A Framework for Recommending Resource Allocation Based on Process Mining

PRANAS: A Process Analytics System Based on Process Warehouse and Cube for Supply Chain Management

Most organizations need to monitor and assess their business activities. In order to support the performance analysis of the business activities in a more systematic manner, in this research, we introduce a PRocess ANalytics System, called PRANAS. The system adopts process warehouses and process cubes to support process-oriented analysis, as well as data-oriented analysis. In this research, the process warehouse and cube were designed to assess business performances for supply chain management, specifically under the SCOR standard models. Furthermore, the process cube was constructed based on process-related dimensions such as time, case type, and event class to support process mining. Finally, we exemplify how the system can be applied to process analytics with three use cases of process discovery, data analytics, and decision point analysis. It is expected that the proposed system can be a helpful reference model when business process analyst designs process analytics systems in the process-oriented perspective, as well as in the data-oriented perspective.

Discovering role interaction models in the Emergency Room using Process Mining

OBJECTIVES

A coordinated collaboration among different healthcare professionals in Emergency Room (ER) processes is critical to promptly care for patients who arrive at the hospital in a delicate health condition, claiming for an immediate attention. The aims of this study are (i) to discover role interaction models in (ER) processes using process mining techniques; (ii) to understand how healthcare professionals are currently collaborating; and (iii) to provide useful knowledge that can help to improve ER processes.

METHODS

A four step method based on process mining techniques is proposed. An ER process of a university hospital was considered as a case study, using 7160 episodes that contains specific ER episode attributes.

RESULTS

Insights about how healthcare professionals collaborate in the ER was discovered, including the identification of a prevalent role interaction model along the major triage categories and specific role interaction models for different diagnoses. Also, common and exceptional professional interaction models were discovered at the role level.

CONCLUSIONS

This study allows the discovery of role interaction models through the use of real-life clinical data and process mining techniques. Results show a useful way of providing relevant insights about how healthcare professionals collaborate, uncovering opportunities for process improvement.