Informatics & Technology
VisualStrata® is a HIPAA-compliant, SaaS-based informatics platform designed by bioinformaticists and data scientists, specifically for healthcare
VisualStrata is designed to collate structured and unstructured data from disparate systems into a single source. Using HL7-FHIR protocols, the system is interoperable via API with EMR, EHR, LIS and RIS platforms. Multi-modality data that can be managed and stored includes medical images (PACS, DICOM, non-DICOM) from radiology and pathology; diagnostic biomarkers (XML, VCF, BED, BAM); PDF; and text from clinical notes and conferences.
Built by bioinformaticists and data scientists, VisualStrata bridges data and image silos across and between institutions using semantic ontological frameworks to promote interoperability, sharing, and reuse of data assets.
Specifically designed for the healthcare industry, VisualStrata is HIPAA-compliant with multiple security layers including:
VisualStrata is a SaaS-based service-oriented architecture (SOA) technology for curation of patient health information that is vendor neutral and device agnostic. Interoperability is accomplished through Health Level Seven International (HL7) protocols, HL7-fast healthcare interoperability resources (FHIR), representational state transfer (REST)ful and simple object access protocol (SOAP) services.
Since the platform is SaaS based, users will always be using the latest version, without ever having to deal with maintenance or costly, time-consuming software updates. The platform itself and the data pool are both scalable. Housed at the eco-friendly Switch premier Tier 4 colocation facility in Las Vegas, NV, the high-availability architecture leverages redundancy and virtualization at every level to support minimal to no downtime.
Leverage VisualStrata’s analytics capabilities to document and report quality of care metrics and for transforming data into actionable insights. Search individual patient records (patient level) to visualize longitudinal patient encounters. Search “like” patient populations (population level) to visualize distinct disease characteristics, distinct patient biomarkers and other characteristics such as outcomes.