A New Reality Calls for Radical Interoperability

Last Published: Dec 23, 2021 |
Richard Cramer
Richard Cramer

Chief Strategist, Healthcare and Life Sciences

Co-authored with Rob Karel, VP, Strategic Marketing Initiatives.

The concept of data interoperability is nothing new. For decades, organizations have been working toward improving interoperability. Firms of all shapes and sizes have focused internally on “integration,” ensuring their siloed internal systems, databases, applications, clouds, and mainframes could pass data back and forth by leveraging a wide variety of data, application, and process integration approaches.

Organizations have also focused on “interoperability,” which we’re defining as the ability to share data across trading, supply chain, distribution, and other ecosystem partners. They’ve leveraged EFT, B2B, EDI, MFT, and a Scrabble-worthy list of other acronyms to enable this. There have also been widely adopted industry standards that have ensured effective data interoperability and trust, such as the Global Data Synchronization Network (GDSN) data pools used extensively by manufacturers and retailers when sharing product and supply chain. Other industry standards have also been created to try and improve the consistency, format, and usage of shared data across organizations, including FHIR (and previously HL7) for healthcare, SWIFT and FDX for financial data, ACORD for insurers, and many others.

One thing is certain. None of these interoperability initiatives has kept up with the complexity of today’s digitally transformed world. Digital business is not a startup phenomenon; it’s required for any organization that wants to remain in business. The exponential growth in the world’s data, along with a revolutionary shift in how data must be used, is impacting everyone’s ability to effectively reduce risk, deliver on customer expectations, reduce costs, improve productivity—and ultimately drive the outcomes expected of your organization.

Current Healthcare Interoperability Failures Are a “Canary in the Coal Mine” for all Industries

data interoperability is essential for healthcare

These interoperability gaps have been especially apparent as our global healthcare system struggles to manage the impacts of the COVID-19 pandemic. Healthcare providers, government response teams (national, regional, and local), and clinical researchers from pharmaceutical firms searching for effective testing, treatments, and cures all need to share and receive data from one another continuously.

Unfortunately, the lack of effective and timely data sharing has led to major challenges with anticipating patient volumes at hospitals, meeting healthcare worker staffing requirements, ensuring healthcare supplies like masks and ventilators are getting to the right locations when needed, and identifying and mitigating risk for our most vulnerable patient populations. Yes, many of these shortages and breakdowns were due to the speed at which the virus spread, but once governments and health systems became aware of the dangers, the lack of data insights became apparent.

In the US healthcare market in particular, this paucity of data interoperability manifests in the lack of a comprehensive lifetime health record for an individual. Patients see a wide variety of providers during different phases of their life as they move from childhood to adulthood to old age. In addition, many individuals and families move every few years, forcing a change in healthcare provider. They also see different providers during the same time period for primary care and specialty care, and perhaps even urgent care or ambulatory clinics operated by their employer or pharmacy. Unfortunately, the data associated with these encounters is locked within the individual provider’s electronic health record and is not shareable across providers or provider networks.

During normal times this lack of interoperability has been frustrating and inefficient, adversely impacting costs and quality. However, with the current pandemic—where predictive modeling is being used to look into every facet of disease spread, severity of illness, utilization of resources, mortality, and countless other dimensions—the absence of a comprehensive record for patients has come into acute focus.

The healthcare system of the future must be radically more interoperable than the healthcare system of the present. New approaches must be found that make sharing data easier, quicker, and more secure; they must also ensure that shared data is reliable and trustworthy for all intended recipients. This data interoperability is necessary to enable the digital transformation of our healthcare system that is both long overdue and desperately needed, as evidenced by the current COVID-19 crisis.

The current health crisis has reached beyond healthcare to touch every industry globally, resulting in a financial crisis with impacts that could last for years. This is why now is the appropriate time for every organization in every industry to focus on “radical interoperability.”

Radical Interoperability Is Required to Further Accelerate Data-Driven Digital Transformation

Radical interoperability enables contextual, trusted, transparent, and authenticated data sharing within and across organizational, industry, and multi-industry collaboration networks. To enable the scale and complexity inherent in this undertaking, radical interoperability requires:

  • Full transparency, discovery, and access—without mandating common tools, infrastructure, or architecture
  • The ability to share data with end-to-end transparency and lineage across organizations
  • Less reliance on complex, exhaustive standards and more reliance on AI/ML, leveraging the tagged metadata context, to onboard new sources and targets efficiently, with trust, and at scale
  • Eliminating the use of manual processes and manual intervention to manage issues around data volume, latency, and complexity in order to facilitate data sharing
  • Intrinsic data quality that ensures data can be trusted and fit for use across its lifecycle
  • Authenticated endpoints and lineage for everything that has happened, from “true” source to “all potential” targets
  • The scale and automation that can be realized only through ongoing innovations in AI and ML

It will remain very important for organizations to continue to enable integration within their own complex hybrid, multi-cloud systems environments. And organizations must also continue to invest in the interoperability that streamlines data sharing with their direct business partners. But radical interoperability now requires CIOs and CDOs to look beyond their immediate “neighborhoods.”

We can begin by redefining what is meant by a data lifecycle. Typically, organizations have focused on managing and governing data from the point their company captures (or otherwise procures) it to the point of use (either in an analytic or business process), and perhaps ending with the data’s retirement. But it’s 2020—data couldn’t care less about your organizational boundaries. It’s very possible that the data you receive from a “source,” say, a partner, has already lived a lifetime of degradation, black box transformation, human error, or malicious intent before it ever arrives at your doorstep. And what about the data you share with your downstream partners? How confident are you that they are managing and governing it effectively, ensuring it remains fit for use for its intended purposes?

So radical interoperability must begin with metadata transparency and lineage: sharing metadata—that critical context—with your partners alongside the data. Just as your Tableau dashboard may show where data came from, which boosts trust in the derived insights, we must enable the same level of transparency for all data sharing.

Radical interoperability must also consider the next logical evolution of data cataloging and governance, which will provide the ability to discover, track, and govern the appropriate usage of critical data along this new extended data lifecycle. This means enabling data discovery, quality, and governance in collaboration with stakeholders outside your organizational boundaries. Your data governance council membership just became a lot more diverse.

Radical interoperability does not throw away existing best practices and investments—it builds upon them. All the data management competencies that your organization has (hopefully) invested many years in building are the foundation that will enable this critical next generation of interoperability.

Next Steps

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First Published: May 17, 2020