As a data-driven endurance athlete, I use several devices to track my performance and progress. Like many others, I occasionally end up in troubleshooting communities (especially those dedicated to Garmin products) trying to understand why a metric looks off or how to recalibrate a sensor. It’s really fascinating to read the discussions. You quickly… Continue reading When Real-World Data Aren’t So “Real” Anymore
Tag: Real World Evidence
Conducting Real-World Evidence (RWE) Studies in Obesity: Opportunities and Challenges
By Patrick Wulf Hanson (Reviewed, adjusted and approved by Dr. Frederik Persson, Head of Clinic, Steno Diabetes Center, Copenhagen, Denmark) 1. Introduction Globally, obesity has emerged as a critical public health challenge, contributing to substantial morbidity and mortality, and it is a leading risk factor for diseases such as type 2 diabetes, cardiometabolic… Continue reading Conducting Real-World Evidence (RWE) Studies in Obesity: Opportunities and Challenges
Internal Data Platforms and Federated Data Models: Understanding the Difference
In the pharmaceutical industry, data has become a strategic asset. Companies are increasingly investing in technologies that enable them to manage, analyze, and derive insights from the enormous amounts of information they generate. As a data strategist, a frequent question I receive is how to build a platform that supports research, monitoring, and evidence generation… Continue reading Internal Data Platforms and Federated Data Models: Understanding the Difference
Data Landscaping for Real-World Evidence: A Strategic Framework and Practical Guide
Introduction Data source landscaping is a foundational step in the design and planning of real-world evidence (RWE) studies. It involves identifying, evaluating, and selecting appropriate data sources that align with the study objectives, target population, and operational requirements. With the increasing availability of electronic health data (EHR), claims records, and disease registries, researchers face both… Continue reading Data Landscaping for Real-World Evidence: A Strategic Framework and Practical Guide
When the Code Isn’t Enough: Building Diagnostic Algorithms and Proxies in RWD Research
In real-world evidence (RWE) research, misclassification is a persistent methodological challenge, particularly when diagnostic information is incomplete, coded inconsistently, ambiguously recorded or entirely absent. When working with data from secondary data sources such as administrative claims or electronic health records (EHRs), not every condition of interest is captured cleanly (or at all) through a well-defined… Continue reading When the Code Isn’t Enough: Building Diagnostic Algorithms and Proxies in RWD Research