Thousands of models, few in practice  

Clinical prediction models can support earlier diagnosis, guide treatment decisions, and enable more personalised care. At the same time, many models developed in research never make the step into routine clinical practice. Over the past decades, thousands of models have been published across clinical areas such as oncology, cardiology, and critical care. Yet, only a small fraction have become useful tools in everyday practice. Often, this stems from insufficient attention to defining genuine clinical needs, embedding models in user-friendly innovations, and preparing for evaluation and sustainable adoption. 

Full pathway from idea to impact 

Improving Health Care with Clinical Prediction Models: From Idea to Impact offers a practical, open-access guide to the entire pathway: from defining a meaningful clinical problem and searching for existing models to developing, validating, evaluating, and implementing prediction-model-based innovations in health care. Written by Luc Smits, Sander van Kuijk, and Laure Wynants, the book combines methodological foundations with real-world clinical examples. It is accessible to readers with a basic background in statistical modelling. 

The authors, drawing from years of research, teaching, and mentoring, emphasise not just building robust models but making them useful, usable, and used. Unlike existing resources that focus solely on development and validation, this textbook covers the entire journey from initial idea to impactful implementation, while addressing challenges such as bias, transparency, and real-world evaluation. 

Educational Value and Target Audience 

The textbook is suitable for students, researchers, and clinicians working with prediction models or AI-based decision support. It can be used in graduate-level teaching on clinical epidemiology, predictive modelling, and AI in health care. Its didactic structure, with learning objectives and practical examples, makes it ideal for Master’s and PhD students in health sciences, medicine, epidemiology, and data science, as well as educators and health professionals. The Open Access edition via Maastricht University Press ensures broad accessibility for teaching, research, and professional development worldwide. 

 

In the past year, we had the pleasure of working with Maastricht University Press. After carefully weighing our options, we decided to stay close to home and go with the Open Science vision of Maastricht University Press. I truly valued their personal approach and flexibility. The door was always open.

Laure Wynants via LinkedIn

 

Improving Health Care with Clinical Prediction Models: From Idea to Impact is available under an open-access license from Maastricht University Press.

🔗 Read online, download, or order your print copy here: https://doi.org/10.26481/mup.2603 

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