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Virtually all healthcare providers are already using electronic health record (EHR) technology, but EHRs alone can’t deliver the promise of digital transformation due to the fragmentation and inconsistency of data collected from so many different sources.
By taking an approach based on a new reference architecture for a digital health platform (DHP), even the most complex and heterogeneous of health IT ecosystems can overcome these challenges and achieve improved patient outcomes as well as reduced healthcare costs.
Patient health outcomes suffer when medical decisions are made without complete and relevant information. This occurs due to the fragmentation of health records across multiple sources. A DHP addresses data fragmentation and associated business challenges by emphasizing modularity, interoperability and a common framework for different components interacting within a cohesive ecosystem.
The DHP concept is predicated on the idea that health IT ecosystems comprising multiple EMRs and other health-related data stores can no longer rely on a single “source of record” for managing the complete lifecycle of health data. No one system can be solely responsible for managing data processing. The DHP reference architecture (DHP-RA) is based on the concept of a “separation of concerns” (SoC) – a design principle for separating solutions into distinct layers that individually satisfy a core business requirement or “concern.”
The DHP-RA creates three distinct layers: systems of engagement, systems of insight and systems of record. The proliferation of multiple systems of engagement and multiple systems of record highlights the problem, as shown in the figure below.
Essentially, systems of record include EMR platforms, non-clinical business systems, data warehouses, patient generated data stores, medical devices, applications, and others. In nearly all cases, this data is not aligned to a canonical form and has variable conformance to industry standards.
When applying the SoC principle, the systems of engagement are decoupled from the systems of record. This enhances modularity so that individual components can be changed or replaced, and provides the ability to build a best-of-breed environment with minimal vendor lock-in and greater portability of applications and components.
This is where the system of insight comes into play. The system of insight acts as an intermediary between the systems of engagement and the systems of record, hiding the complexities of the underlying data architecture.
A well-designed DHP will include the components needed to address all aspects of data acquisition, data processing, data segmentation and tagging and information extrapolation. This includes analytics and pattern matching, natural language processing, identity management, access control and authentication, data access auditing and logging and data exception handling.
Additionally, a well-designed DHP will encapsulate this rich functionality behind APIs aligned to industry standards to ensure predictability and portability. The DHP must also be configurable to support organizational policies for recognizing the source of truth and master data management. In an ideal implementation, a DHP will also be context-aware to tailor the data provided to systems of engagement based on knowledge of the end user, their access rights, their preferences, their workflow and the specific needs of the current task.
Read the white paper to learn more about the components of a DHP reference architecture and how DXC U.S. Public Sector and a community of partners and collaborators are developing a digital health platform reference implementation.
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