Desiderata for the development of next-generation electronic health record phenotype libraries

Author:

Chapman Martin1ORCID,Mumtaz Shahzad2ORCID,Rasmussen Luke V3ORCID,Karwath Andreas4ORCID,Gkoutos Georgios V4ORCID,Gao Chuang2ORCID,Thayer Dan5ORCID,Pacheco Jennifer A3ORCID,Parkinson Helen6ORCID,Richesson Rachel L7ORCID,Jefferson Emily2ORCID,Denaxas Spiros8ORCID,Curcin Vasa1ORCID

Affiliation:

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

2. Health Informatics Centre (HIC), University of Dundee, Dundee, DD1 9SY, UK

3. Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA

4. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK

5. SAIL Databank, Swansea University, Swansea, SA2 8PP, UK

6. European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD, UK

7. Department of Learning Health Sciences, University of Michigan Medical School, MI 48109, USA

8. Institute of Health Informatics, University College London, London, NW1 2DA, UK

Abstract

Abstract Background High-quality phenotype definitions are desirable to enable the extraction of patient cohorts from large electronic health record repositories and are characterized by properties such as portability, reproducibility, and validity. Phenotype libraries, where definitions are stored, have the potential to contribute significantly to the quality of the definitions they host. In this work, we present a set of desiderata for the design of a next-generation phenotype library that is able to ensure the quality of hosted definitions by combining the functionality currently offered by disparate tooling. Methods A group of researchers examined work to date on phenotype models, implementation, and validation, as well as contemporary phenotype libraries developed as a part of their own phenomics communities. Existing phenotype frameworks were also examined. This work was translated and refined by all the authors into a set of best practices. Results We present 14 library desiderata that promote high-quality phenotype definitions, in the areas of modelling, logging, validation, and sharing and warehousing. Conclusions There are a number of choices to be made when constructing phenotype libraries. Our considerations distil the best practices in the field and include pointers towards their further development to support portable, reproducible, and clinically valid phenotype design. The provision of high-quality phenotype definitions enables electronic health record data to be more effectively used in medical domains.

Funder

Engineering and Physical Sciences Research Council

Economic and Social Research Council

Wellcome Trust

Horizon 2020 Framework Programme

National Institute for Health Research

National Institute of General Medical Sciences

National Human Genome Research Institute

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Health Informatics

Reference44 articles.

1. A framework to support the sharing and re-use of computable phenotype definitions across health care delivery and clinical research applications;Richesson;EGEMS (Wash DC),2016

2. Best practices for creating the standardized content of an entry in the OHDSI Phenotype Library;Weaver,2019

3. Introduction to the VA Phenomics Library (VAPheLib);Cho

4. Design and concept of the SMITH Phenotyping Pipeline;Meineke;Stud Health Technol Inform,2019

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