TY - JOUR
T1 - Process mining for healthcare: Characteristics and challenges
AU - Munoz-gama, Jorge
AU - Martin, Niels
AU - Fernandez-llatas, Carlos
AU - Johnson, Owen A.
AU - Sepúlveda, Marcos
AU - Helm, Emmanuel
AU - Galvez-yanjari, Victor
AU - Rojas, Eric
AU - Martinez-millana, Antonio
AU - Aloini, Davide
AU - Amantea, Ilaria Angela
AU - Andrews, Robert
AU - Arias, Michael
AU - Beerepoot, Iris
AU - Benevento, Elisabetta
AU - Burattin, Andrea
AU - Capurro, Daniel
AU - Carmona, Josep
AU - Comuzzi, Marco
AU - Dalmas, Benjamin
AU - De La Fuente, Rene
AU - Di Francescomarino, Chiara
AU - Di Ciccio, Claudio
AU - Gatta, Roberto
AU - Ghidini, Chiara
AU - Gonzalez-lopez, Fernanda
AU - Ibanez-sanchez, Gema
AU - Klasky, Hilda B.
AU - Prima Kurniati, Angelina
AU - Lu, Xixi
AU - Mannhardt, Felix
AU - Mans, Ronny
AU - Marcos, Mar
AU - Medeiros De Carvalho, Renata
AU - Pegoraro, Marco
AU - Poon, Simon K.
AU - Pufahl, Luise
AU - Reijers, Hajo A.
AU - Remy, Simon
AU - Rinderle-ma, Stefanie
AU - Sacchi, Lucia
AU - Seoane, Fernando
AU - Song, Minseok
AU - Stefanini, Alessandro
AU - Sulis, Emilio
AU - Ter Hofstede, Arthur H.m.
AU - Toussaint, Pieter J.
AU - Traver, Vicente
AU - van der Aalst, Wil M.P.
AU - Vanwersch, Rob
PY - 2022/3/1
Y1 - 2022/3/1
N2 - Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.
AB - Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.
KW - Healthcare
KW - Process mining
UR - http://www.scopus.com/inward/record.url?scp=85124238268&partnerID=8YFLogxK
U2 - 10.1016/j.jbi.2022.103994
DO - 10.1016/j.jbi.2022.103994
M3 - Article
C2 - 35104641
SN - 1532-0464
VL - 127
JO - Journal of Biomedical Informatics
JF - Journal of Biomedical Informatics
M1 - 103994
ER -