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: Chapter in Book/Report/Conference proceedingConference contribution

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
Title of host publicationComputational Science - ICCS 2019
Subtitle of host publication19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V
EditorsJoão M. F. Rodrigues, Pedro J. S. Cardoso, Jânio Monteiro, Roberto Lam, Valeria V. Krzhizhanovskaya, Michael H. Lees, Jack J. Dongarra, Peter M. A. Sloot
Place of PublicationCham
PublisherSpringer Verlag
Pages445-452
Number of pages8
VolumeLNCS 11540
ISBN (Electronic)9783030227500
ISBN (Print)9783030227494, 3030227499
DOIs
Publication statusPublished - 13 Aug 2019
Event19th International Conference on Computational Science - Faro, Portugal
Duration: 12 Jun 201914 Jun 2019
https://www.iccs-meeting.org/iccs2019/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11540 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computational Science
Abbreviated titleICCS 2019
CountryPortugal
CityFaro
Period12/06/1914/06/19
Internet address

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Gatta, R., Vallati, M., Lenkowicz, J., Masciocchi, C., Cellini, F., Boldrini, L., ... Damiani, A. (2019). On the Feasibility of Distributed Process Mining in Healthcare. In J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, R. Lam, V. V. Krzhizhanovskaya, M. H. Lees, J. J. Dongarra, ... P. M. A. Sloot (Eds.), Computational Science - ICCS 2019: 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V (Vol. LNCS 11540, pp. 445-452). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11540 LNCS). Cham: Springer Verlag. https://doi.org/10.1007/978-3-030-22750-0_36
Gatta, Roberto ; Vallati, Mauro ; Lenkowicz, Jacopo ; Masciocchi, Carlotta ; Cellini, Francesco ; Boldrini, Luca ; Fernandez-Llatas, Carlos ; Valentini, Vincenzo ; Damiani, Andrea. / On the Feasibility of Distributed Process Mining in Healthcare. Computational Science - ICCS 2019: 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V. editor / João M. F. Rodrigues ; Pedro J. S. Cardoso ; Jânio Monteiro ; Roberto Lam ; Valeria V. Krzhizhanovskaya ; Michael H. Lees ; Jack J. Dongarra ; Peter M. A. Sloot. Vol. LNCS 11540 Cham : Springer Verlag, 2019. pp. 445-452 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Gatta, R, Vallati, M, Lenkowicz, J, Masciocchi, C, Cellini, F, Boldrini, L, Fernandez-Llatas, C, Valentini, V & Damiani, A 2019, On the Feasibility of Distributed Process Mining in Healthcare. in JMF Rodrigues, PJS Cardoso, J Monteiro, R Lam, VV Krzhizhanovskaya, MH Lees, JJ Dongarra & PMA Sloot (eds), Computational Science - ICCS 2019: 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V. vol. LNCS 11540, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11540 LNCS, Springer Verlag, Cham, pp. 445-452, 19th International Conference on Computational Science, Faro, Portugal, 12/06/19. https://doi.org/10.1007/978-3-030-22750-0_36

On the Feasibility of Distributed Process Mining in Healthcare. / Gatta, Roberto; Vallati, Mauro; Lenkowicz, Jacopo; Masciocchi, Carlotta; Cellini, Francesco; Boldrini, Luca; Fernandez-Llatas, Carlos; Valentini, Vincenzo; Damiani, Andrea.

Computational Science - ICCS 2019: 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V. ed. / João M. F. Rodrigues; Pedro J. S. Cardoso; Jânio Monteiro; Roberto Lam; Valeria V. Krzhizhanovskaya; Michael H. Lees; Jack J. Dongarra; Peter M. A. Sloot. Vol. LNCS 11540 Cham : Springer Verlag, 2019. p. 445-452 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11540 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - On the Feasibility of Distributed Process Mining in Healthcare

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AU - Vallati, Mauro

AU - Lenkowicz, Jacopo

AU - Masciocchi, Carlotta

AU - Cellini, Francesco

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AU - Fernandez-Llatas, Carlos

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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A2 - Dongarra, Jack J.

A2 - Sloot, Peter M. A.

PB - Springer Verlag

CY - Cham

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Gatta R, Vallati M, Lenkowicz J, Masciocchi C, Cellini F, Boldrini L et al. On the Feasibility of Distributed Process Mining in Healthcare. In Rodrigues JMF, Cardoso PJS, Monteiro J, Lam R, Krzhizhanovskaya VV, Lees MH, Dongarra JJ, Sloot PMA, editors, Computational Science - ICCS 2019: 19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V. Vol. LNCS 11540. Cham: Springer Verlag. 2019. p. 445-452. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-22750-0_36