Publicação
Using Process Mining to Analyze an Emergency Service
| dc.contributor.author | Gomes, André | |
| dc.contributor.author | Fialho, Joana | |
| dc.contributor.author | Wanzeller Guedes de Lacerda, Ana Cristina | |
| dc.date.accessioned | 2026-04-14T08:40:14Z | |
| dc.date.available | 2026-04-14T08:40:14Z | |
| dc.date.issued | 2022-07-27 | en_US |
| dc.date.updated | 2026-04-13T18:05:42Z | |
| dc.description.abstract | Digital solutions open up advances in institutions and in the services they provide. Many organizations collect large amounts of data (Big Data), but the value of these data is not readily available. Any possible solution to solve this problem is seen as an opportunity to obtain innovative indications for improving the functioning of the institutions. The health area is an important example in the context of the Big Data problem. Data collected in hospitals, combining log records from various sources, allow for a broader picture of medical processes. The scarcity and onerousness of resources and the growing need to provide health care to the population generate increasing pressures for good management of those processes. A possible solution to solve the mentioned problem is the usage of techniques of knowledge extraction from data, more precisely Process Mining. Thus, this work aims to show the benefits of using Process Mining to improve health processes, in this case in an emergency room. The results of this work are models that allow the analysis of the real functioning on care units, making it possible to draw conclusions about their management, as well as their resources’ use. With this type of information, professionals from each unit can act on existing inefficiencies, allowing them to improve a service that is of great importance to the population. | por |
| dc.description.version | N/A | |
| dc.identifier.doi | 10.5171/2022.607107 | en_US |
| dc.identifier.slug | cv-prod-3090502 | |
| dc.identifier.uri | http://hdl.handle.net/10400.19/9768 | |
| dc.language.iso | N/A | por |
| dc.subject | Process Mining | |
| dc.subject | Big Data in Healthcare | |
| dc.subject | Emergency Service | |
| dc.subject | Process Management | |
| dc.subject | Disco Tool | |
| dc.title | Using Process Mining to Analyze an Emergency Service | en_US |
| dc.type | newspaper article | en_US |
| dspace.entity.type | Publication | |
| person.familyName | Wanzeller Guedes de Lacerda | |
| person.givenName | Ana Cristina | |
| person.identifier.ciencia-id | E81F-11C0-E77C | |
| rcaap.cv.cienciaid | 6D16-185B-43D0 | Joana Rita Silva Fialho | |
| rcaap.rights | openAccess | en_US |
| relation.isAuthorOfPublication | b353121e-fa46-43fe-b4c0-5e9848084d17 | |
| relation.isAuthorOfPublication.latestForDiscovery | b353121e-fa46-43fe-b4c0-5e9848084d17 |
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