Breast cancer learning health system: Patient information from a data and analytics platform characterizes care provided
Abstract Purpose: In a learning health system (LHS), data gathered from clinical practice informs care and scientific investigation. To demonstrate how a novel data and analytics platform can enable an LHS at a regional cancer center by characterizing the care provided to breast cancer patients. Methods: Socioeconomic information, tumor characteristics, treatments and out-comes were extracted […]
Developing a Data and Analytics Platform to Enable a Breast Cancer Learning Health System at a Regional Cancer Center
ABSTRACT PURPOSE: This study documents the creation of automated, longitudinal, and prospective data and analytics platform for breast cancer at a regional cancer center. This platform combines principles of data warehousing with natural language processing (NLP) to provide the integrated, timely, meaningful, high-quality, and actionable data required to establish a learning health system. METHODS: Data […]
AI-Powered Patient Identification to Optimize Care
Introduction: The continued integration of artificial intelligence (AI) into healthcare is anticipated to improve clinician productivity, patient outcomes and the delivery of care. One key role for AI is to identify patterns in large datasets to help to provide clinicians with insight that would be near impossible to detect in normal practice. This study was […]
Building a Breast Cancer Learning Health System
Introduction: Data generated through day-to-day clinical practice hold valuable clinical insights describing the impact of treatments on patient outcomes. This was recognized by the Institute of Medicine through describing the Learning Healthcare System (LHS); a continuous cycle or feedback loop in which scientific evidence informs clinical practice, while data gathered from clinical practice and administrative […]
Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer
Abstract In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC […]
Automating Access to Real World Evidence
Abstract Background: Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHR) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence (AI) may facilitate this process. While NLP offers a faster solution than manual methods of extraction, the validity of extracted […]
Developing a Standardized Framework for Curating Oncology Datasets Generated By Manual Abstraction and Artificial Intelligence
Background The widespread uptake of electronic health records (EHRs) has made the creation of custom, real-world datasets for research more feasible. As a result, multiple research datasets with overlapping populations are often generated, using different methodologies, and frequently siloed within and between research groups, limiting the scope of the data’s use. Currently, there is no […]
Exploring Treatment Patterns and Outcomes of Patients with Advanced Lung Cancer (aLC) Using Artificial Intelligence (AI)-Extracted Data
Background With the recent uptake of novel therapeutic agents, such as immunotherapy (IO) to treat aLC, there is a need for real world data (RWD) to understand the shift in treatment patterns and inform strategies to optimize available therapies. While traditional approaches of manual chart review are labour intensive and error prone, innovative AI techniques […]
Vedolizumab Therapeutic Drug Monitoring and Real-World Outcomes in Inflammatory Bowel Disease
Introduction The present study evaluates the relationships between post-induction vedolizumab trough concentrations (VTC) and real-world outcomes in inflammatory bowel disease (IBD), including biomarkers of inflammation and clinical disease scores. Aims & Methods Participants in the Takeda Canada Patient Support Program who were treated with vedolizumab for Crohn’s disease (CD) and ulcerative colitis (UC) were assessed […]
Validation of Scalable, Automated Data Extraction in an Advanced Lung Cancer Patient Population
Introduction Manual extraction from electronic health records (EHRs) is currently the standard approach for accessing real-world healthcare data but can be time consuming and challenging to maintain over time. Automated data extraction using natural language processing (NLP) is emerging as a viable method of data extraction from structured and unstructured fields of EHRs. While speed […]