Publication: Time series analysis of diabetes patients: A case study of Jigme Dorji Wangchuk National Referral Hospital in Bhutan
Issued Date
2018-06-27
Resource Type
ISSN
17426596
17426588
17426588
Other identifier(s)
2-s2.0-85049900363
Rights
Mahidol University
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Physics: Conference Series. Vol.1039, No.1 (2018)
Suggested Citation
Thukten Singye, Suntaree Unhapipat Time series analysis of diabetes patients: A case study of Jigme Dorji Wangchuk National Referral Hospital in Bhutan. Journal of Physics: Conference Series. Vol.1039, No.1 (2018). doi:10.1088/1742-6596/1039/1/012033 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/47361
Research Projects
Organizational Units
Authors
Journal Issue
Thesis
Title
Time series analysis of diabetes patients: A case study of Jigme Dorji Wangchuk National Referral Hospital in Bhutan
Author(s)
Other Contributor(s)
Abstract
© Published under licence by IOP Publishing Ltd. Diabetes has become a concern in Bhutan with its growing number of patients reported to the hospital. Increasing number of patient is likely to result in rising demand for the medical emergencies. Due to having only three referral hospitals in Bhutan, it is important to forecast the future incidences and prepare with proper resource planning. The monthly number of Diabetes patients obtained from Jigme Dorji Wangchuk National Referral Hospital (JDWNRH) is fitted by autoregressive integrated moving average (ARIMA) model. Such dataset starting from January 2006 to December 2016 is divided into two sub datasets; training dataset (January 2006 - December 2015) and validation dataset (January 2016 - December 2016). Using ARIMA, several models were evaluated based on the Bayesian Information Criterion (BIC) and Ljung-Box Q statistics. ARIMA(0, 1, 1) is the best model to describe and predict the future trends of Diabetes incidences on considering the simplest parsimonious lowest order model. Therefore, the proposed model will help to plan appropriately and allocate resources for emergencies.