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White Paper: From Data to Evidence: How NLP Advances Precision Medicine and Population Health

Never has healthcare been more complex and yet, never has there been more potential to improve the health of patients, populations and communities. Increasing variety in payment models and a rapidly expanding understanding of the genetic and social drivers of disease means there is a broader landscape of treatment and management options than ever before.

To fully realize the potential of precision medicine, healthcare organizations must first collect as much accurate data as possible pertaining to patients, such as information about genetics, physical characteristics and the circumstances in which they live. Then, they must apply technology and techniques to that data to yield the best treatment decisions for those patients.

The concept of population health approaches disease management from a different lens. Rather than making treatment decisions based on individual patient findings, population health is focused on looking at the health outcomes of a population as a whole, and understanding how best to manage disease within that group.

Despite these different perspectives, much of the vital data that drives these initiatives comes from patients’ medical records. Therefore, the tools that translate these complex, largely unstructured data into accurate, well curated datasets have huge potential - whether at the individual patient or population level. One of the most important tools in ensuring healthcare organizations have the right data at their fingertips - ready for analysis - is NLP.

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