Full Description:

Dedalus Connected Care platform is an open platform ecosystem offering the building blocks to leverage machine learning (ML) models from third-party artificial intelligence (AI) partners and carry out predictive analytics. The platform offers out-of-the-box self-service analytics dashboards for data investigation, triggers events based on clinical/operational decision support, providing a notification or alert to the clinician to act in a timely manner.

INTEGRATE: Using industry standards, such as HL7, CDA, FHIR and IHE, enable the flow of complex and fragmented data across disparate applications and organizations making it easier to manage high volumes of complex data with its robust scalable and flexible integration services. Serving as an accelerator for integration, it has the flexibility to connect through many protocols and process proprietary formats.

INGEST: Using FHIR, SNOMED-CT, ICD, LOINC and our out-of-the box bidirectional mapping between data formats such HL7 v2.x, FHIR STU 3, FHIR R4, we can accelerate the ingestion of data from various source systems to provide a full picture of the patient’s clinical and administrative data. The aggregated data for MPI identified patients, is semantically processed, and can be securely shared with other internal and external systems by using standard FHIR APIs.

INDEX: Once normalized and stored into our Clinical Data Repository, “semantic linking” or our out-of-the-box tagging and classification system allows disease staging, assigning each claim, encounter, procedure, medication and condition to a disease category and severity level, through multiple code sets and classification of diseases, including ICD-9 codes, ICD-10 codes, SNOMED CT and others. Globally recognized taxonomy and ontology ensures clinicians and researchers can drill down to details about diseases, achieve objectives more rapidly and accelerate the development of analytics insights based on AI/ML approaches.

INSIGHT: The intelligence fabric, or analytics hub, provides a set of pre-defined functions that allow data scientists and engineers to interact with clinically tagged data from the integrated care record directly from a data science notebook. These are a form of interactive computing, in which users write and execute code, visualize the results, share insights and deploy and execute various AI/ML models.

INFORM: Via a powerful “optical layer” that displays clinical information from resources stored in the Clinical Data Repository (CDR), the analytics workbench provides evidence-based insights about populations and individual health, enabling investigative intelligence on the data in the longitudinal patient record through navigable dashboards and pre-defined or customizable visualizations.

INTERVENE: Our platform’s Public API (based on HL7 FHIR) leverages a connected application ecosystem using a set of defined business rules and automated processes, through a notification or alert, to offer an action, ability to optimize productivity and support health outcomes.