AI-powered precision population health – optimising health demand and capacity with predictive intelligence analytics in an England case study

The National Health Service is under increasing pressure due to mismatches between workforce capacity, infrastructure and the evolving needs of population health. These issues have led to rising inefficiencies, structural imbalances and service misalignments relative to actual health demand. Addressing these challenges requires an integrated, data-driven planning approach that enables better resource alignment, targeted investment in critical areas and productivity optimisation through a whole-of-system lens. A phased strategy – combining immediate recovery of service capacity with a long-term transformation plan – is essential. By leveraging artificial intelligence (AI)-enabled system intelligence and predictive analytics, this article presents a detailed case study analysis to support sustainable, value-based healthcare tailored to population needs.

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Publication Details

Journal
Innovation and Emerging Technologies
Published
2025-01-01
DOI
https://doi.org/10.1142/s2737599425300089
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-powered precision population health – optimising health demand and capacity with predictive intelligence analytics in an England case study

Mark Gordon, Rosalind Baker, L. Peixoto Sales, David Moore et al.
Innovation and Emerging Technologies
Health, Environment, Cognitive Aging
article

AI-powered precision population health – optimising health demand and capacity with predictive intelligence analytics in an England case study

Mark Gordon, Rosalind Baker, L. Peixoto Sales, David Moore, Andy Poh
article en

Abstract

The National Health Service is under increasing pressure due to mismatches between workforce capacity, infrastructure and the evolving needs of population health. These issues have led to rising inefficiencies, structural imbalances and service misalignments relative to actual health demand. Addressing these challenges requires an integrated, data-driven planning approach that enables better resource alignment, targeted investment in critical areas and productivity optimisation through a whole-of-system lens. A phased strategy – combining immediate recovery of service capacity with a long-term transformation plan – is essential. By leveraging artificial intelligence (AI)-enabled system intelligence and predictive analytics, this article presents a detailed case study analysis to support sustainable, value-based healthcare tailored to population needs.

Innovation and Emerging TechnologiesVol. 12
Griffith University (AU), Public Health England (GB), Global Security Intelligence (United Kingdom) (GB), Artificial Intelligence in Medicine (Canada) (CA), University of Birmingham (GB)
Openalex Percentile: Top 74%
Health, Environment, Cognitive Aging
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