The HDR UK Phenotype Library is a comprehensive, open access resource providing the research community with information, tools and phenotyping algorithms for UK electronic health records.

1049
Phenotypes
2318
Concepts
201353
Clinical Codes
40
Data Sources
16
Coding Systems
A Reference Catalogue of Human Diseases
Connected. The Phenotype Library is accessible via an API to support interoperability, is integrated with health dataset information in HDR-UK's Innovation Gateway, and hosts content from numerous contributing organisations.

Patient-focused. The Library is enabling important research to improve patient health and well-being. Content spans major disease areas, including heart disease, cancer, COVID-19 and other common and rare human health conditions. Curated collections from contributors such as the HDR UK BREATHE Hub for respiratory health share clinical expertise to tackle critical research questions.

Cutting-edge. Built with a focus on computability, this resource aims to drive the next generation of research methods. Integration with Phenoflow enables executable implementations of the phenotypes in our collection, while the API and R package client facilitate integration of the Library content directly into other analysis workflows.
What is a phenotyping algorithm?
A phenotype is a observable and measurable piece of information that is relevant to health or healthcare. For example, it can be a disease (e.g. type 2 diabetes), a blood pressure measurement, a blood sugar value or a prescription of antibiotics. Phenotyping algorithms are special tools that enable researchers to extract phenotypes from complex, and often messy data that get generated during routine interactions within the healthcare system. They identify and extract data from medical records using clinical codes which are the building block of how information is recorded in healthcare (for example ICD-10). Using these specialized algorithms, researchers and clinicians can maximize the value of patient data contained in medical records and answer important questions that can improve health and healthcare.
How are we driving this work?
The HDR UK Phenotype Library is a platform to host phenotyping algorithms and harness their power for research. Our aim is to provide researchers with the "GitHub of phenotyping": an open platform for creation, storage, dissemination, re-use, evaluation, and citation of curated algorithms and metadata. Our goal is for this to be a place where researchers can share their own work, benefit from what others have shared, and even build new collaborations.
As a funded project of HDR UK , our primary goal is to develop a national platform supporting researchers within the United Kingdom, but we don't want to stop there: we welcome contributions from members of the health research community worldwide.

Search

Start here to explore phenotypes in our library.

Submit a Phenotype

Learn how to contribute your phenotypes to our library.
Key Principles
The aim of the Library is not to standardize or harmonize disease definitions, therefore several phenotypes may be stored for the same condition and the onus is on individual researchers to explore which phenotypes they wish to use
Phenotype definitions will be assigned a unique Digital Object Identifier (DOI) to facilitate identification of the phenotype
Ideally, phenotypes that are deposited in the Library will have undergone some form of peer-review to assess validity and quality either through peer-reviewed publication or some other means of sharing the definition(s)
All material deposited in the Library remain the intellectual property of the research group who created the phenotype(s) the default licensing agreement that information is available under is the Creative Commons Attribution 4.0 (CC A).
The Library stores phenotyping algorithms, metadata and tools only. No data are stored in the Library.
Users should cite the Phenotype Library in all publications, presentations and reports as follows: "HDR UK Phenotype Library phenotypes.healthdatagateway.org"
How to contribute?
To submit an EHR phenotyping algorithm to the Phenotype Library please read our documentation pages.