Transforming Data, Driving Impact

Healthcare Trends and Cromodata Insights

From advances in data technology to real-world applications, here you'll find articles, case studies, and analyses that demonstrate how information drives strategic decision-making.

Real World Data - Introduction

What Is Real-World Data and Why Does IT Matter?
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Every medical visit, prescription, or smart device generates data with the potential to transform healthcare. In this blog, we explain why at Cromodata we believe that understanding this data is key to providing better care for real people.

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Blog Post - AI Trends in Healthcare: Insingths from Standford AI Index 2025

A look at the most relevant applications of artificial intelligence in healthcare.
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‍Stanford’s latest AI Index highlights record growth in healthcare-related AI. In this post, we explore key advances in diagnostics, clinical tools, and medical imaging—and why they matter for the future of healthcare.

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Real World Data. Applications. AI

From Data to Diagnosis: How AI Is Transforming Healthcare.
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Every wearable device, medical consultation, or electronic health record generates data with enormous potential. At Cromodata, we show you how the use of Real World Data, together with Artificial Intelligence, is revolutionizing diagnostics, treatments, and medical research. Because understanding data is the first step toward changing the future of healthcare.

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Real World Data - The Future

Digital Health and Real-World Data: Building the Medicine of Tomorrow
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Digital health is transforming medical care through technologies such as artificial intelligence, telemedicine, and the use of real-world data. One key tool is patient subtyping, which allows treatments to be personalized based on each individual's characteristics, making medicine more precise, efficient, and patient-centered.

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Real World Data - Variability

More data doesn’t always mean better decisions.
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‍A large sample improves precision but doesn’t fix bias or poor study design. Valid causal inference with real-world data requires strong design and representative samples.

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