Dynamic Prediction And Study On Outpatient Appointment And Queuing Management System

The waiting time patients spent in hospital contributed much to their satisfaction and was a key index of the hospital's management level. The job of appointment and queuing management was based on quick and exact outpatient volume forecast, which could help hospital prepare in advance in order to reduce the patients'waiting time remarkably.It was important to raise the customers'satisfaction, humanity of management and the benefit of hospital by reducing the waiting time of patients, realizing orderly waiting and treatment, enhancing the productivity and letting the elder have some priority on the basis of forecast and business process improvement.Constant Mean Discount Bayesian Model was adopted and was compared with Exponent Smoothing Prediction Method about the forecast precision according to the characteristics of outpatient data. There were two kinds of data, one was the real data collected from the intestine section of 7th hospital of Shanghai, the other was generated according to random data obeying Poisson Distribution; the flow in outpatient dept. were analyzed and optimized with the value principle, the key flow were extracted and summarized.In spite of few and fluctuating historical data, Bayesian dynamic linear model was effective in outpatient amount forecast because the estimated distribution could be given in advance which resulted in less required data while getting the similar precision forecast;the system integrated appointed management with queuing management and realized data sharing. By the effective information transfer, the outpatient service efficiency was improved, the workload of nurses was reduced, the workload of doctors was evened, the outpatient order was improved, so both patient satisfaction and benefit of hospital were enhanced; The proposed system had been running in the hospital successfully.