Recovering from a Pandemic? Analysis and Implications of Utilising Predictive Analytics for Improving UK Government Healthcare Financing
Abstract
The COVID-19 pandemic has exacerbated existing challenges in the UK healthcare system, including rising healthcare costs, inefficiencies in resource allocation, and the need for additional financing to support pandemic response efforts. This study explores the potential of predictive analytics, specifically machine learning models, to improve healthcare financing in the UK. Using time series data from 1980 to 2021, we employ three machine learning models—Linear Regression, Prophet, and Theta—to forecast healthcare expenditure as a percentage of GDP from 2023 to 2030. The results indicate a positive relationship between health financing and health outcomes, with healthcare expenditure in the UK expected to continue rising. The study highlights the effectiveness of predictive analytics in forecasting future healthcare financing levels and underscores the need for ongoing investment in healthcare infrastructure to ensure improved health outcomes for all citizens. The findings provide valuable insights for policymakers and stakeholders in the healthcare sector, both in the UK and internationally.
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Authors
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