Background

Patients want to understand in simple terms what they can do to reduce their risk of serious illness. By understanding phenotypes better, we can communicate more useful, more accessible, more usable health advice to ordinary people.

Health, diagnoses and risk: the Phenome

Each health condition exhibits a phenotype which could be as simple as high blood pressure. Therefore, in the context of human health, we define a phenotype as all the characteristics (or “traits”) that together constitute one or more health conditions. The study of phenotypes is known as phenomics, and multiple phenotypes constitute the Phenome.

About this course

The first video entitled ‘The Public Demand for Risk Information’ is one of a collection of bite sized video lessons in this course. The entire series of video lessons will provide some of the phenomics methodological underpinnings to study of the informatics of a wide range of diseases (‘phenomics’) and show where this may challenge and advance familiar ideas of diagnosis, prognosis and risk generation.

Other lessons in the series cover a broad range of topics areas including:

• How we can, by studying the phenome, develop consistent ways to define and understand the risk to an individual’s health across such wide ranges of diseases;
• Understanding real world applications of the phenome in aiding clinical decision making;
• The process, challenges and needs of ‘Informatics consults’ and working with all forms of medical text to help inform decision making;
• The use and importance of multiple digital phenotypes and the challenges, barriers and opportunities of representing biomedical knowledge in machine readable form;
• How to use the HDR UK Phenotype library;
• How patients can inform the definition and use of phenotypes; and
• How to generate a phenotype from diverse health data.

Audience

This series is aimed at researchers and healthcare professionals who wish to understand how data enables better understandings of human health.

Written transcripts are available in each learning module.