The Suitability of Artificial Neural Networks in Service Quality Control and Forecasting for Healthcare Contexts

Over the last decade there has been considerable research into the area of service quality. Service, however, as an intangible, perishable, and heterogenic transaction, is very difficult to quantify and measure, and little success has been reported on a systematic approach in modeling of quality of service transactions (with SERVQUAL and its derivatives as the notable exception). In this paper, we propose an Artificial Neural Network (ANN) to monitor quality of service transaction as a dynamic and real-time monitoring and forecasting system. ANNs are widely used in many engineering fields to model and simulate complex systems. The resulting near-perfect models are particularly suited for applications where real-world complexities make it difficult or even impossible to mathematically model the system. Given the complex nature of healthcare decisions, the following reports on a research in progress study that focuses on applying ANN to a specific healthcare context of the emergency room.