Tag: process modeling

IS-HEART presentation June 5th: Dynamic Clinical Checklist Support Systems

Also see the online agenda item for this session.

Speakers: Lonneke Vermeulen (TU/e – IS) and Ashley De Bie Dekker (Catharina Ziekenhuis Eindhoven)
Title: The first pilot study of DCCSS Tracebook, from idea to results

Abstract: Atul Gawandas’ Checklist Manifesto made the medical world realize the high potential of clinical safety checklists in reducing medical errors and improving patient safety. As the current computerized checklist support systems were too static, the Brainbridge II program (a collaboration between the Eindhoven University of Technology, Zhejiang University, Philips Research and Catharina Hospital Eindhoven) developed a system that can individualize checklists based on information from the patient’s medical record while also considering the context of the clinical workflows. By the end of last year (2014) the first pilot study of the Dynamic Clinical Checklist Support System (DCCSS) Tracebook took place in the hospital. In this presentation we will guide you from the beginning of this project to the results of the first pilot study.

After a short introduction of the Tracebook system, we will describe how we developed these dynamic checklists, which research design we followed and how the pilot study was set up. We will conclude with the promising results from the study and afterwards there is time for discussion.

IS-HEART Presentation by Juby Joseph Ninan

Title: Integrating simulation and enactment models: a reality check

See Agenda Item

Abstract:

As organizations grow larger and the complexity of their business processes increases, it becomes important to use information systems that can use software tools to control, coordinate, execute and monitor their processes. There are different vendors that offer such business process management software and services to automate a company’s business processes, enhance their visibility and control, and provide support for continuous improvement. Business process simulation plays an important role for analyzing processes for continuous improvement. Here simulation is used to study the dynamic behavior of processes over time, thereby showing how the performance of processes or resources can be influenced by changes in the system or environment.

Business Process Simulation is usually used to support strategic decision making in companies, where the objective is to move the organization towards achieving its long term goals. Here simulation helps to understand how a particular decision affects long term behavior of the process. However, these kinds of simulation experiments are not useful to support management or operational decision making, where short term behavior of processes is to be analyzed.

For short term simulations, we can use information readily made available from the business process management system itself, without the need for additional modeling. The BPMS will have knowledge of the process structure definition, the current state of the process instances and the history records of the process execution, all of which can be used to run short- term simulation experiments. The process structure definition will contain information about the control flow and the data flow. The current state of process instances can be used to load the initial state of the simulation model, and analyzing history records may give us simulation relevant properties such as arrival rate of instances, execution time of activities, etc.

This thesis is an attempt to explore the current simulation capabilities in the BPM Suite jBPM (whose core is a light weight, extensible workflow engine that allows execution of business processes using the BPMN 2.0 specification) and also investigate whether such short term simulation experiments can be supported by the tool.

Executable Modeling

This semester, students of the TU/e course “Executable Models of Operational Processes” will make executable models for two healthcare case studies. One case is on skin cancer treatment (regarding the logistic approach of a “one stop shop”) while the other case is on dialysis (regarding the use of home dialysis equipment, etc.). Students will analyze the effect of process redesigns on key performance indicators by means of simulations in CPNTools.