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Fernando, Sandra, Sowinski-Mydlarz, Viktor, Shrestha, Subeksha, Maharjan, Sunila, Stewart, Duncan, Bhakta, Dee, McLean, Gary R. and Illingworth, Sarah (2025) Vitamin D analysis for sustainable healthcare in Inner London Borough. Computational Intelligence, 41 (2) (e70050). pp. 1-13. ISSN 1467-8640
Vitamin D is vital for bone health, immune system support, and muscle function. Deficiency in Vitamin D is widespread, with up to 65% of individuals in certain populations, including Black students at London Metropolitan University, UK, being affected. This study focuses on the need for a deeper understanding of Vitamin D prescription patterns, specifically within an inner London borough, using advanced data analytics. Previous analysis, such as ones conducted by OpenPrescribing.net, has investigated NHS prescription data but lacked a focused examination on Vitamin D. Our study introduces a novel computational approach, integrating NHS datasets from 2013 to 2023. We developed a web‐hosted dashboard using Python, Flask, Cesium, PowerBI, and libraries such as Pandas, Scikit‐learn to provide real‐time data visualization and predictive analytics. Our methodology involved API‐driven ingestion of large‐scale data, focusing on Vitamin D prescriptions in a borough, and mapping this against patient numbers. We used feature manipulation and model training to gain insights into prescription counts, dosages, medication types, and formulations. This interactive platform supports dynamic reporting through PowerBI and Cesium. Our findings reveal significant variations in prescription patterns among GP surgeries influenced by socioeconomic factors. This interdisciplinary project, in future collaboration with local GP federations, United Kingdom, enhances computational health data analysis and aims to inform better prescription practices and healthcare policies, ultimately improving policy practice and public health outcomes.
Available under License Creative Commons Attribution 4.0.
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