Abstract:
This research aim to measuring the factors in terms of a number of patients who take oxygen therapy, time spent by patients in treatment and oxygen rate flow that affect medical oxygen demand by the governmental hospitals in Khartoum State. As well as to testing the effects of type of diseases, age groups of patients who need medical oxygen as a treatment and seasonality of the demand of medical oxygen. The survey covered a number of (15) governmental hospitals in Khartoum State ( 9 urban & 6 rural) .Were selected randomly by using the cluster random sampling method .The study found that factors of a number of patients who take oxygen therapy in a month, oxygen transfer rate to patient and the time period which spent by a patient in treatment , the difference of diseases are affect monthly average of medical oxygen consumption in hospitals per m3 (p < 0.05). Also it detected that the demand of medical oxygen is not affected by the differenceoftheage groups of patients who need medical oxygen as a treatment. The demand of medical oxygen is not affected by the deference of season of year ( p>0.05).Also this research aims to find a suitable model to predict the demand of medical oxygen. The study data contained a number of 120 observations of oxygen consumption( in m3 ) were taken from Soba University Hospital in Khartoum state, since January 2005 to December 2014. We have used Box-Jenkins, Auto Regressive Integrated Moving Average (ARIMA) methodology for building forecasting model. Results suggest that ARIMA(0,1,1) is the most suitable model to be used for predicting the demand of medical oxygen. For testing the forecasting accuracy Root Mean Square Error, Mean Absolute Error, and Mean Absolute Percentage Error are calculated.Finally, the research recommended: The use of cylinders system and work on the transition to the production of oxygen Center in hospitals. Develop plans and strategies and programs that aim to reduce the incidence of respiratory disease rates, especially (Asthma, pneumonia).Develop a model that can be used to predict the demand of medical oxygen, what constitutes a scientific base to put good plans to avoid any shortage of oxygen in the hospitals of Khartoum State.Promote and provide input medical services, especially oxygen in rural hospitals in Khartoum State.