The Health Services Modelling Associates (HSMA) programme, a pioneering initiative that provides free data science and modelling training and support for health and care professionals, has launched a brand-new website.
The new platform serves as a central hub for HSMA projects, training resources, and case studies, demonstrating the real-world impact of modelling and data science on health and care services while providing valuable support for those looking to develop their own expertise.
The HSMA programme, developed by NIHR PenARC’s Operational Research and Data Science Team (PenCHORD), has played a crucial role in improving mental health and urgent care services, securing multi-million-pound investments, and enhancing service delivery through data science, AI, and Operational Research.
Through the new website, users can easily explore existing projects and freely access code, resources, and information, which they can adapt to the needs of their organisation or service. The website also includes a suite of free online books, authored by programme trainer Sammi Rosser, covering a range of topics including AI, Python coding for beginners and geographic modelling for services.
Dr Daniel Chalk, HSMA Programme Director at NIHR PenARC and the University of Exeter, said:
“Over the last 9 years, the HSMA programme has grown from supporting a small number of local projects to supporting hundreds of national associates to use modelling and data science approaches to transform their services.
“Our new website offers an easy way for people to find out more about the extensive work that our associates have already undertaken, use and adapt open source solutions they’ve generated, and even access self-contained multimedia books to allow people to teach themselves new skills.”
The HSMA programme’s success has led to the creation of new modelling and data science roles within the NHS, contributions to the COVID-19 mass vaccination programme, and career advancements for analysts.
Dr Chalk added:
“We hope the website will provide a central hub for people wanting to engage with our community of applied and open data science and modelling”