ORACULUM: A retrospective observational epidemiological study using artificial intelligence and natural language processing in electronic health records to characterize the prostate cancer pathway, management and outcomes in Europe, Middle East and Africa (EMEA region)
Clarke, Noel W
Rey, J. P. M.
del Toro, J. M.
AffiliationOncology Department, Vall d’Hebron Institute of Oncology, Vall d’Hebron University Hospital, Barcelona, Spain;
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AbstractBackground: In Prostate Cancer, there is a need for real-world clinical practice data given the high prevalence and incidence of the disease and the rapid changes in treatment options and diagnosis over recent years. Prostate cancer is a scenario in which ‘Big Data’ is particularly applicable because patients have a long disease course,included in clinical records from thousands of patients and translate these into hundreds of variables. ORACULUM uses EHR population-based data since January 2014, to more accurately describe the epidemiology, diagnosis, management, outcomes, prognostic and predictive factors of response of Prostate Cancer (PCa) patients, across all disease stages. ORACULUM may also provide potential correlations that could have remained hidden so far in the existing literature. Here we describe the methodology for data collection and privacy. generating an immense amount of data. The outcomes would improve our understanding of the potential implication of different diagnostic /treatment approaches in the different profile of patients suffering from this serious disease in clinical practice. The result of this analysis could also inform the scientific community on new hypothesis for future clinical studies. Trial design: ORACULUM is a multi-country, multi-centre, Artificial Intelligence driven, retrospective, observational study analysing deidentified and aggregated information from original EHRs, in four languages (Spanish, English, French and German). ORACULUM uses SAVANA’s EHRead technology, an innovative data-driven system that applies Artificial Intelligence and Natural Language Program techniques. SAVANA software is able to meaningfully interpret physician notes and numerical values
CitationCarles J, Alcaraz A, Clarke NW, Conde A, Heidenreich A, Juarez A, et al. 695TiP ORACULUM: A retrospective observational epidemiological study using artificial intelligence and natural language processing in electronic health records to characterize the prostate cancer pathway, management and outcomes in Europe, Middle East and Africa (EMEA region). Annals of Oncology. 2020;31:S549-S.
JournalAnnals of Oncology
TypeMeetings and Proceedings