NHS England Data Science PhD Internships

Predicting the Impact of Health Inequalities

Keywords: MachineLearning, UnsupervisedClassification, TabularData

Need: The pandemic has shone a brighter light on health inequalities. The NHS needs to take steps to develop population health management approaches that address inequalities in access, experience and outcomes. Addressing health inequalities is at the core of recovery plans, with a particular focus on deprivation and ethnicity. This project, hosted by the East Suffolk and North Essex Foundation Trust, seeks to deliver insights on where inequalities exist across the local health economy so that these may be addressed.

Current Knowledge/Examples & Possible Techniques/Approaches: National and local analysis has highlighted trends between deprivation, ethnicity and health inequalities, including prevalence of obesity, smoking, and preventable diseases, as well as COVID-19 mortality. Analysis has also found links between deprivation and access to services, including waiting times and cancellation rates. A predictive analytics project is underway to identify people with undiagnosed diabetes. However, analysis has thus far been restricted to high-level correlations and insights on the key drivers is needed to inform mitigating action.

Related Previous Internship Projects: n/a

Enables Future Work: Analysis will inform the Trust’s recovery plans and work with partners by identifying any inequalities that should be addressed as a priority. Impactability modelling, including through unsupervised learning, will enable further work to identify people who will benefit most from a range of interventions.

Outcome/Learning Objectives: Deliver a suite of analyses on the prevalence and magnitude of health inequalities and demonstration of impactability modelling, with a particular focus on diabetes.

Datasets: East Suffolk and North Essex Foundation Trust patient administration systems linked to other datasets from primary care (incl. community Integrated Diabetes Service) and open datasets such as indices of deprivation. Approx. 1.7 million patients on the system.

Desired skill set: When applying please highlight any experience around informatics, statistical analysis, deep learning, coding experience, or any other data science experience you feel relevant.

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