Hertfordshire University’s Operational AI Model Targets Healthcare Efficiency
The University of Hertfordshire has created an operational AI forecasting model designed to improve resource efficiency in healthcare. This ambitious project is the result of a partnership between the university and regional NHS health bodies, aiming to utilise machine learning in operational planning. The objective is to analyse healthcare demand to aid managers with decisions related to staffing, patient care, and resource allocation. This initiative is remarkable as most AI initiatives in healthcare concentrate on individual diagnostics or patient-level interventions, while this tool targets system-wide operational management.
Understanding the Model
This operational AI model is constructed using five years of historical data to build its projections. It incorporates metrics such as admissions, treatments, re-admissions, bed capacity, and infrastructure pressures. Additionally, it considers workforce availability and local demographic factors including age, gender, ethnicity, and deprivation. Professor Iosif Mporas, a renowned expert in Signal Processing and Machine Learning, leads this project, which is slated to continue until 2026.
AI Forecasting in Healthcare Operations
The model’s unique value is its ability to generate forecasts illustrating how healthcare demand is likely to evolve. It models the impact of these changes in the short-, medium-, and long-term, enabling leadership to transition from reactive to proactive management. Charlotte Mullins, the Strategic Programme Manager for NHS Herts and West Essex, believes that the model’s strategic demand modelling can influence patient outcomes, including the growing number of patients living with chronic conditions.
The University of Hertfordshire Integrated Care System partnership funds the project, which commenced last year. Currently, the AI model, designed for healthcare operations, is undergoing testing in hospital settings. The project plan includes extending the model to community services and care homes in line with structural changes in the region. The Hertfordshire and West Essex Integrated Care Board, serving 1.6 million residents, is preparing to merge with two neighbouring boards to form the Central East Integrated Care Board.
Implications and Future Prospects
Ultimately, this initiative showcases how legacy data can drive cost efficiencies and demonstrates that predictive models can inform assessments and resource allocation in complex service environments such as the NHS. It highlights the importance of integrating a variety of data sources, from workforce numbers to population health trends, to establish a unified view for decision-making.
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