Population Health Management: Introduction to Statistics for PHM (PHM-4)

Date: 27th September 2022, 13pm 

Population Health Management: Introduction to Statistics for PHM
PHM-4

27th September 2022, 13pm 

In this online training session, population health management experts David Sgorbati, Santosh Kumar and Joe Lillington of the Health Economics Unit will teach the basics of statistics as commonly implemented in population health management. 

This will be a practical, interactive session for analysts where we will explore how we can use R to obtain and visualise summary statistics to standardise analysis, increase confidence in insights, and mitigate biases in population health management. 

Learning Outcomes

This session is designed to give valuable insights for analysts who want to apply statistics for robust analysis in R across population health management.  

Attendees will leave with: 

  • Knowledge of statistical metrics and how to apply these in R 
  • An understanding of how to apply statistical testing in R 
  • An appreciation of the use of statistics in modelling 

Prerequisites

We recommend attending the courses:

Look out for our other population health management training sessions in the coming weeks. The next session is  PHM-5 – Understanding population segmentation for your local population (4th October 2022, 13pm). 

Agenda

  • What statistical metrics can we use?  
  • What is statistical testing and how can it be implemented in R?  
  • How can statistics be useful in population health modelling?  
David Sgobati

David Sgobati is an experienced computer scientist who has worked for several national, regional, ICS and provider teams in the NHS, contributing to the deployment of machine learning techniques to improve patient care.

In the first 10 years of his career, David worked for several machine learning, artificial intelligence and robotics start-ups, developing software for clients in a wide range of industries, including manufacturing, logistics, and marketing. Since joining the NHS in 2014, his focus has been on using advanced analytics techniques to support problem-solving across organisational boundaries; he is passionate about the use of data as a tool to foster better conversations and to generate actionable insights.

Joe Lillington

Joe Lillington. Joseph has broad experience across data science, physics, and engineering, having previously gained degrees from Edinburgh, Imperial, and Cambridge. He gained his PhD thesis in machine learning and computational modelling at the University of Cambridge, before joining the Health Economics Unit.

Joseph enjoys supporting the NHS by applying the skills that he has gained in his research training. He is passionate about applying his data science knowledge within healthcare systems to improve patient outcomes. He also strongly believes in the value of using machine learning to support population health.

Joseph is always keen to collaborate on projects and learn about the interesting work of others.

Santosh Kumar

Santosh Kumar. Santosh is a dedicated machine learning researcher. He is experienced in applying advanced machine learning techniques and natural language processing to solve real-world data-driven problems.

Passionate about improving healthcare systems through the application of machine learning explainability, privacy-preserving machine learning algorithms, and Artificial Intelligence (AI), Santosh has used these techniques to outstanding effect in a variety of cases. This includes:

  • Extracting information from MRI/CT images for early breast cancer prediction
  • Developing unemployment prediction tools by analysing extensive volumes of public sector data

Santosh is always keen to collaborate and is happiest when he is able to apply and extend his expertise in machine learning to provide the greatest benefits to the population.

Pre-requisites

We recommend attending the courses:

Audience
This course is free and available to all those working in the Midlands Public Health and Social Care sector , e.g. NHS, Public Health, Local Authority, ICBs

Duration
2 hours

Location
Online – delivered via Teams

Date: 27th September 2022, 13pm 

Registration now closed

Please see further Population Health Management sessions from the Health Economics Unit – available to book now!

For more information about this course, please contact:

Training & Development Operational Lead, Rachel Caswell