|
Forecasting the number of elderly falls Inpatients in Pathum Thani Province |
|---|---|
| รหัสดีโอไอ | |
| Creator | Byaporn na Nagara |
| Title | Forecasting the number of elderly falls Inpatients in Pathum Thani Province |
| Contributor | Pisitpat Charoenpakdee, Vadhana Jayathavaj, Watcharaphan Srisawasdi, Chonlada Judprakob, Kanyapat Phutsom, Pichittra Yuenyang, Suriyaphongse Kulkeratiyut, Chaisen Pisanwalerd, Theerasest Sriprapassorn |
| Publisher | Pathum thani University |
| Publication Year | 2568 |
| Journal Title | PTU Journal of Science and Technology |
| Journal Vol. | 6 |
| Journal No. | 1 |
| Page no. | 41-52 |
| Keyword | Forecasting, The number of in patients, Elderly falls, Pathum Thani province |
| URL Website | https://ph01.tci-thaijo.org/index.php/PTUJST |
| Website title | https://ph01.tci-thaijo.org/ |
| ISSN | 2697-3820 (Online) |
| Abstract | This time series forecasting research aimed to predict the number of elderly fallsinpatientsaged 60 years and above in Pathum Thani Province in 2024 and 2025. Using the total number of inpatients per year in the elderly falls aged 60 years and over in Pathum Thani Province between 2018 and 2023 from the Injury Prevention Division, Department of Disease Control. Time series were analyzed using Gray theory, GM(1,1) and GM(1,1)EPC (error periodic correction) models. Model accuracy was considered using mean absolute percentage error (MAPE). The results showed that for the forecast of 2024, the GM(1,1) and GM(1,1)EPC models had [MAPE value (percent), forecast value (cases), and growth rate from 2023 (percent)] [40.06, 736, 6.32] and [31.08, 1,160, 67.36], respectively. When the forecast values of 2024 from both methods were used to create the model, it was found that for 2024 and 2025, the minimum forecast was 736 and1,170 cases, respectively, and the maximum forecast was 1,160 and 2,063 cases, respectively. It can be said that the MAPE values of the model were between more than 20 and 50 percent, and can be used for reasonable forecasting |
