Prediction of surgery times and scheduling of operation theaters in ophthalmology department

Abstract

This paper presents the framework for forecasting the surgery time by taking into account the surgical environment in an ophthalmology department (experience of surgeon in years, experience of anesthetist in years, staff experience in years, type of anesthesia etc.). The estimation of surgery times is done using three techniques, such as the Adaptive Neuro Fuzzy Inference Systems (ANFIS), Artificial Neural Networks (ANN) and Multiple Linear Regression Analysis (MLRA) and the results of estimation accuracy were compared. Though the developed framework is general, it is illustrated for three ophthalmologic surgeries such as the cataract surgery, corneal transplant surgery and Oculoplastic surgery. The framework is validated by using data obtained from a local hospital. It is hypothesized that by accurately knowing the surgery times, one can schedule the operations optimally resulting in the efficient utilization of the operating rooms. This increase in the efficiency is demonstrated through computer simulations of the operating theater.