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
Author: Nadia Barozzi
Passionate about data-driven insights and the advancement of Real World Evidence research, drug safety and pharmacovigilance.
Can Real-World Data Redefine Clinical Trial Protocol Design?
A System Built Backwards? Clinical trials are the gold standard for evaluating new treatments, but they are often built on idealized assumptions that poorly reflect the complexity of real-world clinical care. Protocols are crafted around rigid eligibility criteria, theoretical endpoints, and often over-optimized designs that filter out the majority of patients seen in actual clinical… Continue reading Can Real-World Data Redefine Clinical Trial Protocol Design?
How Local Healthcare Systems Shape the Availability and Quality of Real World Data
Real-world evidence (RWE) research is deeply influenced by the way healthcare systems are structured. Local regulations, institutions, reimbursement models, and IT infrastructure all shape how real-world data (RWD) are generated, collected, stored, and made accessible. By tracing the patient’s journey through a country’s healthcare system, we can understand where data are generated, who controls them,… Continue reading How Local Healthcare Systems Shape the Availability and Quality of Real World Data
What Is Patient-Level Prediction? Personalizing Risk with Real-World Data
With the growing adoption of personalized medicine and the increasing availability of large-scale healthcare data, the ability to anticipate clinical outcomes at the individual patient level is becoming a fundamental component of modern medical decision-making. Healthcare systems, payers, and researchers are seeking ways to move beyond generalized treatment guidelines and toward tailored, data-driven approaches. … Continue reading What Is Patient-Level Prediction? Personalizing Risk with Real-World Data
From Pharmacovigilance to Multivigilance: How AI and RWD Are Redefining Safety Surveillance in Healthcare
Artificial intelligence (AI) is rapidly transforming the way safety monitoring is conducted in healthcare. Nowhere is this transformation more visible than in pharmacovigilance (PV), where the traditional model rooted in spontaneous reporting systems and manual case processing is being reshaped by automation, advanced analytics, and real-world data (RWD). But this evolution goes beyond drugs. It… Continue reading From Pharmacovigilance to Multivigilance: How AI and RWD Are Redefining Safety Surveillance in Healthcare