Asia Pacific Business Process Management: Second Asia by Chun Ouyang, Jae-Yoon Jung

By Chun Ouyang, Jae-Yoon Jung

This e-book constitutes the complaints of the second one Asia Pacific convention on enterprise procedure administration held in Brisbane, QLD, Australia, in July 2014.

In all, 33 contributions from 12 nations have been submitted. After each one submission was once reviewed via at the least 3 software Committee individuals, 9 complete papers have been accredited for e-book during this quantity. those 9 papers conceal numerous issues that may be categorised below 4 major study focuses in BPM: technique mining, procedure modeling and repositories, technique version comparability, and procedure analysis.

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Additional info for Asia Pacific Business Process Management: Second Asia Pacific Conference, AP-BPM 2014, Brisbane, QLD, Australia, July 3-4, 2014. Proceedings

Sample text

Figure 1 represents the overall outpatient process analysis framework. It consists of 4 parts: data integration, data preparation, analysis, and discussion. 1 Data Integration and Data Preparation In order to store the records of patients, resources and so on, various information systems are utilized at hospitals. The HIS (Hospital Information System) consists of several applications, such as PMS, EMR, CPOE, PACS, LIS (Laboratory Information System). Therefore, an integrated database needs to be built by integrating records from each information system.

Features meeting the second criterion include Number of connectors , Connector heterogeneity, Control-flow complexity, etc. g. AND-split, AND-join) are supported in the structured workflow net. g. ). However, both of these two process models are structured workflow net, and can be mined properly by most process mining algorithms. Based on these two criteria, 6 suitable features are selected at last: 1. 2. 3. 4. 5. 6. 4 Number Number Number Number Number Number of of of of of of invisible task : the number of invisible tasks in a model.

Mans et al. suggested a methodology for analyzing healthcare processes by applying process mining, which was based on hospital data from the Netherlands [7]. Moreover, they addressed a way of extracting a social network model and doing performance analysis. Alvaro and Diogo conducted a pattern analysis of outpatient processes to extract the standard behavior and the unusual behavior [1]. In addition, there was a research work to analyze compliance rules of healthcare processes for skins cancer patients [3].

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