The Population Health Impacts of Changes to the National Health Service Health Check Programme: A System Dynamics Modelling Approach in a Local Authority in England
Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/2/101 |
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| Summary: | Health checks aim to improve the health of the population by identifying individuals with risk factors earlier and intervening to prevent disease. The role of commissioners is to ensure health checks provide as much benefit as possible for taxpayer funds invested into them. As such, evidence of the potential impacts of different commissioning choices is beneficial in this decision-making process. System dynamics modelling can be used to provide this evidence by modelling the health check programme using a pre-existing cohort model of a given population. This modelling considers local data, literature findings, and stakeholder views, from which nine different scenarios of a local health check programme have been tested. These scenarios found that extending the duration of health checks to 20 years and improving treatment uptake for those with high blood pressure or high cholesterol reduced rates of cardiovascular disease, improved healthy life expectancy and reduced years lived in ill health. In contrast, improving attendance in the most deprived quintile of the population made very little change to the health of the population overall, although a larger effect was observed in the most deprived areas. These findings helped guide local commissioning decisions by showing the long-term impact of different health check scenarios. |
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| ISSN: | 2079-8954 |