The How and Why of Enterprisewide Clinical Data Integration Strategy

COVID-19 brought into sharp focus the importance of sharing healthcare data among diverse stakeholders, as case counts, hospitalizations and death rates became key points for daily discussions on combating the pandemic.

To track and monitor the pandemic, a worried public flocked to sites such as Johns Hopkin’s Coronavirus Resource Center and the COVID Tracking Project. While these highly visible resources represent examples of more straightforward, simple data sharing, the challenge grows as healthcare organizations endeavor to exchange more detailed, granular clinical data.

Terry Boch

A recent Gartner report, titled “Interoperability and Clinical Data Integration: U.S. Healthcare Payer Progress?,” illustrates the current state of clinical data integration clearly. Forty-eight percent of health plans are ingesting digital charts from provider electronic health records systems, but just 14% of them are receiving data that aligns with the HL7 exchange standard from more than 5% of their in-network providers.

Translation: We’re still in the early stages.

The so-far nascent state of clinical data integration represents a significant opportunity for many payers and providers. By sharing more accurate and timely clinical data, healthcare organizations gain the opportunity to improve risk adjustment and quality measurement, in addition to boosting the overall quality of care.

However, most healthcare organizations are not focusing their clinical data integration efforts on an enterprisewide, scalable foundation that lays the groundwork for future innovation. In the future, that is likely to change. While many are working through the near-term data challenges associated with CMS Patient Access compliance, many realize this doesn’t address broader needs.

Here are several key factors for healthcare organizations to consider as they begin down the clinical data integration path:

How to build a winning strategy
For many organizations, the first consideration in building an enterprise clinical data integration strategy is whether to employ a top-down or bottom-up approach. For many, a hybrid approach works best.

A common, top-down example arises through the execution of value-based contracts among payers and providers. Value-based agreements align incentives for both parties to share data bidirectionally to improve quality and reduce the total cost of care. The challenge lies in scaling this approach so that it fits the “connect-once, use-many” model that results in a repeatable, sustainable process.

In a bottom-up approach, organizations start with specific use cases to drive bidirectional data sharing that also demonstrate the value of data sharing to stakeholders across the value-based organization. For example, the improvement of specific quality measures, such as reducing avoidable hospital readmissions through the exchange of admissions, discharge and transfer data, represents one frequent use case that may lead to significant cost reductions. When deciding where to begin with the bottom-up approach, follow the money to determine where efforts will deliver the most impact. Then, progress to add more lines of business after the areas of highest return have first been addressed.

When considering data exchange standards such as FHIR, among the most important principles to keep in mind is to meet the market where it is today while keeping an eye on the future. In other words, be pragmatic in considering how the market exchanges data today, which may include flat files and other legacy standards. At the same time, it is important to anticipate how to implement new standards as innovation begins to spread around the industry.

Overcoming common roadblocks
Generally, the common roadblocks that may prevent successful enterprise clinical data integration fall into two categories, organizational and technical.

In the organizational realm, clinical data exchange is an enterprisewide function that requires enterprisewide leadership to succeed.

In large organizations, in particular, individual departments have their own budgets and priorities. That arrangement sometimes leads to data sharing being viewed as “someone else’s problem” without any clear champion. However, strong organizational support at the top can help individual teams overcome individual priorities to rally behind a common operational goal.

From a technical standpoint, many of the challenges associated with interoperability stem from the disjointed state of healthcare data itself, which often needs to undergo a process of normalization and enrichment, given the industry’s numerous electronic health records systems and various data standards.

Acquiring data may not represent a heavy lift. But once acquired, transforming that data to the point where it can be used to reliably inform business decisions or drive improved outcomes is significantly more challenging. Healthcare organizations that seek to advance their clinical data integration capabilities must first ensure that their data has been “cleansed” to enable seamless bidirectional sharing with other industry group.

Finding ROI

Demonstrating return on clinical data integration investments starts with a baseline assessment of where an organization is and where it wants to go. In other words, analyze how enhanced data liquidity could drive better outcomes for various business goals, which may range from reducing operational costs and total cost of care to improving quality measures and risk adjustment.

Consider risk adjustment, which is critical for Medicare Advantage populations. Manual chart reviews to identify prior risk-adjustable conditions that were not included on previous insurance claims represent a costly investment for payers.Some health plans are paying millions of dollars in chart chasing costs to capture such conditions. However, digital chart reviews can significantly reduce the cost and improve the speed of chart acquisition while reducing provider abrasion and more accurately assessing member risk. Similarly, digital chart reviews reduce the costs and time associated with manual chart retrieval involved in the prior authorization process.

Other use cases associated with enterprise clinical data integration that may yield tangible ROI involve enhanced detection of fraud, waste and abuse, as well as improved care management.

Although many payers and providers in the industry are still in the early stages of clinical data integration, progress is sure to accelerate as federal interoperability rules take effect later this year. Then, as healthcare organizations optimize their strategies for clinical data integration, they will unlock the full potential of their clinical data to represent a true enterprisewide asset.

Terry Boch is the chief commercial officer for Diameter Health, a clinical data optimization company.