In this complimentary webinar, discover utilizing AI for precise extraction of patient data from structured and unstructured electronic medical records (EMRs). Featured speakers will delve into case studies focusing on accurate identification of patients experiencing chronic obstructive pulmonary disease (COPD) exacerbations and the strategic prioritization of individuals for participation in a heart device clinical trial.
The intersection of artificial intelligence (AI) and electronic medical record (EMR) data has ushered in unprecedented accuracy and speed in patient selection for clinical trials, real-world evidence studies, and clinical treatments. This webinar explores novel approaches employed by life sciences companies, leveraging AI to pinpoint patients with greater precision, prioritize research subjects based on therapy-specific criteria, and collaborate with sites for expedited access to EMR data.
Traditionally, identifying suitable patients for trials or research involves searching EMRs for structured codes or conducting keyword searches. Unfortunately, this method yields imprecise results and demands time-consuming processes, including manual chart reviews and validation. Challenges arise when seeking patients without specific codes or encountering inconsistent documentation (e.g., ‘triple negative breast cancer’ appearing as TNBC, triple negative BC, breast tumor – TN, etc.).
Moreover, life science firms often face a prolonged process, often exceeding a year, to acquire access to electronic medical record (EMR) data for the creation of innovative patient-matching algorithms in their research endeavors. Leveraging AI to extract comprehensive, real-time EMR data—encompassing both structured and unstructured elements like clinician notes, omics, labs, and pathology reports—enables swift and accurate identification of all clinically suitable patients for a given clinical trial or research study.
Join this webinar to explore how AI is utilized to identify patients with chronic obstructive pulmonary disease (COPD) exacerbations in clinical settings. Presenters will also detail their approaches to identifying and prioritizing patients for a heart device clinical trial.
Register now to gain a deeper understanding of the advantages of AI-driven patient matching and the analysis of real-time electronic medical record (EMR) data.
