Process mining in healthcare
On April 13, 2020, the sixth run of the free FutureLearn online course ‘Process mining in healthcare’ will start, register now! We are happy to be able to run this course again.
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 course 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, and the ‘Process mining for healthcare’ consortium. Lead educator is Renata Carvalho de Medeiros 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 healthcare’!
We hope to see you soon!
|Renata Carvalho de Medeiros||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 and Process mining for healthcare consortium.|