To address gaps in urological care, the UroEvidenceHub offers a new data capture and analytics platform for urology and related medical disciplines – the Data Haven. By using cutting-edge artificial intelligence algorithms and big data analytics techniques, the UroEvidenceHub data science teams will be able to analyse high-quality and anonymised data. The goal is to break down the complexity of urological conditions, better understand the determinants of patient outcomes, and make urology fit for new challenges in healthcare. The UroEvidenceHub will bring together experts in urology, RWE generation, artificial intelligence in healthcare, epidemiology, data science and guideline development. Read more >
Scientists will apply patient data from diverse Real-World contexts collected from clinical centres as well as directly from patients and make it actionable using cutting edge real world data analytics methods. Where appropriate, using explainable AI algorithms, further research regarding prevention, treatment, rehabilitation, and quality of life of patients with urological diseases can be accelerated. RWE will come from various sources, such as electronic health records (EHR), disease registries, hospital databases and patient surveys. Although classical clinical trials contribute significantly to developing clinical guidelines and improved outcomes in medicine over the past decades, they have their limitations: small cohorts of patients (which leads to excluding specific subgroups and disease variability), a short period of time of data recording, and a reduced scope of analysed determinants. The UroEvidenceHub will provide previously inaccessible insights straight from a diverse group of patients.
The UroEvidenceHub with its specially developed Data Haven, aims to become the largest urology database by collecting large volumes of RWE in a transparent and secure way, following the most rigorous privacy standards, across the spectrum of urological diseases (cancer and benign).
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