A guide for the application of analytics on healthcare processes: A dynamic view on patient pathways.

Objective: The aim of this study is to guide healthcare instances in applying process analytics on healthcare processes. Process analytics techniques can offer new insights in patient pathways, workflow processes, adherence to medical guidelines and compliance with clinical pathways, but also bring along specific challenges which will be examined and addressed in this paper.

Methods: The following methodology is proposed: log preparation, log inspection, abstraction and selection, clustering, process mining, and validation.

Data mining methods for classification of Medium-Chain Acyl-CoA dehydrogenase deficiency (MCADD) using non-derivatized tandem MS neonatal screening data.

Newborn screening programs for severe metabolic disorders using tandem mass spectrometry are widely used. Medium-Chain Acyl-CoA dehydrogenase deficiency (MCADD) is the most prevalent mitochondrial fatty acid oxidation defect (1:15,000 newborns) and it has been proven that early detection of this metabolic disease decreases mortality and improves the outcome. In previous studies, data mining methods on derivatized tandem MS datasets have shown high classification accuracies.