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Annually in the UK, around 60,000 people develop a pulmonary embolism (PE) and 200,000 develop a deep vein thrombosis (DVT), with the number of emergency admissions for suspected cases increasing. Diagnosis remains a challenge due to the non-specific nature of presenting symptoms. There is great interest in finding better tools to identify those with the highest likelihood of a DVT and PE, so that screening services can be focused where needed. Several tools have been suggested but few have been adopted in practice. Methods such as age-adjusted D-dimer tests and 4PEPs and 4D scores aim to predict PE and DVT more accurately. Implementing a more precise system could revolutionise how we diagnose and treat these conditions. This dataset enables an exploration of VTE to better understand disease, identify patients at most risk of the poorest outcomes, and to improve healthcare through the development of new prognostic tools. 
Pioneer Geography: The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix (51% non-white within Birmingham). EHR: UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & an expanded 250 ITU bed capacity during COVID. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Scope: Enabling data-driven research and machine learning models towards improving the diagnosis of Thromboembolic events (PE/DVT). Real-world dataset linked. The dataset includes patient demographics, clinical scores, and medical conditions for PE/DVT patients, alongside outcomes taken from ICD-10 & SNOMED-CT codes. Available Supplementary Data: A synthetic version of thromboembolic events dataset including data pre-processing, synthesising, and post-process steps. Available Supplementary Support: PIONEER can also offer analytics, model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services. This research is supported by the National Institute for Health and Care Research (NIHR) Midlands Patient Safety Research Collaboration (PSRC). This dataset was prepared by and is available through PIONEER, with the support of the NIHR Applied Research Collaboration West Midlands (NIHR ARC WM).
