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

doi:10.1007/978-3-030-22750-0_36

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 proceeding › Conference contribution › peer-review

6 Citations (Scopus)

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 language	English
Title of host publication	Computational Science - ICCS 2019
Subtitle of host publication	19th International Conference Faro, Portugal, June 12-14, 2019 Proceedings, Part V
Editors	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
Place of Publication	Cham
Publisher	Springer Verlag
Pages	445-452
Number of pages	8
Volume	LNCS 11540
ISBN (Electronic)	9783030227500
ISBN (Print)	9783030227494, 3030227499
DOIs	https://doi.org/10.1007/978-3-030-22750-0_36
Publication status	Published - 13 Aug 2019
Event	19th International Conference on Computational Science - Faro, Portugal Duration: 12 Jun 2019 → 14 Jun 2019 Conference number: 19 https://www.iccs-meeting.org/iccs2019/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11540 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Computational Science
Abbreviated title	ICCS 2019
Country/Territory	Portugal
City	Faro
Period	12/06/19 → 14/06/19
Internet address	https://www.iccs-meeting.org/iccs2019/

Access to Document

10.1007/978-3-030-22750-0_36Licence: Unspecified

Distributed_PM___ICCS19Accepted author manuscript, 254 KBLicence: Unspecified

Cite this

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 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). Springer Verlag. https://doi.org/10.1007/978-3-030-22750-0_36

Gatta, Roberto ; Vallati, Mauro ; Lenkowicz, Jacopo et al. / 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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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.",

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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 et al.
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 proceeding › Conference contribution › peer-review

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AU - Vallati, Mauro

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AU - Masciocchi, Carlotta

AU - Cellini, Francesco

AU - Boldrini, Luca

AU - Fernandez-Llatas, Carlos

AU - Valentini, Vincenzo

AU - Damiani, Andrea

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AB - 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.

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VL - LNCS 11540

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

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BT - Computational Science - ICCS 2019

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A2 - Cardoso, Pedro J. S.

A2 - Monteiro, Jânio

A2 - Lam, Roberto

A2 - Krzhizhanovskaya, Valeria V.

A2 - Lees, Michael H.

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)). Epub 2019 Jun 8. doi: 10.1007/978-3-030-22750-0_36

On the Feasibility of Distributed Process Mining in Healthcare

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