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A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale
INTRODUCTION: Critical 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 (I...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Swansea University
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464871/ https://www.ncbi.nlm.nih.gov/pubmed/37650027 http://dx.doi.org/10.23889/ijpds.v7i1.1724 |
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author | Griffiths, Rowena Herbert, Laura Akbari, Ashley Bailey, Rowena Hollinghurst, Joe Pugh, Richard Szakmany, Tamas Torabi, Fatemeh Lyons, Ronan A. |
author_facet | Griffiths, Rowena Herbert, Laura Akbari, Ashley Bailey, Rowena Hollinghurst, Joe Pugh, Richard Szakmany, Tamas Torabi, Fatemeh Lyons, Ronan A. |
author_sort | Griffiths, Rowena |
collection | PubMed |
description | INTRODUCTION: Critical 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. OBJECTIVE: To 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. METHOD: To 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. RESULTS: When 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%) had an emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission. CONCLUSION: This 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. |
format | Online Article Text |
id | pubmed-10464871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Swansea University |
record_format | MEDLINE/PubMed |
spelling | pubmed-104648712023-08-30 A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale Griffiths, Rowena Herbert, Laura Akbari, Ashley Bailey, Rowena Hollinghurst, Joe Pugh, Richard Szakmany, Tamas Torabi, Fatemeh Lyons, Ronan A. Int J Popul Data Sci Population Data Science INTRODUCTION: Critical 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. OBJECTIVE: To 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. METHOD: To 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. RESULTS: When 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%) had an emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission. CONCLUSION: This 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. Swansea University 2022-07-18 /pmc/articles/PMC10464871/ /pubmed/37650027 http://dx.doi.org/10.23889/ijpds.v7i1.1724 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Population Data Science Griffiths, Rowena Herbert, Laura Akbari, Ashley Bailey, Rowena Hollinghurst, Joe Pugh, Richard Szakmany, Tamas Torabi, Fatemeh Lyons, Ronan A. A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title | A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title_full | A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title_fullStr | A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title_full_unstemmed | A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title_short | A methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
title_sort | methodology to facilitate critical care research using multiple linked electronic, clinical and administrative health records at population scale |
topic | Population Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10464871/ https://www.ncbi.nlm.nih.gov/pubmed/37650027 http://dx.doi.org/10.23889/ijpds.v7i1.1724 |
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