RESUMO
Uni-variate time series data analysis has been reported in medical literature for prediction the patients volume, emergency overcrowding, stay length in hospital on surgical procedure and bed occupancy in hospital wards, patients influx or patients arrival, moreover to estimate the cost of hospital stay or any medical or surgical procedure. The present study was designed to fit an appropriate uni-variate ARIMA model [Box-Jenkin methodology] to forecast the patient's incoming at OPML, Mayo Hospital, Lahore. Mayo Hospital Lahore, September 2009 to December 2013 were used for fitting the best model. Time series data of male, female and peads patients coming/reporting in OPML, OPD. The appropriate model for male and female data was found as ARIMA [1, 0, 1] and for peads as ARIMA [1, 1, 1] after residuals diagnostic checks. The estimated number of male patients for Month of January2014 is 632 whereas the actual incoming of male patients in the month of January, 2014 was 649, which shows that the estimated model has ability to forecast the number of incoming patients accurately. It is now concluded that the fitted ARIMA model can be used to forecast the patients incoming to OPD Medical Laboratory for future planning and management