Background

Verto's Digital Twin Orchestration platform enables a revolutionary new approach to healthcare data normalization to drive next-gen automations and robotic process automation. Our technology is composed of three main pillars, which together allow us to create a more robust and useful dataset.

Data Standardization

By aligning our entire platform to the FHIR data standard, we enable quick and easy integration with almost any data source. For FHIR or HL7-compliant EMRs, integration is as simple as plugging into the FHIR API and using our standard resource definitions and mappings to ingest data straight into our database. For non-compliant EMRs, we have automated tools to profile the data and recommend mappings to the Verto FHIR specification. Together, this means we can quickly and seamlessly ingest data from multiple data sources, and amalgamate it to form a single view of a patient.

NLP Data Augmentation

Although data is transformed to the FHIR standard upon ingestion, this still leaves room for unstructured or semi-structured data. Through our NLP clinical entity extraction algorithms, we apply further structure to your data and codify it to enable more robust and reliable downstream automation tasks!

Data Consumption / Sharing

The Verto Digital Twin platform comes complete with a ready-to-consume population health panel that displays metrics from across your population. Users can apply filters to this view to narrow it down to a cohort of interest and see key metrics about that cohort. Alongside the population health panel, our platform contains a custom API for patient cohort querying, allowing your team to ingest data to downstream applications. This API is described in detail in this documentation.