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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.
Afiliação
  • Griffiths R; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
  • Herbert L; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
  • Akbari A; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
  • Bailey R; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
  • Hollinghurst J; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
  • Pugh R; Department of Anaesthetics, Glan Clwyd Hospital, Betsi Cadwaladr University Health Board, Rhyl, UK.
  • Szakmany T; Department of Anaesthesia, Intensive Care and Pain Medicine, Division of Population Medicine, Cardiff University, Cardiff, UK.
  • Torabi F; Critical Care Directorate, Royal Gwent Hospital, Aneurin Bevan University Health Board, Newport, UK.
  • Lyons RA; Population Data Science, Health Data Research UK, Swansea University Medical School, Swansea University, Wales, UK.
Int J Popul Data Sci ; 7(1): 1724, 2022.
Article em En | MEDLINE | ID: mdl-37650027
ABSTRACT

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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cuidados Críticos / Unidades de Terapia Intensiva Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Cuidados Críticos / Unidades de Terapia Intensiva Idioma: En Ano de publicação: 2022 Tipo de documento: Article