Identifying Ontario geographic regions to assess adults who present to hospital with laboratory-defined conditions: a descriptive study
In 2007, an electronic repository called the Ontario Laboratories Information System (OLIS) was introduced to allow health care providers timely access to laboratory test results. Since not all laboratories began submitting their data to OLIS simultaneously, we sought to create a date-dependent tabl...
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Veröffentlicht in: | CMAJ open 2019-10, Vol.7 (4), p.E624-E629 |
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creator | Iskander, Carina McArthur, Eric Nash, Danielle M Gandhi-Banga, Sonja Weir, Matthew A Muanda, Flory Tsobo Garg, Amit X |
description | In 2007, an electronic repository called the Ontario Laboratories Information System (OLIS) was introduced to allow health care providers timely access to laboratory test results. Since not all laboratories began submitting their data to OLIS simultaneously, we sought to create a date-dependent table of geographic regions (forward sortation areas [FSAs]) from which people would likely present to a hospital linked to OLIS.
In this descriptive study, we used administrative data to capture adults in Ontario who presented to the emergency department for any reason from 2007 to 2017. To assess changes over time, we classified all emergency department visits into fiscal quarters. The primary outcome measure was the proportion of people in a given FSA presenting to an emergency department at an OLIS-linked hospital (v. a hospital not linked to OLIS). To be included in the catchment area, at least 90% of all emergency department visits in a given quarter from a given FSA must have occurred at an OLIS-linked hospital.
By Dec. 31, 2017, 323 (61.4%) of 526 Ontario FSAs were in the catchment area (a population of about 8.5 million). There were no differences in selected demographic characteristics or comorbidities between people residing within the catchment area of OLIS-linked hospitals and those residing in the catchment area of unlinked hospitals on Dec. 31, 2017. We used the FSA information to construct a date-dependent table of geographic areas likely to have hospital laboratory data available in OLIS for future studies.
We identified relevant Ontario geographic regions from which people would likely present to a hospital linked to OLIS. These geographic regions constitute a catchment area that may be used in future studies to capture adults who present to an OLIS-linked hospital with laboratory-defined conditions such as acute kidney injury, hyperkalemia and hyponatremia. |
doi_str_mv | 10.9778/cmajo.20190065 |
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In this descriptive study, we used administrative data to capture adults in Ontario who presented to the emergency department for any reason from 2007 to 2017. To assess changes over time, we classified all emergency department visits into fiscal quarters. The primary outcome measure was the proportion of people in a given FSA presenting to an emergency department at an OLIS-linked hospital (v. a hospital not linked to OLIS). To be included in the catchment area, at least 90% of all emergency department visits in a given quarter from a given FSA must have occurred at an OLIS-linked hospital.
By Dec. 31, 2017, 323 (61.4%) of 526 Ontario FSAs were in the catchment area (a population of about 8.5 million). There were no differences in selected demographic characteristics or comorbidities between people residing within the catchment area of OLIS-linked hospitals and those residing in the catchment area of unlinked hospitals on Dec. 31, 2017. We used the FSA information to construct a date-dependent table of geographic areas likely to have hospital laboratory data available in OLIS for future studies.
We identified relevant Ontario geographic regions from which people would likely present to a hospital linked to OLIS. These geographic regions constitute a catchment area that may be used in future studies to capture adults who present to an OLIS-linked hospital with laboratory-defined conditions such as acute kidney injury, hyperkalemia and hyponatremia.</description><identifier>ISSN: 2291-0026</identifier><identifier>EISSN: 2291-0026</identifier><identifier>DOI: 10.9778/cmajo.20190065</identifier><identifier>PMID: 31641060</identifier><language>eng</language><publisher>Canada: Joule Inc. or its licensors</publisher><ispartof>CMAJ open, 2019-10, Vol.7 (4), p.E624-E629</ispartof><rights>Copyright 2019, Joule Inc. or its licensors.</rights><rights>Copyright 2019, Joule Inc. or its licensors 2019 Joule Inc. or its licensors</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3055-41ff015381f4bb7bf829c26e922a3bbb22776ce5bda31a5f9e8eb8744a8288763</citedby><cites>FETCH-LOGICAL-c3055-41ff015381f4bb7bf829c26e922a3bbb22776ce5bda31a5f9e8eb8744a8288763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944071/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944071/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27922,27923,53789,53791</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31641060$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Iskander, Carina</creatorcontrib><creatorcontrib>McArthur, Eric</creatorcontrib><creatorcontrib>Nash, Danielle M</creatorcontrib><creatorcontrib>Gandhi-Banga, Sonja</creatorcontrib><creatorcontrib>Weir, Matthew A</creatorcontrib><creatorcontrib>Muanda, Flory Tsobo</creatorcontrib><creatorcontrib>Garg, Amit X</creatorcontrib><title>Identifying Ontario geographic regions to assess adults who present to hospital with laboratory-defined conditions: a descriptive study</title><title>CMAJ open</title><addtitle>CMAJ Open</addtitle><description>In 2007, an electronic repository called the Ontario Laboratories Information System (OLIS) was introduced to allow health care providers timely access to laboratory test results. Since not all laboratories began submitting their data to OLIS simultaneously, we sought to create a date-dependent table of geographic regions (forward sortation areas [FSAs]) from which people would likely present to a hospital linked to OLIS.
In this descriptive study, we used administrative data to capture adults in Ontario who presented to the emergency department for any reason from 2007 to 2017. To assess changes over time, we classified all emergency department visits into fiscal quarters. The primary outcome measure was the proportion of people in a given FSA presenting to an emergency department at an OLIS-linked hospital (v. a hospital not linked to OLIS). To be included in the catchment area, at least 90% of all emergency department visits in a given quarter from a given FSA must have occurred at an OLIS-linked hospital.
By Dec. 31, 2017, 323 (61.4%) of 526 Ontario FSAs were in the catchment area (a population of about 8.5 million). There were no differences in selected demographic characteristics or comorbidities between people residing within the catchment area of OLIS-linked hospitals and those residing in the catchment area of unlinked hospitals on Dec. 31, 2017. We used the FSA information to construct a date-dependent table of geographic areas likely to have hospital laboratory data available in OLIS for future studies.
We identified relevant Ontario geographic regions from which people would likely present to a hospital linked to OLIS. These geographic regions constitute a catchment area that may be used in future studies to capture adults who present to an OLIS-linked hospital with laboratory-defined conditions such as acute kidney injury, hyperkalemia and hyponatremia.</description><issn>2291-0026</issn><issn>2291-0026</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNpVUctq3DAUFaUhCWm2WRYtu_FUkm1J7qJQQh-BQDbNWkjyla3gsVxdOWG-IL_dmeZBuroXzhMOIRecbTql9Ge_tXdpIxjvGJPtO3IqRMcrxoR8_-Y_IeeId4wxzpRouT4mJzWXDWeSnZLHqx7mEsMuzgO9mYvNMdEB0pDtMkZPMwwxzUhLohYREKnt16kgfRgTXTLgXn0Ax4RLLHaiD7GMdLIuZVtS3lU9hDhDT32a-1gOXl-opT2gz3Ep8R4olrXffSBHwU4I58_3jNz--P778ld1ffPz6vLbdeVr1rZVw0NgvK01D41zygUtOi8kdELY2jknhFLSQ-t6W3Pbhg40OK2axmqhtZL1Gfn65Lusbgu939fPdjJLjlubdybZaP5H5jiaId0b2TUNU3xv8OnZIKc_K2Ax24gepsnOkFY0omaaK8mbQ9bmiepzQswQXmM4M4cBzb8BzcuAe8HHt-Ve6S9z1X8B_Fubyg</recordid><startdate>20191001</startdate><enddate>20191001</enddate><creator>Iskander, Carina</creator><creator>McArthur, Eric</creator><creator>Nash, Danielle M</creator><creator>Gandhi-Banga, Sonja</creator><creator>Weir, Matthew A</creator><creator>Muanda, Flory Tsobo</creator><creator>Garg, Amit X</creator><general>Joule Inc. or its licensors</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20191001</creationdate><title>Identifying Ontario geographic regions to assess adults who present to hospital with laboratory-defined conditions: a descriptive study</title><author>Iskander, Carina ; McArthur, Eric ; Nash, Danielle M ; Gandhi-Banga, Sonja ; Weir, Matthew A ; Muanda, Flory Tsobo ; Garg, Amit X</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3055-41ff015381f4bb7bf829c26e922a3bbb22776ce5bda31a5f9e8eb8744a8288763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Iskander, Carina</creatorcontrib><creatorcontrib>McArthur, Eric</creatorcontrib><creatorcontrib>Nash, Danielle M</creatorcontrib><creatorcontrib>Gandhi-Banga, Sonja</creatorcontrib><creatorcontrib>Weir, Matthew A</creatorcontrib><creatorcontrib>Muanda, Flory Tsobo</creatorcontrib><creatorcontrib>Garg, Amit X</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>CMAJ open</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Iskander, Carina</au><au>McArthur, Eric</au><au>Nash, Danielle M</au><au>Gandhi-Banga, Sonja</au><au>Weir, Matthew A</au><au>Muanda, Flory Tsobo</au><au>Garg, Amit X</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying Ontario geographic regions to assess adults who present to hospital with laboratory-defined conditions: a descriptive study</atitle><jtitle>CMAJ open</jtitle><addtitle>CMAJ Open</addtitle><date>2019-10-01</date><risdate>2019</risdate><volume>7</volume><issue>4</issue><spage>E624</spage><epage>E629</epage><pages>E624-E629</pages><issn>2291-0026</issn><eissn>2291-0026</eissn><abstract>In 2007, an electronic repository called the Ontario Laboratories Information System (OLIS) was introduced to allow health care providers timely access to laboratory test results. Since not all laboratories began submitting their data to OLIS simultaneously, we sought to create a date-dependent table of geographic regions (forward sortation areas [FSAs]) from which people would likely present to a hospital linked to OLIS.
In this descriptive study, we used administrative data to capture adults in Ontario who presented to the emergency department for any reason from 2007 to 2017. To assess changes over time, we classified all emergency department visits into fiscal quarters. The primary outcome measure was the proportion of people in a given FSA presenting to an emergency department at an OLIS-linked hospital (v. a hospital not linked to OLIS). To be included in the catchment area, at least 90% of all emergency department visits in a given quarter from a given FSA must have occurred at an OLIS-linked hospital.
By Dec. 31, 2017, 323 (61.4%) of 526 Ontario FSAs were in the catchment area (a population of about 8.5 million). There were no differences in selected demographic characteristics or comorbidities between people residing within the catchment area of OLIS-linked hospitals and those residing in the catchment area of unlinked hospitals on Dec. 31, 2017. We used the FSA information to construct a date-dependent table of geographic areas likely to have hospital laboratory data available in OLIS for future studies.
We identified relevant Ontario geographic regions from which people would likely present to a hospital linked to OLIS. These geographic regions constitute a catchment area that may be used in future studies to capture adults who present to an OLIS-linked hospital with laboratory-defined conditions such as acute kidney injury, hyperkalemia and hyponatremia.</abstract><cop>Canada</cop><pub>Joule Inc. or its licensors</pub><pmid>31641060</pmid><doi>10.9778/cmajo.20190065</doi><oa>free_for_read</oa></addata></record> |
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title | Identifying Ontario geographic regions to assess adults who present to hospital with laboratory-defined conditions: a descriptive study |
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