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| Content Provider | ACM Digital Library |
|---|---|
| Author | van Genuchten, Michiel Wismeijer, Daniel Reijers, Hajo Mans, Ronny |
| Abstract | 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. |
| Starting Page | 379 |
| Ending Page | 388 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450307819 |
| DOI | 10.1145/2110363.2110407 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-01-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Process mining Workflow management Dentistry |
| Content Type | Text |
| Resource Type | Article |
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