Process Mining and the Black Swan: An Empirical Analysis of the Influence of Unobserved Behavior on the Quality of Mined Process Models

2018 ◽  
pp. 256-268 ◽  
Author(s):  
Jana-Rebecca Rehse ◽  
Peter Fettke ◽  
Peter Loos
Keyword(s):  
Empirical Analysis ◽  
Process Mining ◽  
Process Models ◽  
Black Swan

Application of process mining to assess the data quality of routinely collected time-based performance data sourced from electronic health records by validating process conformance

2016 ◽  
Vol 22 (4) ◽  
pp. 1017-1029 ◽  
Author(s):  
Lua Perimal-Lewis ◽  
David Teubner ◽  
Paul Hakendorf ◽  
Chris Horwood
Keyword(s):  
Electronic Health Records ◽  
Data Quality ◽  
Performance Metrics ◽  
Process Mining ◽  
Hospital Performance ◽  
Process Models ◽  
Patient Journey ◽  
Health Records ◽  
Electronic Health

Effective and accurate use of routinely collected health data to produce Key Performance Indicator reporting is dependent on the underlying data quality. In this research, Process Mining methodology and tools were leveraged to assess the data quality of time-based Emergency Department data sourced from electronic health records. This research was done working closely with the domain experts to validate the process models. The hospital patient journey model was used to assess flow abnormalities which resulted from incorrect timestamp data used in time-based performance metrics. The research demonstrated process mining as a feasible methodology to assess data quality of time-based hospital performance metrics. The insight gained from this research enabled appropriate corrective actions to be put in place to address the data quality issues.

scholarly journals Simplified Process Model Discovery Based on Role-Oriented Genetic Mining

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Weidong Zhao ◽  
Xi Liu ◽  
Weihui Dai
Keyword(s):  
Process Model ◽  
Process Mining ◽  
Fitness Function ◽  
Control Flow ◽  
Process Models ◽  
Programming Approach ◽  
Event Logs ◽  
Process Complexity

Process mining is automated acquisition of process models from event logs. Although many process mining techniques have been developed, most of them are based on control flow. Meanwhile, the existing role-oriented process mining methods focus on correctness and integrity of roles while ignoring role complexity of the process model, which directly impacts understandability and quality of the model. To address these problems, we propose a genetic programming approach to mine the simplified process model. Using a new metric of process complexity in terms of roles as the fitness function, we can find simpler process models. The new role complexity metric of process models is designed from role cohesion and coupling, and applied to discover roles in process models. Moreover, the higher fitness derived from role complexity metric also provides a guideline for redesigning process models. Finally, we conduct case study and experiments to show that the proposed method is more effective for streamlining the process by comparing with related studies.

scholarly journals How social challenges affect children’s regulation and assignment quality in hypermedia: a process mining study

2019 ◽  
Vol 14 (2) ◽  
pp. 189-213
Author(s):  
Cindy Paans ◽  
Erdem Onan ◽  
Inge Molenaar ◽  
Ludo Verhoeven ◽  
Eliane Segers
Keyword(s):  
Cognitive Processing ◽  
Learning Process ◽  
Process Mining ◽  
Process Models ◽  
Vicious Cycle ◽  
Social Challenges ◽  
Social Challenge ◽  
Low Levels ◽  
Sequential Analyses

Abstract The present study investigated the extent to which 18 dyads in 5th and 6th grade, who experienced low levels of social challenge, differed from 12 dyads who experience high levels of social challenge in terms of the quality of their written assignment, as well as the frequency and sequential pattern of their cognitive, metacognitive, relational, and off-task activities during a collaborative hypermedia assignment. Sequential analyses were performed by means of process mining with a fuzzy miner algorithm. Results showed that assignment quality was higher for low social challenge dyads. In addition, these more successful dyads showed more cognitive processing activities, more high-cognition, and fewer off-task activities. In terms of their process models, low and high challenge dyads showed marked differences. More specifically, high social challenge dyads showed a vicious cycle of social challenges and off-task behaviors, whereas low social challenge dyads engaged in high-cognition. In addition, for low challenge dyads, but not high challenge dyads, the various metacognitive activities were closely connected to each other. These findings indicate that social challenges not only affect assignment quality, but also fundamentally affect the overall learning process.

scholarly journals Cross-Organization Emergency Response Process Mining: An Approach Based on Petri Nets

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Cong Liu ◽  
Huiling Li ◽  
Qingtian Zeng ◽  
Ting Lu ◽  
Caihong Li
Keyword(s):  
Petri Nets ◽  
Emergency Response ◽  
Resource Sharing ◽  
Process Mining ◽  
Process Models ◽  
Response Process ◽  
Extensive Experience ◽  
Event Logs ◽  
Collaboration Patterns ◽  
Sharing Patterns

To support effective emergency disposal, organizations need to collaborate with each other to complete the emergency mission that cannot be handled by a single organization. In general, emergency disposal that involves multiple organizations is typically organized as a group of interactive processes, known as cross-organization emergency response processes (CERPs). The construction of CERPs is a time-consuming and error-prone task that requires practitioners to have extensive experience and business background. Process mining aims to construct process models by analyzing event logs. However, existing process mining techniques cannot be applied directly to discover CERPs since we have to consider the complexity of various collaborations among different organizations, e.g., message exchange and resource sharing patterns. To tackle this challenge, a CERP model mining method is proposed in this paper. More specifically, we first extend classical Petri nets with resource and message attributes, known as resource and message aware Petri nets (RMPNs). Then, intra-organization emergency response process (IERP) models that are represented as RMPNs are discovered from emergency drilling event logs. Next, collaboration patterns among emergency organizations are formally defined and discovered. Finally, CERP models are obtained by merging IERP models and collaboration patterns. Through comparative experimental evaluation using the fire emergency drilling event log, we illustrate that the proposed approach facilitates the discovery of high-quality CERP models than existing state-of-the-art approaches.

Quality of Medical Care and Choice of Medical Treatment in Kenya: An Empirical Analysis

1993 ◽  
Vol 28 (4) ◽  
pp. 838 ◽  
Author(s):  
Germano Mwabu ◽  
Martha Ainsworth ◽  
Andrew Nyamete
Keyword(s):  
Medical Treatment ◽  
Medical Care ◽  
Empirical Analysis ◽  
Quality Of Medical Care

scholarly journals Business process mining

2017 ◽  
Vol 01 (01) ◽  
pp. 1630004 ◽  
Author(s):  
Asef Pourmasoumi ◽  
Ebrahim Bagheri
Keyword(s):  
Process Mining ◽  
Status Quo ◽  
Process Models ◽  
Added Value ◽  
Conformance Checking ◽  
Event Logs ◽  
Organizational Information ◽  
Organization Process ◽  
The Status ◽  
Business Process Mining

One of the most valuable assets of an organization is its organizational data. The analysis and mining of this potential hidden treasure can lead to much added-value for the organization. Process mining is an emerging area that can be useful in helping organizations understand the status quo, check for compliance and plan for improving their processes. The aim of process mining is to extract knowledge from event logs of today’s organizational information systems. Process mining includes three main types: discovering process models from event logs, conformance checking and organizational mining. In this paper, we briefly introduce process mining and review some of its most important techniques. Also, we investigate some of the applications of process mining in industry and present some of the most important challenges that are faced in this area.

Sign in / Sign up

Export Citation Format

Share Document