Listing Thumbnail

    John Snow Labs' Total Patient Journey

     Info
    This service constructs complete patient timelines from structured and unstructured clinical data using the Patient Journey platform from John Snow Labs. It standardizes events, maps them to common data models, and prepares them for analytics on AWS. The service supports use cases in clinical care, research, quality improvement, and payer operations.

    Overview

    John Snow Labs Patient Journey Services help healthcare organizations transform raw clinical information into ordered and analytics ready patient timelines. The service ingests text documents, imaging reports, scanned files, claims, and EHR data, then applies clinical language models to extract diagnoses, medications, symptoms, procedures, laboratory results, social factors, and other key events. These events are normalized, linked across documents, and placed into a complete chronology modeled with OMOP Common Data Model. The result is a clear and comprehensive view of each patient journey that supports cohort analytics, guideline alignment, clinical review, and advanced study design.

    This service is delivered using the John Snow Labs Healthcare NLP platform which is ranked first in accuracy across multiple clinical extraction benchmarks. It integrates naturally with AWS services including Amazon S3 for storage, Amazon EMR or AWS Glue for large scale processing, and Amazon HealthLake or custom data lake architectures for downstream analysis. Customers can also use the timelines as a source of enriched and standardized data for natural language interfaces built on Amazon Bedrock or for advanced patient level querying through John Snow Labs medical language models. The service can be deployed entirely inside the customer AWS account which keeps all protected data inside the secure boundary and supports HIPAA eligible architecture patterns.

    Patient Journey Services can be used to accelerate clinical operations, real world evidence programs, quality initiatives, and payer workflows. From oncology timeline construction to chronic condition review and automated HCC support, the output brings structure to large clinical datasets and makes them easier to search, analyze, and validate.

    Highlights

    • Complete patient timeline creation using clinical language models: Transforms raw EHR notes, imaging reports, scanned documents, and claims into structured patient timelines mapped to standard terminology and OMOP Common Data Model.
    • AWS ready architecture for scalable processing and analytics: Integrates with Amazon S3, Amazon EMR, AWS Glue, Amazon HealthLake, and other AWS data services to support large scale processing of clinical narratives and population level studies.
    • Supports advanced clinical and research use cases: Enables cohort building, guideline comparison, clinical review, real world evidence workflows, and payer operations through accurate multi source event extraction and chronology building.

    Details

    Delivery method

    Deployed on AWS
    New

    Introducing multi-product solutions

    You can now purchase comprehensive solutions tailored to use cases and industries.

    Multi-product solutions

    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

    How can we make this page better?

    We'd like to hear your feedback and ideas on how to improve this page.
    We'd like to hear your feedback and ideas on how to improve this page.

    Legal

    Content disclaimer

    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Support

    Vendor support

    Technical support by Development Team support@johnsnowlabs.comÂ