Discover the challenges and solutions in converting unstructured data into structured data from Electronic Medical Records (EMRs). Learn how Natural Language Processing (NLP), standardized terminologies, and data integration tools can help overcome these obstacles, ensuring accurate and efficient data extraction for improved healthcare outcomes.
Tag: Data
Chart Review and EMR Extractions in RWE Research
Two primary methods used to gather data for Real World Evidence (RWE) research are chart reviews and Electronic Medical Record (EMR) extractions. Chart Review involves manually extracting data from patient medical records, including both paper-based charts and digital documents. This method provides a rich source of detailed clinical information. EMR Extractions involve the… Continue reading Chart Review and EMR Extractions in RWE Research
Common Data Models in Clinical Research
In clinical research, data models are essential for organizing, storing, and analyzing complex healthcare data. Effective data modeling ensures accurate data integration, facilitates efficient data analysis, and enhances data sharing across different systems and studies. Let’s explore some of the most commonly used data models in clinical research and their applications. 1. CDISC… Continue reading Common Data Models in Clinical Research
Unlocking Athletic Potential: Harnessing Wearable Data for Enhancing Performance
Over the years, endurance athletes have undergone extensive transformations. In the last decade we have witnessed a fast growing exercising population, which uses wearables and other devices to gather an incredible volumes of data for monitoring their training and performance. This includes recording speed, distance, heart rate, accelerations, power, blood glucose, sweat rates, among other… Continue reading Unlocking Athletic Potential: Harnessing Wearable Data for Enhancing Performance
Enhancing Registry Data Quality: Key Measures and Strategies
Registries play a central role in real-world evidence (RWE) studies by providing comprehensive, real-world data (RWD) on patient populations, treatments, and outcomes outside of controlled clinical trial settings. This data is invaluable for assessing disease progression, the effectiveness, safety, and utilization of medical interventions in everyday clinical practice, guiding healthcare decisions, and informing regulatory decisions.… Continue reading Enhancing Registry Data Quality: Key Measures and Strategies