Loading…
Knowledge Discovery through Mining Emergency Department Data
The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modele...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c135t-993af413a93f4fae5d156255abeb1d100e7087537b7f45a7d010e41f819ddc5d3 |
---|---|
cites | |
container_end_page | 142c |
container_issue | |
container_start_page | 142c |
container_title | |
container_volume | |
creator | Ceglowski, A. Churilov, L. Wassertheil, J. |
description | The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modeled the treatment of patients. This paper describes how the combination of a process philosophy with data mining resulted in the discovery of definitive "treatment pathways". These pathways comprehensively model treatment of patients. Examination of these pathways indicated that the ratio of treatment procedures remained fairly constant. It was concluded that workload in the emergency department varies only by number of presentations, not in type of procedure carried out. Some applications of this knowledge are discussed. |
doi_str_mv | 10.1109/HICSS.2005.371 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_1385525</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1385525</ieee_id><sourcerecordid>1385525</sourcerecordid><originalsourceid>FETCH-LOGICAL-c135t-993af413a93f4fae5d156255abeb1d100e7087537b7f45a7d010e41f819ddc5d3</originalsourceid><addsrcrecordid>eNotzE1Pg0AQANCNH4lYe_XihT8Azuwyu2zixUC1jTUequdmYQeKKdAAavj3HvT0bk-IW4QYEez9epPtdrEEoFgZPBOBJCMjnWp5LpbWpGC0JSl1ShciQFIQoQa6Etfj-AkgIUEdiIeXrv85sq85zJux7L95mMPpMPRf9SF8bbqmq8NVy0PNXTmHOZ_cMLXcTWHuJncjLit3HHn570J8PK3es3W0fXveZI_bqERFU2StclWCyllVJZVj8khaErmCC_QIwAZSQ8oUpkrIGQ8InGCVovW-JK8W4u7vbZh5fxqa1g3zHlVKJEn9AgXpSVc</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Knowledge Discovery through Mining Emergency Department Data</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Ceglowski, A. ; Churilov, L. ; Wassertheil, J.</creator><creatorcontrib>Ceglowski, A. ; Churilov, L. ; Wassertheil, J.</creatorcontrib><description>The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modeled the treatment of patients. This paper describes how the combination of a process philosophy with data mining resulted in the discovery of definitive "treatment pathways". These pathways comprehensively model treatment of patients. Examination of these pathways indicated that the ratio of treatment procedures remained fairly constant. It was concluded that workload in the emergency department varies only by number of presentations, not in type of procedure carried out. Some applications of this knowledge are discussed.</description><identifier>ISSN: 1530-1605</identifier><identifier>ISBN: 9780769522685</identifier><identifier>ISBN: 0769522688</identifier><identifier>EISSN: 2572-6862</identifier><identifier>DOI: 10.1109/HICSS.2005.371</identifier><language>eng</language><publisher>IEEE</publisher><subject>Australia ; Data analysis ; Data mining ; Disaster management ; Fitting ; Government ; Hospitals ; Industrial engineering ; Medical services ; Medical treatment</subject><ispartof>Proceedings of the 38th Annual Hawaii International Conference on System Sciences, 2005, p.142c-142c</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c135t-993af413a93f4fae5d156255abeb1d100e7087537b7f45a7d010e41f819ddc5d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1385525$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1385525$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ceglowski, A.</creatorcontrib><creatorcontrib>Churilov, L.</creatorcontrib><creatorcontrib>Wassertheil, J.</creatorcontrib><title>Knowledge Discovery through Mining Emergency Department Data</title><title>Proceedings of the 38th Annual Hawaii International Conference on System Sciences</title><addtitle>HICSS</addtitle><description>The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modeled the treatment of patients. This paper describes how the combination of a process philosophy with data mining resulted in the discovery of definitive "treatment pathways". These pathways comprehensively model treatment of patients. Examination of these pathways indicated that the ratio of treatment procedures remained fairly constant. It was concluded that workload in the emergency department varies only by number of presentations, not in type of procedure carried out. Some applications of this knowledge are discussed.</description><subject>Australia</subject><subject>Data analysis</subject><subject>Data mining</subject><subject>Disaster management</subject><subject>Fitting</subject><subject>Government</subject><subject>Hospitals</subject><subject>Industrial engineering</subject><subject>Medical services</subject><subject>Medical treatment</subject><issn>1530-1605</issn><issn>2572-6862</issn><isbn>9780769522685</isbn><isbn>0769522688</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotzE1Pg0AQANCNH4lYe_XihT8Azuwyu2zixUC1jTUequdmYQeKKdAAavj3HvT0bk-IW4QYEez9epPtdrEEoFgZPBOBJCMjnWp5LpbWpGC0JSl1ShciQFIQoQa6Etfj-AkgIUEdiIeXrv85sq85zJux7L95mMPpMPRf9SF8bbqmq8NVy0PNXTmHOZ_cMLXcTWHuJncjLit3HHn570J8PK3es3W0fXveZI_bqERFU2StclWCyllVJZVj8khaErmCC_QIwAZSQ8oUpkrIGQ8InGCVovW-JK8W4u7vbZh5fxqa1g3zHlVKJEn9AgXpSVc</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Ceglowski, A.</creator><creator>Churilov, L.</creator><creator>Wassertheil, J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2005</creationdate><title>Knowledge Discovery through Mining Emergency Department Data</title><author>Ceglowski, A. ; Churilov, L. ; Wassertheil, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c135t-993af413a93f4fae5d156255abeb1d100e7087537b7f45a7d010e41f819ddc5d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Australia</topic><topic>Data analysis</topic><topic>Data mining</topic><topic>Disaster management</topic><topic>Fitting</topic><topic>Government</topic><topic>Hospitals</topic><topic>Industrial engineering</topic><topic>Medical services</topic><topic>Medical treatment</topic><toplevel>online_resources</toplevel><creatorcontrib>Ceglowski, A.</creatorcontrib><creatorcontrib>Churilov, L.</creatorcontrib><creatorcontrib>Wassertheil, J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ceglowski, A.</au><au>Churilov, L.</au><au>Wassertheil, J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Knowledge Discovery through Mining Emergency Department Data</atitle><btitle>Proceedings of the 38th Annual Hawaii International Conference on System Sciences</btitle><stitle>HICSS</stitle><date>2005</date><risdate>2005</risdate><spage>142c</spage><epage>142c</epage><pages>142c-142c</pages><issn>1530-1605</issn><eissn>2572-6862</eissn><isbn>9780769522685</isbn><isbn>0769522688</isbn><abstract>The complexity of hospital emergency department operations limits comprehension and inhibits efforts to improve efficiency. Attempts have been made to reduce the complexity by streaming patients into similar classes of treatment or grouping them into similar cases. These have not successfully modeled the treatment of patients. This paper describes how the combination of a process philosophy with data mining resulted in the discovery of definitive "treatment pathways". These pathways comprehensively model treatment of patients. Examination of these pathways indicated that the ratio of treatment procedures remained fairly constant. It was concluded that workload in the emergency department varies only by number of presentations, not in type of procedure carried out. Some applications of this knowledge are discussed.</abstract><pub>IEEE</pub><doi>10.1109/HICSS.2005.371</doi></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1530-1605 |
ispartof | Proceedings of the 38th Annual Hawaii International Conference on System Sciences, 2005, p.142c-142c |
issn | 1530-1605 2572-6862 |
language | eng |
recordid | cdi_ieee_primary_1385525 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Australia Data analysis Data mining Disaster management Fitting Government Hospitals Industrial engineering Medical services Medical treatment |
title | Knowledge Discovery through Mining Emergency Department Data |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T22%3A42%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Knowledge%20Discovery%20through%20Mining%20Emergency%20Department%20Data&rft.btitle=Proceedings%20of%20the%2038th%20Annual%20Hawaii%20International%20Conference%20on%20System%20Sciences&rft.au=Ceglowski,%20A.&rft.date=2005&rft.spage=142c&rft.epage=142c&rft.pages=142c-142c&rft.issn=1530-1605&rft.eissn=2572-6862&rft.isbn=9780769522685&rft.isbn_list=0769522688&rft_id=info:doi/10.1109/HICSS.2005.371&rft_dat=%3Cieee_6IE%3E1385525%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c135t-993af413a93f4fae5d156255abeb1d100e7087537b7f45a7d010e41f819ddc5d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1385525&rfr_iscdi=true |