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Using AI to understand how preventative interventions can improve the
health of children in the UK and reduce winter pressures on the NHS
Rethinking Poverty, Insecurity and the Cost of Living Crisis in the North
West and Beyond
Martin Chapman
Using AI to understand how preventative interventions can
improve the health of children in the UK and reduce winter
pressures on the NHS
A research project funded by Health Data Research UK and the
National Institute for Health and Care Research looking at winter
pressures faced by the NHS.
Designed to generate rapid insight (January – March 2023), which can
be used for future winters.
An interdisciplinary team with expertise in health informatics;
paediatrics and general practice; mental health; inequalities and racism
and health; and policy.
Living in cold, damp, and mouldy homes
leads to poor health, such as chest
conditions in children and mental health
problems in adolescents.
The rising cost of energy, coupled with
wages not increasing in line with inflation,
is likely to further widen social inequalities
in child health.
With families unlikely to be able to afford
to heat their homes, health problems for
children and young people (CYP) may
worsen.
1
Implement
2
1
Model
Evaluate
What is our ‘digital mimic’?
What is our ‘digital mimic’?
Engagement
1
Coding
2 Data
3
Low SEC Middle SEC High SEC
White British Ethnic Minority
Asthma
Depression
1
Coding
2
Data
e.g. Low SEC
+ Asthma
1
Coding
2
Data
Interviews
3.1
Engagement
3
Focus groups
3.2
Questionnaires
3.3
Scope
Determine
behaviour
Evaluate
3.2
Questionnaires
Household
payments
1
Advice
2
3
Vaccine
eligibility
83,776 individuals analysed
30+ engagement activities
37 subgroups of interest
33,000 simulations run
1. Our model is designed to be an objective entity, and as such its
outputs may not necessarily align with our own personal
thoughts or preferences on the best way forward.
2. Any mention of ‘behaviours’ refers to behaviours in the context
of winter pressures (e.g. use of heating) as opposed to behaviours
in a mental health context.
Note
SEC +
Asthma
Unique ID of
observed group
Primary care Note scale
+5% of income Eligibility +2 years
SEC +
Asthma
+5% of income Eligibility +2 years
Ethnicity +
Asthma
Overall health utilisation can
potentially be reduced by issuing
government advice.
Disparities between different SEC
groups can potentially be reduced
by issuing government advice.
Requires further validation before
implementation into policy.
1
2
SEC +
Asthma
Very early insight!
The long-term picture is
more complex.
github.com/digitalmimic/model github.com/digitalmimic/winter-analysis
Dr. Martin Chapman (PI)
Abigail G-Medhin (Data Scientist)
Kian Daneshi (Research Software Engineer)
Professor Mark Ashworth (GP)
Professor Laia Becares (Racism and Health)
Dr. Harriet Boulding (Policy)
Professor Vasa Curcin (Health Informatics)
Professor Seeromanie Harding
(Inequalities)
Professor Craig Morgan (Mental Health)
Dr. Divya Parmar (Health Systems)
Professor Lucilla Poston (Maternal and
Child Health)
Dr. Ingrid Wolfe (Paediatrician)
Dr. Mariam Molokhia (GP)
What’s next?
• More data (e.g. additional health utilisation data)
• More PPIE (e.g. additional SEC insight)
• More validation (e.g. against existing intervention implementations)
• Interested in discussions around how our model and/or method can
be applied to related domains and related datasets.
@martin_chap_man
Using AI to understand how preventative interventions can improve the
health of children in the UK and reduce winter pressures on the NHS
Rethinking Poverty, Insecurity and the Cost of Living Crisis in the North
West and Beyond
Martin Chapman
Image sources various, including Shutterstock

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Using AI to understand how preventative interventions can improve the health of children in the UK and reduce winter pressures on the NHS.

  • 1. Using AI to understand how preventative interventions can improve the health of children in the UK and reduce winter pressures on the NHS Rethinking Poverty, Insecurity and the Cost of Living Crisis in the North West and Beyond Martin Chapman
  • 2. Using AI to understand how preventative interventions can improve the health of children in the UK and reduce winter pressures on the NHS A research project funded by Health Data Research UK and the National Institute for Health and Care Research looking at winter pressures faced by the NHS. Designed to generate rapid insight (January – March 2023), which can be used for future winters. An interdisciplinary team with expertise in health informatics; paediatrics and general practice; mental health; inequalities and racism and health; and policy.
  • 3. Living in cold, damp, and mouldy homes leads to poor health, such as chest conditions in children and mental health problems in adolescents. The rising cost of energy, coupled with wages not increasing in line with inflation, is likely to further widen social inequalities in child health. With families unlikely to be able to afford to heat their homes, health problems for children and young people (CYP) may worsen.
  • 6. What is our ‘digital mimic’?
  • 7. What is our ‘digital mimic’?
  • 9. Low SEC Middle SEC High SEC White British Ethnic Minority Asthma Depression 1 Coding 2 Data
  • 10. e.g. Low SEC + Asthma 1 Coding 2 Data
  • 14. 83,776 individuals analysed 30+ engagement activities 37 subgroups of interest 33,000 simulations run
  • 15. 1. Our model is designed to be an objective entity, and as such its outputs may not necessarily align with our own personal thoughts or preferences on the best way forward. 2. Any mention of ‘behaviours’ refers to behaviours in the context of winter pressures (e.g. use of heating) as opposed to behaviours in a mental health context. Note
  • 16. SEC + Asthma Unique ID of observed group Primary care Note scale
  • 17. +5% of income Eligibility +2 years SEC + Asthma
  • 18. +5% of income Eligibility +2 years Ethnicity + Asthma
  • 19. Overall health utilisation can potentially be reduced by issuing government advice. Disparities between different SEC groups can potentially be reduced by issuing government advice. Requires further validation before implementation into policy. 1 2 SEC + Asthma
  • 20. Very early insight! The long-term picture is more complex.
  • 22. Dr. Martin Chapman (PI) Abigail G-Medhin (Data Scientist) Kian Daneshi (Research Software Engineer) Professor Mark Ashworth (GP) Professor Laia Becares (Racism and Health) Dr. Harriet Boulding (Policy) Professor Vasa Curcin (Health Informatics) Professor Seeromanie Harding (Inequalities) Professor Craig Morgan (Mental Health) Dr. Divya Parmar (Health Systems) Professor Lucilla Poston (Maternal and Child Health) Dr. Ingrid Wolfe (Paediatrician) Dr. Mariam Molokhia (GP)
  • 23. What’s next? • More data (e.g. additional health utilisation data) • More PPIE (e.g. additional SEC insight) • More validation (e.g. against existing intervention implementations) • Interested in discussions around how our model and/or method can be applied to related domains and related datasets. @martin_chap_man
  • 24. Using AI to understand how preventative interventions can improve the health of children in the UK and reduce winter pressures on the NHS Rethinking Poverty, Insecurity and the Cost of Living Crisis in the North West and Beyond Martin Chapman Image sources various, including Shutterstock