Incorporating intelligent risk detection to enable superior decision support: the example of orthopaedic surgeries.

Abstract

Decision making in healthcare is unstructured, complex and critical. Today, healthcare professionals are continually under immense time pressure to make appropriate treatment decisions which in turn have far reaching implications on the quality of outcomes. Moreover, in order to make such decisions it is necessary for them to process large amounts of disparate data and information. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support. In this application data mining tools in combination with Knowledge Discovery (KD) techniques are used to score the surgery risk levels, assess surgery risks and help medical professionals to make appropriate and superior complex surgical decisions for each patient. To illustrate the benefits of such intelligent risk detection to improve decision efficacy in healthcare contexts we focus within the context of Orthopaedic Surgeries, specifically on hip and knee surgeries. This paper concludes with a conceptual model to move successfully from idea to design and then implementation.