The automatic discovery of a model to represent the history of encounters of a group of patients with the healthcare system -- the so-called "pathway of patients" -- is a new field of research that supports clinical and organisational decisions to improve the quality and efficiency of the treatment provided. The pathways of patients with chronic conditions tend to vary significantly from one person to another, have repetitive tasks, and demand the analysis of multiple perspectives (interventions, diagnoses, medical specialities, among others) influencing the results. Therefore, modelling and mining those pathways is still a challenging task. In this work, we propose a framework comprising: (i) a pathway model based on a multi-aspect graph, (ii) a novel dissimilarity measurement to compare pathways taking the elapsed time into account, and (iii) a mining method based on traditional centrality measures to discover the most relevant steps of the pathways. We evaluated the framework using the study cases of pregnancy and diabetes, which revealed its usefulness in finding clusters of similar pathways, representing them in an easy-to-interpret way, and highlighting the most significant patterns according to multiple perspectives.

IBM is to sell off the data assets of its AI-powered Watson Health operation to private equity firm Francisco Partners, in move which pretty much ends the story for the beleaguered healthcare unit. Announced on Friday, exact details of the deal were undisclosed, but media reports suggested a sale of more than $1bn. The sell-off marks an end to IBM's healthcare ambitions, as the Armonk, NY based giant concentrates on its hybrid cloud business. Where reports earlier in the month had suggested IBM was looking to sell off the entirety of the poorly performing unit, last week's deal is a sale of Watson Health's data and analytics assets. IBM had previously built out Watson Health through a series of acquisitions totalling more than $4bn.