Creating a next-generation phenotype library: the health data research UK Phenotype Library.

algorithms application programming interface electronic health records medical informatics phenotyping public health informatics

Journal

JAMIA open
ISSN: 2574-2531
Titre abrégé: JAMIA Open
Pays: United States
ID NLM: 101730643

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 19 06 2023
revised: 12 02 2024
accepted: 20 05 2024
medline: 19 6 2024
pubmed: 19 6 2024
entrez: 19 6 2024
Statut: epublish

Résumé

To enable reproducible research at scale by creating a platform that enables health data users to find, access, curate, and re-use electronic health record phenotyping algorithms. We undertook a structured approach to identifying requirements for a phenotype algorithm platform by engaging with key stakeholders. User experience analysis was used to inform the design, which we implemented as a web application featuring a novel metadata standard for defining phenotyping algorithms, access via Application Programming Interface (API), support for computable data flows, and version control. The application has creation and editing functionality, enabling researchers to submit phenotypes directly. We created and launched the Phenotype Library in October 2021. The platform currently hosts 1049 phenotype definitions defined against 40 health data sources and >200K terms across 16 medical ontologies. We present several case studies demonstrating its utility for supporting and enabling research: the library hosts curated phenotype collections for the BREATHE respiratory health research hub and the Adolescent Mental Health Data Platform, and it is supporting the development of an informatics tool to generate clinical evidence for clinical guideline development groups. This platform makes an impact by being open to all health data users and accepting all appropriate content, as well as implementing key features that have not been widely available, including managing structured metadata, access via an API, and support for computable phenotypes. We have created the first openly available, programmatically accessible resource enabling the global health research community to store and manage phenotyping algorithms. Removing barriers to describing, sharing, and computing phenotypes will help unleash the potential benefit of health data for patients and the public.

Identifiants

pubmed: 38895652
doi: 10.1093/jamiaopen/ooae049
pii: ooae049
pmc: PMC11182945
doi:

Types de publication

Journal Article

Langues

eng

Pagination

ooae049

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Déclaration de conflit d'intérêts

The authors have no competing interests to declare.

Auteurs

Daniel S Thayer (DS)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Shahzad Mumtaz (S)

Health Informatics Centre, School of Medicine, University of Dundee, Dundee, DD1 9SY, United Kingdom.
School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, AB24 3UE, United Kingdom.

Muhammad A Elmessary (MA)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Ieuan Scanlon (I)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Artur Zinnurov (A)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Alex-Ioan Coldea (AI)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Jack Scanlon (J)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Martin Chapman (M)

Department of Population Health Sciences, King's College London, London, SE1 1UL, United Kingdom.

Vasa Curcin (V)

Department of Population Health Sciences, King's College London, London, SE1 1UL, United Kingdom.

Ann John (A)

Adolescent Mental Health Data Platform and DATAMIND, Swansea University, Swansea, SA2 8PP, United Kingdom.

Marcos DelPozo-Banos (M)

Adolescent Mental Health Data Platform and DATAMIND, Swansea University, Swansea, SA2 8PP, United Kingdom.

Hannah Davies (H)

SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.

Andreas Karwath (A)

Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom.

Georgios V Gkoutos (GV)

Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom.

Natalie K Fitzpatrick (NK)

Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom.

Jennifer K Quint (JK)

School of Public Health and National Heart and Lung Institute, Imperial College London, London, W12 0BZ, United Kingdom.

Susheel Varma (S)

Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.

Chris Milner (C)

Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.

Carla Oliveira (C)

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Welcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.

Helen Parkinson (H)

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Welcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.

Spiros Denaxas (S)

Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom.
University College London Hospitals National Institute of Health Research Biomedical Research Centre, London, NW1 2BU, United Kingdom.
British Heart Foundation Data Science Center, Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.

Harry Hemingway (H)

Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom.
University College London Hospitals National Institute of Health Research Biomedical Research Centre, London, NW1 2BU, United Kingdom.

Emily Jefferson (E)

Health Informatics Centre, School of Medicine, University of Dundee, Dundee, DD1 9SY, United Kingdom.
Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.

Classifications MeSH