Exchanging data from disparate systems with different protocols has become highly challenging in today’s healthcare information systems. Since the data reception is from various systems like Health Information Exchange (HIE), Patient Protocols, Scheduling Software, Laboratory Information Systems, Provider Information and many other sources with different data structures, Data Management tasks like aggregation, normalization, storage, processing etc have become more complex to process. This further leads to the major complications in healthcare data interoperability.
FHIR (Fast Healthcare Interoperability Resources) has emerged addressing this problem very intensely as a standard with a structure. It offers a seamless exchange of healthcare information electronically amongst Patients, Payers, Providers and various other healthcare beneficiaries. FHIR solution is widely implemented because of its unique architecture and based on secured web services enabling to access the resources built on HL7 standards. FHIR resource is a set of information in JSON/XML format containing Metadata, and data elements in a predefined HL7 data structure which can be processed by any healthcare information systems which is FHIR compliant. Specific resource data can also be bundled with all resource types (eg: appointments, diagnostics) and can be accessed through a URI.
As HHS and CMS are beginning to mandate FHIR implementations for healthcare data exchange, multiple vendors are stepping forward to comply with FHIR data exchange standard. FHIR provides base resource types allowing for further customization using Profiles for Resources, Extensions for custom attributes, Value sets. FHIR supports RESTful architectures and exchange of information using modern web standards like XML, JSON, Protobuf, and HTTP etc.
Healthcare data is shared securely through open APIs at lightning speed amongst various beneficiaries involved in Healthcare chain along with data flow between mobile applications and servers. Security of the API is ensured by widely used authentication protocols like OAuth which enables control over access to resources. With all the above mentioned advantages and outstanding features, Developers can build standardized applications that allow access to the data regardless of the source systems (like EHR’s) and its underlying data model and infrastructure.
The uniqueness of FHIR lies in HL7 interoperability mechanism. It provides a standard structure for various resources – medical conditions, claims or insurance in exposing the data in HL7 format. It also authorizes the client to display the FHIR server to any external client by providing them access. Exafluence’s FHIR server with API customization exclusively presents the data in HL7 format saved to MongoDB database ensuring a secure, hassle-free and agile mechanism.
FHIR implementation is an unceasing sustainable solution in solving the complications that are extreme in interoperability. Exafluence partnered with MongoDB intensely addresses this issue in HL7 standards with utmost flexibility regardless of the resource systems enabling without any need for multiple data conversions and resulting in the best performance analysis. FHIR adaption is pretty simple, concise, flexible and very economical supporting seamless exchange of healthcare information establishing harmonious collaboration amongst the Providers and Payers.
FHIR specification is very flexible and free of cost with no restrictions on licensing. FHIR offers multiple implementations libraries, and several open-source FHIR servers are available that can easily be set up to get started and can plugin to the existing systems. The FHIR data model is flexible to add custom attributes, besides the ones defined in the structure definition using extensions resource type and publish as a profile to the FHIR server. This makes it easier to exchange custom data along with pre-defined FHIR standard data elements of a particular resource type.
Exafluence FHIR solution offers a generic FHIR server and API along with data migration tools with Spark for batch processing and Kafka for stream processing. These migration tools would let clients export their data from their existing source systems (eg: SQL, Oracle, MySQL) to MongoDB seamlessly. Spark is configured to update the data periodically in batches and Kafka is subscribed to the existing application endpoints to stream and update the data in MongoDB. The source system data mapped with Metadata is automatically converted to FHIR profiles and structure definitions and imported in JSON format to respective resource type MongoDB collections. The secured APIs use the OAuth 2.0 protocol for authentication and authorization of the resources and underlying data. The data in MongoDB is encrypted in-flight and at rest and uses role-based access control to govern the access to database, collections, documents and fields. It also supports LDAP (Lightweight Directory Access Protocol) integration.
Exafluence partnered with MongoDB uses MongoDB Atlas database that supports multiple cloud providers (AWS, Azure, and GCP) to store data in replica sets for high availability that allows sharing large data sets for distribution across multiple machines supporting high throughput operations. Besides, MongoDB also supports multi-document ACID transactions and SQL based BI connectivity. MongoDB Realm allows the use of an embedded database with Synchronizing for mobile applications.
DIAGRAMMATIC REPRESENTATION OF FHIR PROCESSING ARCHITECTURE FOR HEALTHCARE APPLICATIONS
RevAssurant, a secured web portal allows providers to access patient data which includes patient history, care measurements, diagnostics, laboratory reports and Insurance claims. The portal enables providers to track and view patient activity, submit ICD 10 codes to close gaps in the patient medical record. This process helps in improving the performance of health plans and their provider networks with accurate MRA scores. RevAssurant also includes various actionable reporting capabilities such as progress reports with risk scores of providers and members.
DIAGRAMMATIC REPRESENTATION OF REVASSURANT DATA FLOW
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