An intelligence risk detection framework to improve decision efficiency in healthcare contexts: the example of pediatric congenital heart disease

Superior decision making in healthcare can literally mean the difference between life and death. Given the time pressures faced by healthcare professionals coupled with the need to process large amounts of disparate data and information to make appropriate treatment decisions, these professionals are faced with an increasingly challenging work context. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support systems and try to develop a suitable model. To illustrate the benefits of risk detection to improve decision efficacy in healthcare contexts we focus on the case of Congenital Heart Disease (CHD), an area which requires complex high risk decisions to facilitate identification of appropriate treatment strategies.