Multi-level process mining methodology for exploring disease-specific care processes

Vathy-Fogarassy, Ágnes; Vassányi, István; Kósa, István

doi:10.1016/j.jbi.2021.103979

Cited by 8 publications

(9 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Vathy-Fogarassy et al [70] proposed a goal-based process discovery methodology specifically for a healthcare environment and ignored tasks not required to analyze disease under focus. They simplify the process model based on the domain-specific taxonomy by introducing multilevel abstractions over the log.…”

Section: Goal-based Abstractionmentioning

confidence: 99%

See 1 more Smart Citation

Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

Process mining techniques are used to extract knowledge about the efficiency and compliance of an organization's business processes through process models. Real-life processes are unstructured, and applying process mining to discover such processes often results in complex process models that do not provide actionable insights. Several solutions have been presented to overcome this problem. However, the process mining domain lacks an explicit definition of complexity and its measurement. This vagueness results in ad-hoc solutions that vary according to the approach, modelling construct, and process properties. Additionally, the strength and limitations of the proposed solutions have not been adequately highlighted. Therefore, we conducted a systematic literature review on complexity in process mining over six popular scholarly indexing databases. Based on the review results, an explicit definition of complexity, the main contributing factors and their impact on process mining results were identified. We discovered various process complexity matrices and their application context. The analysis of studies led to the development of a taxonomy consisting of four different approaches for addressing the complexity problem, along with their strengths and limitations. Finally, the open research challenges and potential for future research are discussed.

show abstract

Section: Goal-based Abstractionmentioning

confidence: 99%

“…IT management process 5% [68], [70] or behavioral complexity measures such as the fitness, precision & f-measure [31], [38], [62], [69].…”

Section: Healthcare Process 30%mentioning

confidence: 99%

Complex Process Modeling in Process Mining: A Systematic Review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…These processes may include both clinical and nonclinical activities, which are performed by various resources such as doctors, clerks and nurses, and can change for each organization (Rojo et al , 2022; Mans et al , 2015). Distinguishing development possibilities in the health care processes can support to overcome waiting times, increasing the service quality and decrease overcrowding (Vathy-Fogarassy et al , 2022; Konrad et al , 2013). Little developments in healthcare processes may result in a deep impact on the life quality of patients.…”

Section: Related Workmentioning

confidence: 99%

Process mining based on patient waiting time: an application in health processes

Doğan

2022

IJWIS

View full text Add to dashboard Cite

Purpose Similar to many business processes, waiting times are also essential for health care processes, especially in obstetrics and gynecology outpatient department (GOD), because pregnant women may be affected by long waiting times. Since creating process models manually presents subjective and nonrealistic flows, this study aims to meet the need of an objective and realistic method. Design/methodology/approach In this study, the authors investigate time-related bottlenecks in both departments for different doctors by process mining. Process mining is a pragmatic analysis to obtain meaningful insights through event logs. It applies data mining techniques to business process management with more comprehensive perspectives. Process mining in this study enables to automatically create patient flows to compare considering each department and doctor. Findings The study concludes that average waiting times in the GOD are higher than obstetrics outpatient department. However, waiting times in departments can change inversely for different doctors. Research limitations/implications The event log was created by expert opinions because activities in the processes had just starting timestamp. The ending time of activity was computed by considering the average duration of the corresponding activity under a normal distribution. Originality/value This study focuses on administrative (nonclinical) health processes in obstetrics and GOD. It uses a parallel activity log inference algorithm (PALIA) to produce process trees by handling duplicate activities. Infrequent information in health processes can have critical information about the patient. PALIA considers infrequent activities in the event log to extract meaningful information, in contrast to many discovery algorithms.

show abstract

“…It becomes, therefore, crucial that all information is amalgamated in a single source. However, given the great multiplicity of systems involved, which makes data collection complex, process mining techniques could prove very useful as they would allow, starting from the individual events carried out in each division, to obtain the entire process, which could provide an overview that, for example, could ensure good reporting of the examinations performed [18], [19]. In this paper, the first two sections we introduce, explain and give a systematic literature review which evaluates the process mining tools applications in the healthcare scenario.…”

Section: Astesj Issn: 2415-6698mentioning

confidence: 99%

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Striani¹,

Colucci²,

Corallo³

et al. 2022

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Process mining is an innovative technique through which inefficiencies in production systems can be eliminated. This technique has therefore become very important internationally in recent years and is also useful for pursuing the improvement of production systems by extrapolating process knowledge from event logs recorded by information systems. Process mining has easy application in production systems as current business processes are integrated with information systems and this makes data available immediately. This makes the complex nature of industrial operations understandable and, for this reason, process mining could also be used in the healthcare field where cost containment and the quality of service increasing offered to the community has become paramount. The problem is that in this sector, it is much more complex to identify useful data in order to extrapolate the relevant log file. The article aim is to examine the state of the art of the application of process mining in the healthcare sector in order to understand the level of diffusion of these techniques. In the light of this analysis, a case study will then be analysed on the application of process mining techniques in the healthcare sector, and in particular in medical teleconsultation in the field of neuroradiology.

show abstract

Multi-level process mining methodology for exploring disease-specific care processes

Cited by 8 publications

References 40 publications

Complex Process Modeling in Process Mining: A Systematic Review

Complex Process Modeling in Process Mining: A Systematic Review

Process mining based on patient waiting time: an application in health processes

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Contact Info

Product

Resources

About