NLP-Enriched EHR Data Solutions

Veradigm Network EHR Data Solutions

Healthcare data solutions that tap into the power of the Veradigm Network

Real-world data (RWD) sourced from disparate electronic health records (EHRs), clinical data registries, and other siloed sources can often be fragmented and difficult to work with. In today’s fast-paced healthcare environment, your teams need efficient, data-driven healthcare solutions that don’t waste precious time and resources on inconsistent and unwieldy medical data.

Veradigm Network EHR Data

Veradigm Network EHR Data is purpose-built for research and provides streamlined access to over over 154 million patient records* by combining multiple EHR data sources within the Veradigm Network.

5 Year Time Period: Q3 2019 – Q2 2024

Unlock the Power of NLP-Enriched EHR Data

Did you know that 80% of critical patient information is trapped in unstructured data, such as clinical notes, making it hard to access valuable insights¹? Unlike niche data aggregators, Veradigm has direct access to raw structured and unstructured data through multiple EHR systems.

Veradigm’s proprietary natural language processing (NLP) models are used to extract meaningful elements from unstructured and semi-structured data, providing deeper insights about the patient cohort of interest. NLP-enriched EHR data can empower researchers to better understand therapeutic decisions, disease progression, and patient outcomes across diverse populations.

Veradigm’s NLP-Enriched EHR Data Sets Can Help You

Veradigm’s EHR data solutions are meticulously crafted to support research and advance health outcomes. Thanks to a sophisticated, NLP-enriched electronic health records dataset that integrates data from various EHR sources within the expansive Veradigm Network, you can:

• Spend less time managing fragmented data, and more time on the analysis that drives results
• Achieve faster results with EHR data that is purpose-built for research, curated, and harmonized directly from the point-of-care
• Draw meaningful research insights from the geographic, demographic, and social diversity found within Veradigm Network EHR data

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Key Aspects of Veradigm Network EHR Data

Veradigm’s EHR data solutions are designed to empower life sciences research in studying outcome, safety, as well as measuring comparative effectiveness and patient care.

• NLP-Enriched EHR data: Veradigm’s proprietary NLP models extract critical insights from unstructured data, revealing patient insights often missed by traditional methods.
• Nationally Representative Data: Covering multiple regions, payer types, and demographics.
• Longitudinality and Near Real-time Access: With the ability to track patients over time, Veradigm data supports retrospective and prospective studies, refreshed nightly, weekly, or monthly.
• Patient Tokenization and Flexible Integration: Ensures robust patient journey mapping by linking data across providers, as well as third-party data sources to enable fit-for-purpose solutions.
• Regulatory-Grade and Research-Ready: Veradigm’s data is standardized, de-identified, and statistically certified to meet the highest research and regulatory standards.
• Data Originator Advantage: Veradigm’s patient engagement platform and direct relationships with healthcare providers enable the ability to conduct prospective and retrospective data collection, perform data clarification, and position us as experts in the curation and interpretation of our own data.​

Through the power of the Veradigm Network, you can license cohorts of data across a variety of therapeutic areas, define a patient cohort based on diagnosis, treatment and demographics, or license the entire Veradigm Network EHR dataset.

Click the button below to request patient counts and learn more about how Veradigm Network EHR Data can help you achieve your goals.

Request Patient Counts

References:

1. Eastwood B. How to Navigate Structured and Unstructured Data as a Healthcare Organization. HealthTech, May 8, 2023. https://healthtechmagazine.net/article/2023/05/structured-vs-unstructured-data-in-healthcare-perfcon
   *Q2 2019-Q1 2024