On August 7 the first run of the free FutureLearn online course 'Process mining 
in healthcare' started, but you can still 
Healthcare in particular has come under increasing pressure to reduce cost 
while improving the quality of care. One way to achieve this is by further 
improving the efficiency of treatment processes: by making more efficient use 
of the scarce resources, only effective treatments are executed. Luckily, the 
advance of big data and increased support of information systems in day-to-day 
healthcare processes provide the data needed to find efficiency gains.
Process mining is a novel collection of techniques that connects the areas of 
data science and business process management. Using process mining techniques 
healthcare processes can be analysed in great detail. Based on event data (what 
happened when, by which resource, and for which patient), process mining 
techniques can automatically discover process models, describing the process 
flow of the majority of patient treatments. Existing process models or 
guidelines can be validated against the event data, in order to analyse 
deviations. Performance and bottleneck information can be projected on process 
models to easily detect where most time is spent in a process. Also the social 
network of how resources in a process collaborate and hand over work can be 
analysed, all based on the event data containing four columns: what, when, for 
which patient, and by whom.
In this free 
 you will learn how process mining can provide answers to the most common 
challenges in healthcare. We will discuss the healthcare environment, and spend 
significant time on how to get the right data. We also provide example 
datasets, both artificial and from real-life, which are used in tutorials where 
our free and open source process mining software ProM is applied, by you!
We will also present several case studies, where process mining techniques have 
been applied in real healthcare organisations. For each case study we will 
discuss the main goal, provide an overview of the obtained results, and provide 
the key conclusions and impact on the processes. These case studies are 
contributed by different partners.
The course 'Process mining in healthcare' is an initiative of the European Data 
Science Academy EU project<http://edsa-project.eu/>, and the 'Process mining 
for healthcare' consortium<http://www.processmining4healthcare.org/>. Lead 
educator is dr.ir. Joos Buijs from Eindhoven University, who specialises in 
process mining in the healthcare domain.
Are you interested? Or do you want to know more? Register for free at 
FutureLearn for our online course 'Process mining in 
We hope to see you soon!
Joos Buijs - Eindhoven University of Technology
Carlos Fernandez-Llatas - Universitat Politècnica de València
Roberto Gatta - Gemelli ART (Advanced Radiation Therapy) and KBO (Knowledge 
Based Oncology) Labs, Rome
Jorge Munoz-Gama - Pontificia Universidad Católica de Chile
Marcos Sepulveda - Pontificia Universidad Católica de Chile
Lucia Sacchi - University of Pavia
Davide Aloini - University of Pisa
And the members of the European Data Science Academy EU 
project<http://edsa-project.eu/> and Process mining for healthcare 

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