On the feasibility of distributed process mining in healthcare

Roberto Gatta, Mauro Vallati, Jacopo Lenkowicz, Carlotta Masciocchi, Francesco Cellini, Luca Boldrini, Carlos Fernandez Llatas, Vincenzo Valentini, Andrea Damiani

Research output: Contribution to journalConference article

Abstract

Process mining is gaining significant importance in the healthcare domain, where the quality of services depends on the suitable and efficient execution of processes. A pivotal challenge for the application of process mining in the healthcare domain comes from the growing importance of multi-centric studies, where privacy-preserving techniques are strongly needed. In this paper, building on top of the well-known Alpha algorithm, we introduce a distributed process mining approach, that allows to overcome problems related to privacy and data being spread around. The introduced technique allows to perform process mining without sharing any patients-related information, thus ensuring privacy and maximizing the possibility of cooperation among hospitals.
Original languageEnglish
Pages (from-to)445-452
Number of pages8
JournalLecture Notes in Computer Science
Volume11540
DOIs
Publication statusPublished - 2019
Event19th International Conference on Computational Science, ICCS 2019 - FARO
Duration: 12 Jun 201914 Jun 2019

Keywords

  • Distributed learning
  • Healthcare
  • Process mining

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