Fig 1.
Process mining approach including process discovery, conformance checking and enhancements for a hospital [7].
Table 1.
Overview of reviewed researches.
Fig 2.
Proposed methodology based on process mining for patient’s careflows.
Fig 3.
The first discovered process (A spaghetti model) using every trace.
Fig 4.
General business model for the heart surgeries in the hospital.
Fig 5.
A part of event log.
Fig 6.
Database model for the case study.
Fig 7.
Boxplots for events durations.
Table 2.
Event data before and after applying preprocessing phase.
Fig 8.
Four clusters generated from “ActiTraC” method.
Fig 9.
BPMN models of the two clusters generated from using Markov clustering algorithm upon on refers from attribute.
(a) Cluster refers from “Doctor” (b) Cluster refers from “Emergency”.
Table 3.
The properties of the two clusters generated from using Markov clustering algorithm.
Fig 10.
BPMN models generated after clustering patients upon on the interest of hospital’s experts.
(a) Cardiac Stent and Diagnostic Catheterization (b) open heart surgery (c) without any surgery just a medication.
Fig 11.
Result model from heuristic miner.
Fig 12.
Result model from inductive miner.
Fig 13.
Petri net from the ILP miner.
Fig 14.
Result from ETM miner algorithm.
Table 4.
Index of the activities.
Table 5.
Most frequent traces.
Fig 15.
Result Replay of Petri net based on inductive miner with extracted log.
Fig 16.
The statistical information obtained from replay Petri net based on petri net from inductive miner with extracted log.
Fig 17.
Precision and generalization results of Petri net based on inductive miner.
Table 6.
Quantify the complexity of the model from the inductive and ETM discovery miners.
Table 7.
Comparison among the four applied algorithms.
Table 8.
The length of the patient journey (in days) into hospital according to the patient refer from type.
Table 9.
Length of the patient journey (in days) into hospital according to the patient diagnostics.
Fig 18.
Replaying the Event Log and the Petri Net of the base Model “Standard model” for Conformance Analysis and Bottleneck analysis.
Fig 19.
The resulting Statistical information obtained from replaying the event log with the Petri Net of the base model “Standard model” for conformance checking process.
Fig 20.
The process model explains the deviations.
Fig 21.
Patients’ distribution among hospital services.
Fig 22.
The process model explains sojourn time of the resources.
Fig 23.
The dotted chart of whole event log.
Fig 24.
The dotted chart of cluster 1 of “cardiac stent and diagnostic catheterization”.
Fig 25.
The dotted chart of cluster 2 of “open heart surgery”.
Fig 26.
The dotted chart of cluster 3 of “the patients leaved the hospital without any surgery but only took medication care”.
Fig 27.
Social network of the hospital originators with the handover of work metric.