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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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URI: https://cronfa.swan.ac.uk/Record/cronfa60604
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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.
Item Description: 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.
Keywords: intensive care; critical care; electronic health records; linkable research data; ICNARC
College: Faculty of Medicine, Health and Life Sciences
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’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.
Issue: 1

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