EMR Optimization and Modernization
Fast Healthcare Interoperability Resources
Prime Dimensions’ event-driven architecture supports applications based on Fast Healthcare Interoperability Resources (FHIR), an emerging Health Level Seven (HL7) standard describing data for-mats and elements (known as “resources”) and an Application Programming Interface (API) for exchanging health data. FHIR uses a modern Web-based suite of API technologies, including HTTP-based RESTful and SOAP protocols for user interface integration, and supports both JSON and XML for data representation. With FHIR, it is possible to develop applications that can access and pro-cess HL7 data in real time via RESTful and SOAP APIs. FHIR facili-tates interoperability across health care systems; provides critical, actionable information to clinicians and patients; and brings con-text to each patient encounter in real time for improved clinical decision support. FHIR also allows third-party application develop-ers to provide medical applications which can be easily integrated into existing systems. FHIR provides an alternative to document-centric approaches by directly exposing discrete data elements as services. For example, basic elements of health care like patients, admissions, diagnostic reports, and medications can be retrieved and manipulated via their own resource URLs.
API management is the process of publishing and monitoring application programming interfaces (APIs) in a secure, scalable environment. APIs not only facilitate integration of new features into existing applications but also provide standard specifications for accessing and sharing data via remote Web service calls via SOAP and RESTful APIs. API management includes the creation of end user support resources that define and document the API, as well as setting attributes and parameters for publishers and subscribers. APIs are essential for establishing a virtualized data environment and event-driven architecture (EDA). With proper API management, publishers make APIs available to subscribers, and those transactions are managed at the application level. Applying cross-boundary, cross-domain data governance, standardization, mapping and harmonization across disparate systems, including EMRs, claims data, financial data, and operational data promotes higher perfor-mance, flexibility and scalability in the architecture.
Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without re-quiring technical details about the data, such as location, structure, format, and storage technology. Data virtualization provides an abstraction layer that data consumers can use to access data in a consistent manner. A data consumer can be any application re-trieving or manipulating data, such as a reporting or data entry application. This abstraction layer hides all the technical aspects of data storage. Data virtualization is typically implemented on an enterprise service bus (ESB) as the abstraction layer, through which Web services (i.e., SOAP or RESTful APIs) are invoked by applications that allow access to data. The ESB can also publish APIs and allow access to data in a cloud repository. Data virtualiza-tion is also used in conjunction with in-memory databases, in which APIs facilitate processing analytics at the source and pre-senting the results rather than the underlying data. This provides significant performance and scalability advantages.
Event-driven Architecture is a design pattern that builds on the fundamental aspects of Service-Oriented Architecture (SOA), in which event notifications are transmitted between decoupled soft-ware components and services to facilitate immediate information dissemination and reactive business process execution. In an EDA, information can be propagated in nearly real time throughout a highly distributed environment, enabling the organization to pro-actively respond to business “events.” (Examples include submis-sion of new patient admission form, payment of a claim, approval for a procedure, and physician orders.) Since EDA uses asynchro-nous messaging to communicate among two or more application processes, it is much more efficient than SOA. Within an EDA, busi-ness processes are modeled into discrete state transitions (compared to sequential process workflows), with event-based triggers and decoupled interactions. EDA relies on data sources sharing a common gateway or ESB.