Process Mining in Healthcare Systems: A Critical Review and its Future

doi:10.30534/ijeter/2020/50892020

Cited by 16 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An event log [20] consists of multiple traces. A trace [21] is a sequence of activity names abstracted from other attributes in the order of events.…”

Section: -Process Mining Algorithms 4-1-alpha Minermentioning

confidence: 99%

Performance Analysis and Activity Deviation Discovery in Event Log Using Process Mining Tool for Hospital System

M¹,

Nayak²,

Jadala³

et al. 2023

jist

View full text Add to dashboard Cite

All service and manufacturing businesses are resilient and strive for a more efficient and better end in today's world. Data mining is data-driven and necessitates significant data to analyze the pattern and train the model. Assume the data is incorrect and was not collected from reliable sources, causing the analysis to be skewed. We introduce a procedure in which the dataset is split into test and training datasets with a specific ratio to overcome this challenge. Process mining will find the traces of actions to streamline the process and aid data mining in producing a more efficient result. The most responsible domain is the healthcare industry. In this study, we used the activity data from the hospital and applied process mining algorithms such as alpha miner and fuzzy miner. Process mining is used to check for conformity in the event log and do performance analysis, and a pattern of accuracy is exhibited. Finally, we used process mining techniques to show the deviation flow and fix the process flow. This study showed that there was a variation in the flow by employing alpha and fuzzy miners in the hospital.

show abstract

“…An event log [20] consists of multiple traces. A trace [21] is a sequence of activity names abstracted from other attributes in the order of events.…”

Section: -Process Mining Algorithms 4-1-alpha Minermentioning

confidence: 99%

Performance Analysis and Activity Deviation Discovery in Event Log Using Process Mining Tool for Hospital System

M¹,

Nayak²,

Jadala³

et al. 2023

jist

View full text Add to dashboard Cite

show abstract

“…Process mining has a strong evidencebased method by analysing event log that has been extracted from the automatically recorded data in the healthcare database. Process mining can be utilized for process-oriented data science, where event data is collected and used as the primary input to find processes in health services, such as patient treatments and diagnoses [8].…”

Section: Introductionmentioning

confidence: 99%

Process Mining for Disease Trajectory Analysis on the Indonesia Health Insurance Data

Kurniati

Kusuma²,

Wisudiawan³

2022

Jur. Ris. Kom.

View full text Add to dashboard Cite

Process mining has been implemented in many domains, including healthcare. In healthcare, process mining projects aimed to inform sequential patterns of processes based on the actual process executions as they are recorded in the event log. Event log as the main input of process mining tasks can be extracted from the automatically recorded data of patient treatments or diagnoses. By understanding common patterns of patient diagnoses, we can analyse disease trajectories of a cohort of patients. Disease trajectory analysis has been used to describe the course or progression of diseases, especially chronic diseases, as experienced over time. We applied process mining as the main methodology for disease trajectory analysis, following the process mining project methodology, to analyse patient records on the Indonesia Health Insurance (BPJS Kesehatan) Data Samples. We extracted the data samples, transform them into an event log, discover the disease trajectories based on process discovery algorithm, analyse it to inform their conformance to the event log. Contributions of our research are to promote process mining for disease trajectory analysis and to open wider opportunities to analyse Indonesia Health Insurance data representing Indonesia health conditions. As a case study, we explored disease trajectory of cancer patients

show abstract