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Health Education England to use machine learning in monitoring doctor training

18/12/20

Mark Say Managing Editor

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Health Education England (HEE) is aiming to adopt machine learning (ML) as part of its oversight of training for junior doctors in the NHS.

It has carried out discovery work and is now looking to use ML in its predictive analytics to better understand the pipeline of trainees.

It has begun to look for a partner in a two-month alpha project that should inform its approach to solving future problems around the use of ML.

HEE wants to be able to predict and identify the factors that affect the progression of junior doctors through training, such as attrition and extensions to the process. Among those it wants to better understand are reasons for people leaving and what causes gaps in attainment levels between different groups.

It also wants to identify what precedes a trainee having difficulty so teaching hospitals can provide support when early signals become apparent.

Its earlier work, carried out on the Azure ML services platform and focused on training for GP and cardiology services, established that it could process more data and find hidden patterns at greater speed.

Image from iStock, Natalie Mis

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