Predicting Outpatient Visits using Time Series Data based on ARIMA Model

  Liv T. Onic,  Minle Mar M. Ayalin,  Hiezyl M. Gorantes,  Jay C. Liza

The purpose of the research is to find out who is visiting the community health center by forecasting patients visits using the ARIMA method, which is very suitable for processing time series data, The time series data of outpatient visits at the Rural Health Unit of the Municipality of Janiuay from January 1, 2020, to August 11, 2022, was gathered through secondary data collection method. Forecasting the health data of the patients using the 95% confidence interval showed that symptoms trended up per day for twenty-one (21) days, resulting in a 16.13% increase, rising by 44.00% in 4 days. The number of symptoms jumped from 25 to 36 during its steepest incline. Acute respiratory tract infection is the most common symptom, followed by urinary tract infection and gastroesophageal reflux disease. Acute respiratory tract infection accounted for 17.83% of all barangays, and adults made up 7.13% of those with acute respiratory tract infection, which is the most prevalent symptom covering almost all barangays, followed by urinary tract infection and gastrointestinal reflux. It is concluded that acute respiratory tract infection tops the list of symptoms that the patients are experiencing, as recorded on the outpatient visits, and covers almost all of the barangays affected. Most of all, it also affects adults. It is recommended that the local government unit of the Municipality of Janiuay prioritize medicines that would address minimizing respiratory tract-related concerns and other related health problems.

Keywords- outpatient, visits, ARIMA, time series

Unique Identification Number - IJEDR2302006
Page Number(s) - 35-39
Pubished in - Volume 11 | Issue 2 | April 2023
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Liv T. Onic,  Minle Mar M. Ayalin,  Hiezyl M. Gorantes,  Jay C. Liza,   "Predicting Outpatient Visits using Time Series Data based on ARIMA Model", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.11, Issue 2, pp.35-39, April 2023, Available at :http://www.ijedr.org/papers/IJEDR2302006.pdf