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Creating a next-generation phenotype library: the health data research UK Phenotype Library.
Thayer, Daniel S; Mumtaz, Shahzad; Elmessary, Muhammad A; Scanlon, Ieuan; Zinnurov, Artur; Coldea, Alex-Ioan; Scanlon, Jack; Chapman, Martin; Curcin, Vasa; John, Ann; DelPozo-Banos, Marcos; Davies, Hannah; Karwath, Andreas; Gkoutos, Georgios V; Fitzpatrick, Natalie K; Quint, Jennifer K; Varma, Susheel; Milner, Chris; Oliveira, Carla; Parkinson, Helen; Denaxas, Spiros; Hemingway, Harry; Jefferson, Emily.
Afiliação
  • Thayer DS; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Mumtaz S; Health Informatics Centre, School of Medicine, University of Dundee, Dundee, DD1 9SY, United Kingdom.
  • Elmessary MA; School of Natural and Computing Sciences, University of Aberdeen, Aberdeen, AB24 3UE, United Kingdom.
  • Scanlon I; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Zinnurov A; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Coldea AI; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Scanlon J; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Chapman M; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Curcin V; Department of Population Health Sciences, King's College London, London, SE1 1UL, United Kingdom.
  • John A; Department of Population Health Sciences, King's College London, London, SE1 1UL, United Kingdom.
  • DelPozo-Banos M; Adolescent Mental Health Data Platform and DATAMIND, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Davies H; Adolescent Mental Health Data Platform and DATAMIND, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Karwath A; SAIL Databank, Medical School, Swansea University, Swansea, SA2 8PP, United Kingdom.
  • Gkoutos GV; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom.
  • Fitzpatrick NK; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom.
  • Quint JK; Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom.
  • Varma S; School of Public Health and National Heart and Lung Institute, Imperial College London, London, W12 0BZ, United Kingdom.
  • Milner C; Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.
  • Oliveira C; Health Data Research United Kingdom, London, NW1 2BE, United Kingdom.
  • Parkinson H; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Welcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.
  • Denaxas S; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Welcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom.
  • Hemingway H; Institute of Health Informatics, University College London, London, NW1 2DA, United Kingdom.
  • Jefferson E; University College London Hospitals National Institute of Health Research Biomedical Research Centre, London, NW1 2BU, United Kingdom.
JAMIA Open ; 7(2): ooae049, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38895652
ABSTRACT

Objective:

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. Materials and

Methods:

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.

Results:

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.

Discussion:

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.

Conclusions:

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JAMIA Open Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JAMIA Open Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido