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INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.

Rowena Griffiths, Laura Herbert Orcid Logo, Ashley Akbari Orcid Logo, Rowena Bailey, Joe Hollinghurst, Richard Pugh Orcid Logo, Tamas Szakmany Orcid Logo, Fatemeh Torabi Orcid Logo, Ronan Lyons Orcid Logo

International Journal of Population Data Science, Volume: 7, Issue: 1

Swansea University Authors: Rowena Griffiths, Laura Herbert Orcid Logo, Ashley Akbari Orcid Logo, Rowena Bailey, Joe Hollinghurst, Fatemeh Torabi Orcid Logo, Ronan Lyons Orcid Logo

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DOI (Published version): 10.23889/ijpds.v7i1.1724

Abstract

IntroductionCritical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICU...

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Published in: International Journal of Population Data Science
ISSN: 2399-4908
Published: Swansea University 2022
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fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-08-15T15:23:05.6055611</datestamp><bib-version>v2</bib-version><id>60604</id><entry>2022-07-22</entry><title>INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.</title><swanseaauthors><author><sid>381464f639f98bd388c29326ca7f862c</sid><firstname>Rowena</firstname><surname>Griffiths</surname><name>Rowena Griffiths</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>0d5765f5486b80e173366af9a61ee200</sid><ORCID>0000-0001-7580-7413</ORCID><firstname>Laura</firstname><surname>Herbert</surname><name>Laura Herbert</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>455e2c1e6193448f6269b9e72acaf865</sid><firstname>Rowena</firstname><surname>Bailey</surname><name>Rowena Bailey</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>d7c51b69270b644a11b904629fe56ab0</sid><firstname>Joe</firstname><surname>Hollinghurst</surname><name>Joe Hollinghurst</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>f569591e1bfb0e405b8091f99fec45d3</sid><ORCID>0000-0002-5853-4625</ORCID><firstname>Fatemeh</firstname><surname>Torabi</surname><name>Fatemeh Torabi</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2022-07-22</date><deptcode>HDAT</deptcode><abstract>IntroductionCritical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research.ObjectiveTo describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care.MethodTo demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales.ResultsWhen applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) hadan emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission.ConclusionThis methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways.</abstract><type>Journal Article</type><journal>International Journal of Population Data Science</journal><volume>7</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Swansea University</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2399-4908</issnElectronic><keywords>intensive care; critical care; electronic health records; linkable research data; ICNARC</keywords><publishedDay>18</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-07-18</publishedDate><doi>10.23889/ijpds.v7i1.1724</doi><url/><notes>Data availability:The linkable data sources used in this study are available inthe SAIL Databank at Swansea University, Swansea, UK, butas restrictions apply, they are not publicly available. SAIL hasestablished an application process to be followed by anyonewho would like to access data for approved research purposesat https://www.saildatabank.com/application-process. Whenaccess has been granted, it is gained through a privacyprotecting safe haven and remote access system referred toas the SAIL Gateway.</notes><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported by the Con-COV team funded by theMedical Research Council (grant number: MR/V028367/1).This work was supported by Health Data Research UK, whichreceives its funding from HDR UK Ltd (HDR-9006) funded bythe UK Medical Research Council, Engineering and PhysicalSciences Research Council, Economic and Social ResearchCouncil, Department of Health and Social Care (England),Chief Scientist Office of the Scottish Government Health andSocial Care Directorates, Health and Social Care Researchand Development Division (Welsh Government), Public HealthAgency (Northern Ireland), British Heart Foundation (BHF)and the Wellcome Trust. his work was supported by the ADRWales programme of work. The ADR Wales programme ofwork is aligned to the priority themes as identified in the WelshGovernment&#x2019;s national strategy: Prosperity for All. ADR Walesbrings together data science experts at Swansea UniversityMedical School, staff from the Wales Institute of Social andEconomic Research, Data and Methods (WISERD) at CardiffUniversity and specialist teams within the Welsh Governmentto develop new evidence which supports Prosperity for Allby using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of theEconomic and Social Research Council (part of UK Researchand Innovation) funded ADR UK (grant ES/S007393/1). Thiswork was supported by the Wales COVID-19 Evidence Centre,funded by Health and Care Research Wales.</funders><projectreference/><lastEdited>2022-08-15T15:23:05.6055611</lastEdited><Created>2022-07-22T19:11:58.4745312</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Rowena</firstname><surname>Griffiths</surname><order>1</order></author><author><firstname>Laura</firstname><surname>Herbert</surname><orcid>0000-0001-7580-7413</orcid><order>2</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>3</order></author><author><firstname>Rowena</firstname><surname>Bailey</surname><order>4</order></author><author><firstname>Joe</firstname><surname>Hollinghurst</surname><order>5</order></author><author><firstname>Richard</firstname><surname>Pugh</surname><orcid>0000-0002-2848-4444</orcid><order>6</order></author><author><firstname>Tamas</firstname><surname>Szakmany</surname><orcid>0000-0003-3632-8844</orcid><order>7</order></author><author><firstname>Fatemeh</firstname><surname>Torabi</surname><orcid>0000-0002-5853-4625</orcid><order>8</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>9</order></author></authors><documents><document><filename>60604__24927__00bac8a1f67e4950b9ebd3100af6edf7.pdf</filename><originalFilename>60604.pdf</originalFilename><uploaded>2022-08-15T15:20:42.9669190</uploaded><type>Output</type><contentLength>1774824</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; The Authors. 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spelling 2022-08-15T15:23:05.6055611 v2 60604 2022-07-22 INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale. 381464f639f98bd388c29326ca7f862c Rowena Griffiths Rowena Griffiths true false 0d5765f5486b80e173366af9a61ee200 0000-0001-7580-7413 Laura Herbert Laura Herbert true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 455e2c1e6193448f6269b9e72acaf865 Rowena Bailey Rowena Bailey true false d7c51b69270b644a11b904629fe56ab0 Joe Hollinghurst Joe Hollinghurst true false f569591e1bfb0e405b8091f99fec45d3 0000-0002-5853-4625 Fatemeh Torabi Fatemeh Torabi true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2022-07-22 HDAT IntroductionCritical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research.ObjectiveTo describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care.MethodTo demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales.ResultsWhen applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) hadan emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission.ConclusionThis methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways. Journal Article International Journal of Population Data Science 7 1 Swansea University 2399-4908 intensive care; critical care; electronic health records; linkable research data; ICNARC 18 7 2022 2022-07-18 10.23889/ijpds.v7i1.1724 Data availability:The linkable data sources used in this study are available inthe SAIL Databank at Swansea University, Swansea, UK, butas restrictions apply, they are not publicly available. SAIL hasestablished an application process to be followed by anyonewho would like to access data for approved research purposesat https://www.saildatabank.com/application-process. Whenaccess has been granted, it is gained through a privacyprotecting safe haven and remote access system referred toas the SAIL Gateway. COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University This work was supported by the Con-COV team funded by theMedical Research Council (grant number: MR/V028367/1).This work was supported by Health Data Research UK, whichreceives its funding from HDR UK Ltd (HDR-9006) funded bythe UK Medical Research Council, Engineering and PhysicalSciences Research Council, Economic and Social ResearchCouncil, Department of Health and Social Care (England),Chief Scientist Office of the Scottish Government Health andSocial Care Directorates, Health and Social Care Researchand Development Division (Welsh Government), Public HealthAgency (Northern Ireland), British Heart Foundation (BHF)and the Wellcome Trust. his work was supported by the ADRWales programme of work. The ADR Wales programme ofwork is aligned to the priority themes as identified in the WelshGovernment’s national strategy: Prosperity for All. ADR Walesbrings together data science experts at Swansea UniversityMedical School, staff from the Wales Institute of Social andEconomic Research, Data and Methods (WISERD) at CardiffUniversity and specialist teams within the Welsh Governmentto develop new evidence which supports Prosperity for Allby using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of theEconomic and Social Research Council (part of UK Researchand Innovation) funded ADR UK (grant ES/S007393/1). Thiswork was supported by the Wales COVID-19 Evidence Centre,funded by Health and Care Research Wales. 2022-08-15T15:23:05.6055611 2022-07-22T19:11:58.4745312 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Rowena Griffiths 1 Laura Herbert 0000-0001-7580-7413 2 Ashley Akbari 0000-0003-0814-0801 3 Rowena Bailey 4 Joe Hollinghurst 5 Richard Pugh 0000-0002-2848-4444 6 Tamas Szakmany 0000-0003-3632-8844 7 Fatemeh Torabi 0000-0002-5853-4625 8 Ronan Lyons 0000-0001-5225-000X 9 60604__24927__00bac8a1f67e4950b9ebd3100af6edf7.pdf 60604.pdf 2022-08-15T15:20:42.9669190 Output 1774824 application/pdf Version of Record true © The Authors. This work is licensed under a Creative Commons Attribution 4.0 International License true eng https://creativecommons.org/licenses/by/4.0/
title INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
spellingShingle INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
Rowena Griffiths
Laura Herbert
Ashley Akbari
Rowena Bailey
Joe Hollinghurst
Fatemeh Torabi
Ronan Lyons
title_short INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
title_full INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
title_fullStr INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
title_full_unstemmed INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
title_sort INTEGRATE: A methodology to facilitate critical care research using multiple, linked electronic health records at population scale.
author_id_str_mv 381464f639f98bd388c29326ca7f862c
0d5765f5486b80e173366af9a61ee200
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d7c51b69270b644a11b904629fe56ab0
f569591e1bfb0e405b8091f99fec45d3
83efcf2a9dfcf8b55586999d3d152ac6
author_id_fullname_str_mv 381464f639f98bd388c29326ca7f862c_***_Rowena Griffiths
0d5765f5486b80e173366af9a61ee200_***_Laura Herbert
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
455e2c1e6193448f6269b9e72acaf865_***_Rowena Bailey
d7c51b69270b644a11b904629fe56ab0_***_Joe Hollinghurst
f569591e1bfb0e405b8091f99fec45d3_***_Fatemeh Torabi
83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons
author Rowena Griffiths
Laura Herbert
Ashley Akbari
Rowena Bailey
Joe Hollinghurst
Fatemeh Torabi
Ronan Lyons
author2 Rowena Griffiths
Laura Herbert
Ashley Akbari
Rowena Bailey
Joe Hollinghurst
Richard Pugh
Tamas Szakmany
Fatemeh Torabi
Ronan Lyons
format Journal article
container_title International Journal of Population Data Science
container_volume 7
container_issue 1
publishDate 2022
institution Swansea University
issn 2399-4908
doi_str_mv 10.23889/ijpds.v7i1.1724
publisher Swansea University
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
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description IntroductionCritical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research.ObjectiveTo describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care.MethodTo demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales.ResultsWhen applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) hadan emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission.ConclusionThis methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways.
published_date 2022-07-18T04:18:51Z
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