An integrated data management approach to manage health care data
| dc.contributor.author | Guerra, Diogo | |
| dc.contributor.author | Gawlick, Ute | |
| dc.contributor.author | Bizarro, Pedro | |
| dc.contributor.author | Gawlick, Dieter | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Lehner, Wolfgang | |
| dc.contributor.editor | Mitschang, Bernhard | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Schwarz, Holger | |
| dc.date.accessioned | 2019-01-17T10:36:46Z | |
| dc.date.available | 2019-01-17T10:36:46Z | |
| dc.date.issued | 2011 | |
| dc.description.abstract | Surgical Intensive Care Unit data management systems suffer from three problems: data and meta-data are spread out in different systems, there is a high rate of false positives, and data mining predictions are not presented in a timely manner to health care staff. These problems lead to missed opportunities for data analysis, alert fatigue and reactive, instead of proactive analysis. In this demo, and in contrast to current CEP efforts, we present a proof-of-concept, integrated engine that runs entirely within a single database system. The resulting novel and low cost event processing architecture uses features and components commercially available from Oracle Corporation. We demonstrate how multiple data from a realworld surgical intensive care unit (bed-side sensors and all other information available about the patients) are assimilated and queries, alarms, and rules are applied. The system is highly customizable: staff can point and click to create, edit and delete rules, compose personal rules (per patient, per doctor, per patientdoctor), and, while maintaining a hierarchy of rules, create rules that inherit and override previous rules. The system is also integrated with the data mining module, being able to offer predictions of high risk situations in real-time (e.g., predictions of cardiac arrests). Using simulated inputs, we show the complete system working, including writing and editing rules, triggering simple alerts, prediction of cardiac arrests, and visual explanation of predictions. | en |
| dc.identifier.isbn | 978-3-88579-274-1 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/19603 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW) | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-180 | |
| dc.title | An integrated data management approach to manage health care data | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 605 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 596 | |
| gi.conference.date | 02.-04.03.2011 | |
| gi.conference.location | Kaiserslautern | |
| gi.conference.sessiontitle | Regular Research Papers |
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