Population Health Management – Practical Application

Bruno Petrungaro

Population Health Management – Practical Application

This course will deliver bespoke teaching on the practical application of population health management (PHM) tools and the underlying analytical principles of PHM. During the course, participants will use a real-world dataset with prepared practice problems with full detailed explanations of the process using R software.

This course will provide analysts with clear examples of how to perform PHM analytics in practical terms and will make sure that participants know how to translate the skills to the datasets they have access to in their everyday roles. Additionally, this course will ensure that participants understand the underlying principles of PHM so that they can accurately and efficiently apply the skills in an independent manner following completion of the course.

Heather Humphreys

The Health Economics Unit will deliver this course which aims to provide analysts with the necessary knowledge and skills to support population health management approaches within their Integrated Care System and will cover:

  • Segmentation
  • Risk stratification
  • Impactability using causal inference

Your trainers are: Bruno Petrungaro and Heather Humphreys

Audience and pre-requisites
Audience: Analysts in Integrated Care Systems in the Midlands 
Should have a good knowledge of R and regression and probability theory. For example, it would be useful to know how to do the following:

  • Upload libraries.
  • Call functions from base R and libraries.
  • Upload data to R and understand data types of each columns.
  • Manipulate data frames. For example, transform columns , create new columns from existing ones, reshape data frames.
  • Understand through R or Excel use the notion of ‘if’ and ‘if else’.
  • Understand the notion of for loops.

The ‘Introduction to R’ training currently covers some of these elements.

Number of places per ICS
2 spaces available per ICS

Duration and start date
4 days over consecutive weeks
Dates to be confirmed.


For more information about this course, please contact the course lead:

Bruno Petrungaro