhammad Radhi, Nur Aishah, Musa, Syazalina, Abdul Halim, Mohd Firdaus Akbar
• Format: Article
• Language: English; English
• Published: Wolters Kluwer Health 2021
• Subjects: QA276 Mathematical Statistics; QA297 Numerical Analysis; RK Dentistry
• Online Access: http://irep.iium.edu.my/92975/3/Web%20of%20Science%20Master%20Journal%20List%20-%20JIOH.pdf; http://irep.iium.edu.my/92975/19/92975_Time-series%20forecasting%20analysis.pdf; http://irep.iium.edu.my/92975/; https://www.jioh.org/article.asp?issn=0976-7428;year=2021;volume=13;issue=5;spage=485;epage=492;aulast=Ismail;type=3
• Institution: Universiti Islam Antarabangsa Malaysia

Aim: To identify the trend for major treatment needs among patients referred for conservative and periodontal treatments upon screening at Dental Outpatient Clinic, International Islamic University Malaysia, and to forecast the future need for this treatment using time-series forecasting analysis. Materials and Methods: This retrospective cross-sectional study used records of all patients referred for periodontal and conservative treatments from January 1, 2014 until December 31, 2016. The retrieved information includes patient’s age, gender, residential areas, and their treatment needs. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) software program, version 20.0 (SPSS Inc., Chicago, IL, USA). The number of patients requiring each treatment need was counted, and the major treatment need was identified. For the time-series analysis, the weekly data for the major treatment need were fitted using few univariate models (moving-average, single-exponential, double-exponential, and Holt’s) in Minitab software version 17.0 (Minitab, LLC, State College, PA, USA) and the best-fitted model was chosen for forecasting the future need of this treatment. Results: From 3388 patients, majority were women (59.2%), aged 20–34 years old (54.5%), and came from urban areas (42.4%). The major treatment needs were scaling-polishing (65.0%) and dental filling (74.1%), respectively. The 3-year weekly pattern for both time series showed no apparent seasonal component. Using the best-fit moving-average model, it is forecasted that the 741 patients per year will require scaling-polishing and 855 patients per year will require dental-filling for the following years. Conclusions: The trends for scaling-polishing and dental-filling need among this population were nonseasonal, and the future needs were forecasted to remain high as in previous years.