The model of situations of the psychiatric patients at the Galya Rajanagarindra Institute

Abstract

Objective: To study the suitable statistical prediction model for the prognosis of patients encountered situations and forecasting the trends of psychiatric patients receiving service at the Galya Rajanagarindra Institute.

Methods:  The research aims to studying the forecasting methods by using secondary time series data. The data used was information of outpatients who received psychiatric services from October 2012 - September 2018. The 5 time series forecasting techniques were examined to find the suitable statistical forecasting method. The accuracy of the forecast was measured by absolute percentage deviation (MAPE) and it was applied to forecast the trend from October 2018 to September 2020.

Results: The results showed that most of the psychiatric patients are males, single status, aged around 40-49 years old, living in the 5^th health area and paying their own treatment cost. They were mostly diagnosed with ICD-10 code F20-F29 (schizophrenia, schizophrenic behavior and delusions) with the highest number of F20 (schizophrenia). The appropriate forecasting model was Winters' Additive Exponential Smoothing technique with the MAPE value 3.775 for predicting the trend of psychiatric outpatients. The forecasting indicated that the number of patients receiving services is likely to increase every year. It is expected that there will be 40,695 and 43,806 patients in the year 2019 and 2020, respectively. The highest number of patients were in August (3,582 and 3,841). The most common diagnosis was F20-F29 that estimated to 3,890 in 2019 and 3,920 in 2020. The prediction results were under stable geographic or environmental conditions.

Conclusion: There should be plans for service system development, budget management and medical supplies according to the predicted increasing number of patients.