How will you design information architecture to unlock the power of data?

As emerging technologies transform health and care, we explore how to create the right data environment for a connected health ecosystem.

The health industry won’t be the same after the COVID-19 pandemic. In the long run, the upside of this disruption is a permanent change in the way health systems, organizations and consumers use digital health technologies. Widespread adoption of tech-enabled care and emerging technologies will transform the very foundations of health and care. A new information architecture is foundational to unlocking the power of digital technologies and creating the connected health ecosystem of tomorrow. Read the full report (pdf) here, or the executive summary below.

What it means to be healthy has become broader, moving beyond the traditional confines of the health industry to embody a more diverse, integrated and seamless system of care and well-being. Powered by digital health technologies, consumers are actively engaging with health systems in vastly different ways. Accustomed to on-demand and self-directed experiences in other areas of their digital lives, consumers expect something more: within the next decade, they believe that health care will be anchored around digitally enabled care, including virtual delivery, remote monitoring and interactive person-centered tools.¹

We live in a highly connected society, and advances in technologies and 5G connectivity are making a suite of new solutions possible around well-being, remote care, smart homes and communities. While complex and high-risk cases and trauma care within a hospital will always play a vital role in health systems, care models across the board are migrating to lower-cost settings. Many of these lie beyond the four walls of the clinic or hospital and are happening closer to the consumer – at home or in the community. 

Health and social care systems create data with ease, and more data than ever before will be collected by, and on behalf of, individuals. Sharing organized and complete data to generate insights for better health outcomes is the driving force behind improving health. For consumers, this means tailored care and lifelong engagement. For providers and payors, it means a longitudinal view of the drivers of health, and current and future demand. For entrepreneurs, it means opportunities to bring disruptive solutions to the market.

What the health ecosystem needs next is a new information architecture: one that not only spans the health and social dimensions of an individual’s life journey but also realizes the immense value of health data in accelerating novel solutions for better and more efficient health and care. Here we describe a new approach to health information architecture that bridges the gap between the information systems of today and the connected health system of tomorrow.

Health systems today are not built to enable data liquidity

Herein lies the challenge. Structural and technological issues, including access, (re)-usability and interoperability of data are barriers to moving toward systems built on data liquidity. Current health information architectures have integration capabilities but limitations around what can be integrated. The sheer quantity of solutions (and thus integration points) makes sharing data within and across systems difficult.

True portability, persistence and completeness of data records are still a long way off, and clinicians’ dissatisfaction with electronic health record (EHR) systems is well-recognized.² Interoperability issues are currently resolved using intermediaries such as Fast Healthcare Interoperability Resources (FHIR) standards that allow different applications and different health systems to communicate. However, if health information systems shared a common language (standards, semantics and structure), the translational interoperability friction and bridging would not be required.

Keeping up with the velocity and variety of health data

It’s clear that we are reaching a pivotal point where health and social data needs to be better connected, combined and shared.

In health care, we don’t yet have the means to connect the volume and variety of data in a way that keeps pace with the velocity at which health and social data are generated. Data linkages aren’t comprehensive or seamless, nor are they accruing for optimal benefit. We must remedy this by designing for the future with the entire system in mind. The potential for societal and economic dividend is a powerful incentive for scaling data exchange across health systems.

The technologies that will connect us to a wellness-oriented, anytime, anywhere health ecosystem are available today. But the challenge is creating something that doesn’t yet exist in health: a ubiquitous information technology infrastructure that is built around data persistence (where an output lasts longer than the system that generated it), extensibility (additional elements or features added to an existing structure) and true interoperability³  (the coordinated access, exchange and collaborative use of information within and across organizational boundaries).

This requires a system-level infrastructure to serve three purposes: safe clinical care, appropriate automation of clinical and back office operations, and the delivery of personalized care and prevention. This will not lead to abandoning existing core services, such as EHRs, imaging and laboratory systems; rather, these will become part of the broader data ecosystem. 

Although the overall goal is ecosystem-wide interoperability, health organizations wanting to unlock interaction data and to modernize their consumer and staff experience face hard decisions around what to pursue, what to repurpose or divest, and where to invest. This means weighing the current state including existing deployments and contractual obligations; the lifecycle stage of legacy systems; and the regulatory and reporting environment. Strategy decisions will hinge on whether to optimize existing assets (by modification or extension), introduce new modular resources that complement the existing core, or invest in creating a new ecosystem from the ground up.
 

Creating the right data environment for tomorrow

As the focus of health systems moves toward supporting wellness — anytime, anywhere — an open platform environment is required to connect and share data, at scale, within and between enterprises and systems. The optimal platform will separate content and technology and be vendor-neutral, distributed and modular — incorporating third-party as well as legacy systems.

This demands a new way of thinking about data. Rather than data being locked away in siloed systems, a decentralized and networked infrastructure could unify disparate information from multiple sources and make sense of it. This means capturing and linking all relevant data regardless of where it is stored.

To progress toward a truly connected health system, a data environment with no connection restrictions other than permissions and security is foundational. This, in turn, necessitates an open platform architecture that allows for the storage and linking of structured and unstructured data and that determines how data flows. Design considerations should provide clear data provenance to deliver trusted algorithms. Built on common standards, this platform forms the base for third-party applications, ensuring safe and interoperable systems.

Adoption and scaling of such an architecture will be a gradual process of localized activity and interest. But over time, when all enterprise and local area activities are added together, the ecosystem coalesces and a connected health ecosystem emerges.

1. A frame of reference

2. An architecture built upon layers

The future health and care information platform we describe separates the architecture into different layers that organize transactions and interactions:

• The data layer confirms that the data is up to the task. It is standardized in terms of format, nomenclature, terminologies and definitions, which allows it to flow into other systems as specified by the data owner. Good rules for data storage will not change much, if at all, allowing for persistence and ultimately, interoperability.
• The application layer requires a fully systemic design of workflow. This means knowing context, or what comes before and after, in the care journey. It is based on triggered events of care or intervention (e.g., clinical workflows or health consumer alerts) rather than constant human monitoring.
• The logic layer incorporates artificial intelligence (AI) that is governed by a set of rules that defines boundaries and exceptions and can form workflows. AI and intelligence are monitored and managed by humans and subject to regular monitoring for audit and clinical safety.

Data is stored separately from the applications that collect, edit and display it. Greater flexibility allows for multiple use cases, multiple vendors and future growth. Such flexibility enables data to flow for better care models and data extensibility (e.g., across a patient’s lifetime.) Clean, standardized, shared data will enable AI and predictive analytics to come out of the data stream. Also necessary is a rules base that governs access and content management. It’s also essential to incorporate internationally recognized standards for terminology, interfaces, storage and coding of records, documents and images (e.g., SNOMED CT and LOINC and other standards developed and adopted over time).

Rapid innovation will take place in the application and logic layers without altering the underlying data structure. As the figure below shows, in the next five years, the new information architecture will shift from siloed vaults of data to a more harmonized arrangement.

3. Mix and match with existing core systems

A more flexible, dynamic infrastructure will be built around existing systems, communicating through standard interfaces like FHIR and web APIs. The APIs of today will inform the technical design of tomorrow but also bridge the gap in data models and current absence of system-level design. In the future, systemically architected systems will make this bridging function unnecessary. Web APIs will persist into the future as ways of creating the frictionless data layer, but they won’t be necessary for creating terminology or future data standards. In the near term, platform-based systems and legacy EHRs will coexist by maintaining basic functionality in legacy systems while building and innovating in a platform-based environment. 

Internationally, there are a number of examples where steps are being taken toward more open and interoperable systems. Estonia, for example, has almost fully digitalized its health system and is currently integrating health and social data for clinical practice support and for research. Several Nordic countries, including Norway and Sweden, are setting in place permission-driven consumer and clinician-accessible health records that follow the patient, irrespective of care location. In the UK, Salford Royal NHS Foundation Trust has deployed an open EHR clinical data repository alongside a core patient record system to meet changing clinical requirements and incorporate patient-recorded outcome measures. And in Germany, the AOK, a major health insurance provider, is developing a digital health network built around data interoperability to make health information available nationwide for its 25 million members.

What these all have in common is a steady progress toward system change built around meeting end-user needs, vendor-neutrality, data persistence, and the demand for flexibility and data fluidity. None of these involve big bang changes; rather, they’re staged building blocks for the future.

What lies ahead?

While the overall goal is ecosystem-wide interoperability, there are several steps that health care organizations and policy makers could take today to meet the demands of tomorrow.

Where we see success in the marketplace is when organizations understand that the way forward is built around data and technologies that grow the business of tomorrow, rather than just a repeat of today’s procurement cycle. These organizations build from an ecosystem mindset, identifying what data is critical and the right strategy to access it. They follow a transformation agenda to create new business models as data becomes the central asset in the organization.

Digital technologies form a data-driven foundation for the future health industry, and conversations about how we can use technology to make a real difference are long overdue. A systemically architected approach for the management of health data is an important step toward a connected health ecosystem, and the technical elements for such a system already exist. To move forward, we will need to reconfigure the information backbone of health care as a new frictionless information architecture, strategically and thoughtfully.

To lay the groundwork for the coming years, here are three things to consider:

1. Framing up the future

The speed of technological change and complexity in the health market require reflecting on purpose, capabilities and priorities.

        To find out what creates value and how to get there, ask:

• What lens is your organization looking through? How is purpose defined, and where do value streams lie: with the consumer, the organization or both?
• How will data shape future business models and reimbursement, and what infrastructure must be in place to unlock interaction data and to modernize the employee and consumer experience?
• What risk is involved, and how deep is the appetite for change – incremental steps or redesign from the ground up?

2. How ready is the organization to change?

Future relevance requires agility and confidence to shift, and to do so at scale. But where best to begin? The speed of change is often slow, hampered by contractual obligations, capital-intensive infrastructures and legacy technologies.

      To identify the problem, ask:

• What are the pain points to be resolved?
  
  For example, a desire to : 
  • Drive better clinical outcomes
  • Respond to growing demand
  • Migrate to new care models and teaming
  • Reverse clinician burnout
  • Secure revenue streams
  • Free investment resources through back-office automation 
  • Step away from lock-in with longstanding entangled systems 
• To what extent does the current tech environment cause or exacerbate the pain points, and how would changing the technology environment resolve the problems?
• What are the opportunities to personalize, simplify and streamline?

3. What is the road map, given the current stage along the technology journey?

Where legacy IT infrastructure exists, the way forward may well lie with maintaining core functionality while investing in adaptable infrastructure such as open architecture and blockchain-enabled solutions that support a connected ecosystem.

To develop the road map, ask:

• What is the plan? 
  • To optimize existing assets (either by modification or extension); to introduce resources that complement the existing core; or to create a new ecosystem from the ground up
•  What is the process?
  • A phased transition to new solutions; a greenfield approach of creating new capabilities on a new platform; or a big bang approach that converts all capabilities to a modernized solution in single or multiple events
• What else must be done?
  • Design for trust, governance and align organizational culture - where boards, clinical and organizational leadership are comfortable with creating friction and deviating from the status quo, and have the skills to do so
  • Bring other stakeholders, including the board and policy makers, along on the journey
  • Build the right in-house team with right capabilities to execute