EAU reveals new data hub to address evidence gaps in urological care

The EAU announced a new data capture and analytics platform for urology and related medical disciplines – the Data Haven. Using cutting-edge Big Data analytics techniques and, where appropriate, explainable artificial intelligence (AI) algorithms, the EAU 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. Collecting Real-World Evidence for personalised care 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 have contributed 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. Yet, the UroEvidenceHub will provide previously inaccessible insights straight from a diverse group of patients. The UroEvidenceHub will take advantage of the latest achievements in data science, broadening the methods currently used for evidence generation. Therefore, the ambitious UroEvidenceHub will expand and complement the current data innovation initiatives coordinated by the EAU - PIONEER and OPTIMA. 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). The EAU UroEvidenceHub equips healthcare professionals with cutting-edge technologies The UroEvidenceHub will offer a unique controlled environment to explore methodological advances around the incorporation of RWE and traditionally published evidence (RCT evidence) into clinical practice guidelines and other decision-making activities and policies. The UroEvidenceHub will bring together experts in urology, RWE generation, artificial intelligence in healthcare, epidemiology, data science and guideline development. This collaborative structure is essential for the UroEvidenceHub to feature population-level data and granular registry-based core outcome data sets likely to significantly impact health outcomes. Living guidelines The UroEvidenceHub will ultimately elevate the current urological guidelines and offer a new way of interaction between clinicians and patients. Among potential benefits are also improved quality of care, strengthening the role of shared treatment decisions and individualised treatment plans that consider physical, emotional and psychological patient needs. All the efforts will lead to treating patients with urological diseases in Europe in a standardised and personalised way, following constantly updated recommendations. This is necessary: prostate cancer is the most common cancer in men, and bladder cancer is the fifth most frequent cancer diagnosed in Europe. Furthermore, 30% of cancers in the EU relate to the urinary system. Data Haven The UroEvidenceHub with its Data Haven is a new interoperable and secure platform that envisions connecting with federated data networks, hub nodes and databases from other relevant data initiatives such as DARWIN EU (Data Analysis and Real World Interrogation Network) and EHDS (European Health Data Space). Also, National Societies/Associations are invited to collaborate. Apart from data providers and data users, stakeholders from academia, data science and IT companies, patient organisations, regulatory bodies and pharma/med-tech companies will be invited to contribute, leading to a tight-knit Ecosystem of Excellence.