The pharmaceutical industry has seen an explosion in the availability of real-world data in recent years. In the past, pharma companies mainly relied on data from clinical trials. Today, real-world data provides new insights and opportunities to assess a broader population.
This information is increasingly influencing healthcare decision-makers. However, data scientists must have the skills to sort through unstructured health data, analyze it, understand the big picture, and portray the data visually.
Why is real-world health data valuable? According to Ryan Copping, Contributor to the Harvard Business Review:
"Patient data collected in real time during doctor or hospital visits provides an opportunity to better understand diseases, treatment patterns, and clinical outcomes in an uncontrolled, real-world setting. It also allows companies to assess real-world challenges that cannot be observed in a clinical trial, such as drug compliance and the utilization of health care resources."
Real-world data can come from a variety of different sources. Here are a few of the current sources given by the FDA:
- Electronic health records (EHRs)
- Claims and billing activities
- Product and disease registries
- Patient-related activities in out-patient or in-home use settings
- Health-monitoring devices
While these electronic tools generate many opportunities, they also bring business challenges. As Ryan Copping states:
"For the industry, the biggest challenge by far has been talent: upgrading skill sets from those sufficient to analyze relatively small amounts of clinical trial data to those required to gain insights from the vast amount of real-world data, including unstructured data such as physicians’ notes, scans and images, and pathology reports."
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