FORECASTING OF MONTHLY PATIENT VOLIUME AT RADIOLOGY DEPARTMENT COMING FOR ULTRASOUND: A TIME SERISE APPROCH. - Khubaib Shahid; Tariq Manzoor; Muhammad Ibrahim (Journal of University Medical & Dental College, 2016)
ABSTRACT:BACKGROUND & OBJECTIVE: Prediction of clinical events/occurrences, patients’ volume at OPD, emergency overcrowding, and stay length in hospital for treatment and bed occupancy in wards is considered an important feature for future planning of hospital/clinical management. Patients incoming at emergency and OPD has drawn considerable attention since last two decades. This study was conducted to forecast the patient’s volume at Radiology Department of FMH hospital, Shadman Lahore, coming for Ultrasound. Time series approach was used to analyze the data. METHOD: Time series monthly data of patients coming for ultrasound at radiology department, from January 2001 to May 2015 was used for ﬁtting the best model. RESULT & CONCLUSION: The ARIMA (12, 1, and 12) model for patient volume was found appropriate, after residuals diagnostic checks. The ARIMA model was used to forecast the patient’s volume from June 2015 to May 2017 by applying software GRETL. The actual patient’s volume for May 2015 is 5482 and the predicted value for same time is 5422. The predicted error is 1.1%. It is now concluded that the ﬁtted ARIMA is adequate model and can be used to forecast the patient’s incoming to Radiology Department for future planning and management.