Getty Images
Health Pros: Pragmatic Over Perfect for Increased Interoperability
Three healthcare professionals recommend a more pragmatic approach to functional interoperability, rather than chasing perfection.
Health IT experts should focus on identifying standards limitations and asking clinicians how to develop practical solutions to gain functional interoperability, according to University of California, San Francisco’s Julia Adler-Milstein, Aaron Neinstein, and Russell Cucina.
To ensure this happens, the trio wrote an op-ed in the Health Affairs blog that recommends a more pragmatic approach rather than attempting to perfect interoperability.
interoperability allows clinicians to view outside patient data within their EHR. However, this data typically exists apart from their local patient data and it does not combine with the local medication lists, problem lists, or laboratory results.
According to the authors, when data is viewable but not combined, clinicians are not as likely to utilize outside data sources because of the effort it takes to combine local and outside data within the EHR.
“While it may seem the remaining work to achieve data integration and realize user-friendly interoperability is minor, the current reality is far from it,” wrote the authors. “The pace of progress is painfully slow because formal policies and informal norms favor perfection over pragmatism in how data from different sources are treated. If we want clinically functional interoperability, clinicians must become more involved to promote pragmatic decisions about when and how to combine data across sources.”
Current data standards don’t have much depth, the authors said, so there is a disconnect between data availability and data integration, the authors said.
“As a result, much electronic health data is exchanged today either as plain text or discrete data unique to the source system,” they explained. “For clinicians, in both cases, this means that you can see and read these data, but you cannot effectively use them as you do data native to your EHR.”
Because of the cost and time it takes to develop standards, it’s unlikely a set of standards will be sufficient enough to ensure perfection for every test result.
But the authors questioned if these differences truly matter from one lab to another.
“This favoring of perfection over pragmatism prevents clinicians from trending results over time across institutions and from importing outside labs into a local record with the appropriate context,” they continued.
The pragmatic approach
The three authors suggested a shift toward pragmatism over perfection to achieve clinically functional interoperability.
The authors said the key to this approach is differentiating when the same test from separate laboratories is clinically different. Test results that are clinically different cannot be treated safely and observed as equivalent. Additionally, health IT experts must note when the distinctions are not clinically meaningful.
However, the trio asked who will be the go-between if there is a shift to a more pragmatic approach.
“We suggest that specialty societies define the guidelines for their commonly used lab tests, describing when different data sources can be integrated and when they should be kept separate, which EHR vendors can then implement,” the authors explained.
“This approach would counterbalance, and perhaps standardize, current involvement of lab directors who, under College of American Pathologists guidelines, approve the approach to reporting outside lab results in their home institution. More broadly, this approach has precedent in federal programs where specialty societies participate in defining quality measures relevant to their specialty,” the three continued.
Risks of a pragmatic approach
While a pragmatic approach could advance functional interoperability, Adler-Milstein, Neinstein, and Cucina said it is not easy to track the risks.
“Integrating more, but not all, types of lab results could create inconsistency in what clinicians see and experience, risking confusion and missed information,” the authors explained. “In addition, perspectives on which differences are clinically meaningful may differ by specialty for the same lab test.”
For instance, specific patient data might matter more to a specialist than a primary care doctor. However, the current framework does not allow the risks, benefits, and costs of customizing integrated data at different levels.
“Instead, we default to the most conservative approach that likely overweighs these risks and undervalues the tremendous potential gains from even modest increases in data integration,” the group added. “Without clinically functional interoperability, a provider may not notice an important trend, such as a gradual decline in kidney or liver function, or must spend significant time manually tracking the data.”
The potential result of this approach is the mix of incomplete data and clinician burden.
Other interoperability benefits from a pragmatic approach
Although Adler-Milstein, Neinstein, and Cucina use lab results as their prime example, the pragmatic approach can lend itself to other areas in interoperability.
“The problem of interoperability of prescription or inpatient medications is similar – for example, in which cases is the same pharmaceutical produced by different manufacturers equivalent? In other clinical data domains, the challenge is even more daunting because terminology standards (like LOINC) do not yet exist or are not widely accepted,” the authors added.
The health professionals cited the United States Core Data for Interoperability (USCDI), a standardized set of health data classes and data elements for health information exchange, that provides a typology of clinical notes. However, implemented EHRs typically have legacy typologies to a site that are often complex, local, and unregulated.
“Fulfilling the promise of interoperability requires charting a new pragmatic approach that recognizes the limitations of standards and increasingly engages clinicians in driving decisions about how to deliver functional solutions,” concluded the authors. “It will not get us to perfect interoperability but we will end up a lot closer to good.”
Dig Deeper on Interoperability in healthcare
-
Investigating electronic phenotyping’s role in clinical analytics
-
Workforce Woes Surpass Financial Pressure As Healthcare’s Top Threat
-
3 Key Pieces to the Interoperability Puzzle: #3 Query-Based Exchange + Directed Exchange
-
Federal Policy Drives Healthcare API Adoption, But EHR Data Barriers Persist