Mining processes in dentistry

Business processes in dentistry are quickly evolving towards digital dentistry . This means that many steps in the dental process will increasingly deal with computerized information or computerized half products. A complicating factor in the improvement of process performance in dentistry, however, is the large number of independent dental professionals that are involved in the entire process. In order to reap the benefits of digital dentistry, it is essential to obtain an accurate view on the current processes in practice. In this paper, so called process mining techniques are applied in order to demonstrate that, based on automatically stored data, detailed process knowledge can be obtained on dental processes, e.g. it can be discovered how dental processes are actually executed. To this end, we analyze a real case of a private dental practice, which is responsible for the treatment of patients (diagnosis, placing of implants and the placement of the final restoration), and the dental lab that is responsible for the production of the final restoration. To determine the usefulness of process mining, the entire process has been investigated from three different perspectives: (1) the control-flow perspective, (2) the organizational perspective and (3) the performance perspective. The results clearly show that process mining is useful to gain a deep understanding of dental processes. Also, it becomes clear that dental process are rather complex, which require a considerable amount of flexibility. We argue that the introduction of workflow management technology is needed in order to make digital dentistry a success

Lightweight interacting patient treatment processes

Nick Russell has over 20 years experience in IT, both in Australia and the Netherlands, in a variety of senior management, technical, and research roles. He is currently Chief Technology Officer for a major Australian tools distributor. Prior to this, he was a postdoctoral researcher at Eindhoven University of Technology. He completed his masters and doctoral degrees at Queensland University of Technology. Over the past 7 years, he has been the driving force for the extension of the workflow patterns to the data, resource, and exception handling perspectives and the development of the newYAWL business process modeling reference language. Nick ABSTRACT Processes concerning the diagnosis and treatment of patients cannot be straightjacketed into traditional production-like workflows. They can be best characterized as weakly-connected interacting light-weight workflows where tasks reside at different levels of granularity. Moreover, for each individual patient a doctor proceeds in a step-by-step way deciding about the next steps to be taken. Classical workflow notations fall short in supporting these patient processes as they have been designed to support monolithic processes. Classical notations (WFnets, BPMN, EPCs, etc.) assume that a workflow process can be modeled by specifying the lifecycle of a single case in isolation. To address these problems, we present an extension of the Proclets framework which allows for dividing complex entangled processes into simple autonomous fragments. Additionally, increased emphasis is placed on interaction related aspects such that fragment instances for individual patients can cooperate in any desired way. Finally, we describe an implementation of the Proclets framework. Proclets have been added to the opensource Workflow Management System YAWL to better support inter-workflow support functionalities

Lightweight interacting patient treatment processes

Processes concerning the diagnosis and treatment of patients cannot be straightjacketed into traditional production-like workflows. They can be best characterized as weakly-connected interacting light-weight workflows where tasks reside at different levels of granularity, and for each individual patient a doctor proceeds in a step-by-step way deciding what next steps be taken. Classical workflow notations fall short in supporting these patient processes as they have been designed to support monolithic processes. Classical notations (WF-nets (work flow nets), BPMN (Business Process Model and Notation), EPCs (Electronic Prescriptions for Controlled Substances), etc.) assume that a workflow process can be modeled by specifying the life-cycle of a single case in isolation. To address these problems, the authors present an extension of the Proclets framework which allows for dividing complex entangled processes into simple autonomous fragments. Additionally, increased emphasis is placed on interaction related aspects such that fragment instances for individual patients can cooperate in any desired way. The authors describe an implementation of the Proclets framework. Proclets have been added to the open-source Workflow Management System YAWL to better support inter-workflow support functionalities