Population Health Management: Understanding Impactibility for Your Local Population (PHM-9)

Date: 1st November 2022, 13pm 

Population Health Management: Understanding Impactibility for Your Local Population
PHM-9

1st November 2022, 13pm 

In this virtual session, population health management experts Andi Orlowski, David Sgorbati and Sophie Hodges of the Health Economics Unit will lead attendees through a two-hour interactive session. 

This session is designed to give valuable insights for employees across the ICS, whether you’re analytical or not. There will be practical, interactive and useful examples of systems working together, and plenty of opportunity for discussion and questions. 

Learning Outcomes

Attendees will leave with: 

  • An understanding of what impactibility is 
  • The ability to interpret impactibility analysis 
  • The ability to evaluate impactibility analysis 

Prerequisites

It is recommended that attendees have a basic understanding of population health management, population segmentation and risk stratification to attend this session.

You may wish to attend

Look out for our other population health management training sessions in the coming weeks. It is recommended that analysts also attend the next session  PHM-10 – Doing causal inference for impactibility assessments for your local population causal inference for impactibility assessments for your local population (8th November 2022, 35pm). 

Agenda

  • What is impactibility? 
  • How impactibility is used to predict those who will be most responsive to care 
  • Overview of impactibility models 
  • How are these techniques used in practice? 
  • Potential pitfalls – avoiding exacerbating inequalities 
  • Group exercise and discussion 
Andi Orlowski

Andi Orlowski. Andi is a health economist with particular interest in population health analytics, especially addressing health inequalities and the concept of impactibility modelling. He is researching this for his PhD at Imperial College London. He is also a senior advisor for NHS England on population health management in the Operations and Information Directorate and works with STPs and ICSs across the country.

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.

Sophie Hodges

Sophie Hodges. Sophie has a background in population health management and is passionate about providing better evidence to improve decisionmaking in healthcare. She has a first-class degree in economics with econometrics (BSc) from the University of Kent and will soon complete a masters in health data analytics (MSc) from UCL. Sophie also has experience in building communities of practice supporting analytical upskilling and developing system intelligence functions.

Reading Materials

Pre-requisites

It is recommended that attendees have a basic understanding of population health management, population segmentation and risk stratification to attend this session.

You may wish to attend

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: 1st November 2022, 13pm 

Registration: Please use the online link below

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