Process mining for healthcare: Characteristics and challenges.
Healthcare
Process mining
Journal
Journal of biomedical informatics
ISSN: 1532-0480
Titre abrégé: J Biomed Inform
Pays: United States
ID NLM: 100970413
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
01
09
2021
revised:
16
11
2021
accepted:
10
01
2022
pubmed:
2
2
2022
medline:
17
3
2022
entrez:
1
2
2022
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 35104641
pii: S1532-0464(22)00010-7
doi: 10.1016/j.jbi.2022.103994
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
103994Informations de copyright
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