Comparing Care Pathways Between COVID-19 Pandemic Waves Using Electronic Health Records: A Process Mining Case Study.

ABSTRACT: The COVID-19 pandemic caused rapid shifts in the workflow of many health services, but evidence of how this affected multidisciplinary care settings is limited. In this data study, we propose a process mining approach that utilises timestamped data from electronic health records to compare care provider patterns across pandemic waves. To investigate healthcare patterns during the pandemic, we collected routine events from Scottish hospital episodes in adults with COVID-19 status, generating treatment logs based on care provider input. Conformance checking metrics were used to select the Inductive Miner infrequent (IMi) algorithm for downstream analysis. Visual diagrams from the discovered Petri Nets indicated interactions on provider- and activity-level data subsets. Measures of "cross-log

SUBMITTER: Georgiev K 

PROVIDER: S-EPMC11782707 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature