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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)
Carles, J. Alcaraz, A. Clarke, Noel W Conde, A. Heidenreich, A. Juarez, A. Rey, J. P. M. Puente, J. Hernandez-Medrano, I. Salcedo, I.
Carles, J.
Alcaraz, A.
Clarke, Noel W
Conde, A.
Heidenreich, A.
Juarez, A.
Rey, J. P. M.
Puente, J.
Hernandez-Medrano, I.
Salcedo, I.
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Abstract
Background: 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
Description
Date
2020
Publisher
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Keywords
Type
Meetings and Proceedings
Citation
Carles 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.