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Advancing Interoperability to Support Informed Healthcare

Achieving seamless interoperability depends on the healthcare industry’s ability to overcome obstacles such as lack of data standardization and integrity.

The continued adoption of health information technology — namely EHR systems — has laid a foundation for more robust care coordination. However, the reality is many providers still lack the tools to reconcile external health data with what is documented in their local records. As a result, potentially valuable data go underutilized. Advancing interoperability hinges on standardizing and integrating data from disparate sources to create a unified longitudinal patient record; a comprehensive view of the patient supports effective clinical decision-making. It’s imperative we enable clinicians with information in an integrated experience that doesn’t introduce additional burden nor take away their precious time with patients.

“Clinicians are looking for a clinical longitudinal view of the patient,” says Margo Jackson, lead product manager at Oracle Cerner. “Given the amount of noise that comes with exchanging large volumes of data, we want to present what is new and most important for the clinician to see. The greatest need currently is to have the right record delivered to the clinicians, but there are gaps in information in the way of achieving full semantic interoperability.”

This is where interoperability solutions have the opportunity to transform care coordination and delivery. People, process and technology are essential components of advancing healthcare interoperability. Ensuring that actionable data is available at the point of care requires that different health IT systems can communicate securely and efficiently and integrate external data into the system of record to improve care delivery and patient outcomes.

“When external data lives alongside all other data in one place, interoperability can support intuitive workflows that save clinicians time and energy and enable more meaningful interactions with patients,” maintains Ali Thole, senior product manager at Oracle Cerner.

Achieving seamless interoperability depends on the healthcare industry’s ability to overcome obstacles such as lack of data standardization and integrity. According to Jackson and Thole, eliminating these barriers will bring the industry one step closer to making complete data available at the point of care.

The value of data standardization

Following a decade of rapid EHR adoption spurred on by federal incentives, the vast majority of healthcare organizations have in place a foundation for the exchange of health information. That said, data standardization remains a key missing piece to the interoperability puzzle.

“We’ve come a long way from the printing and faxing of records. We then shifted into the Meaningful Use era, where regulation drove home the importance of disparate systems needing to speak in the same language. Even still, data standardization across proprietary systems remains problematic,” Thole explains. “When we talk about the longitudinal record, it starts with standardizing that data. And a key component to achieving that goal is getting organizations to opt into and leverage national data exchange frameworks to help enable the greater exchange of the data across the board because at its core, interoperability must cross care settings.”

According to Jackson, using a common language to connect these systems is a critical step toward semantic interoperability, where exchanged data is understood by each system without intervention. “For us to be able to understand these records and understand the equivalence of it semantically, we need to speak the same language,” she stresses.

Data standardization efforts must also extend to other care settings where privacy rules and regulations require great levels of compliance, such as mental and behavioral healthcare. Connecting the entire healthcare system becomes that much more complex.

“The industry as a whole doesn’t handle exchanging more sensitive clinical data very well right now, in terms of understanding the context of information being exchanged. What is sensitive and what’s not? It’s a tough topic,” Jackson states.

“We’ve pushed forward from a regulatory perspective with minimum requirements, but we need to go beyond that,” she continues. “We’re working to manage the confidential nature of certain health data to ensure that people feel comfortable about sharing their data. As we progress with standards and move forward with increasing information sharing, we still need to put those controls in place.”

More advanced and widely adopted standards will ensure data flows across the healthcare system. The challenge then turns to improving the accuracy, completeness and consistency of exchanged data.

Building trust: the workflows around shared data

The practice of medicine has a high standard when it comes to clinical evidence. Incomplete or inaccurate data in the patient record could easily lead to confusion and frustration for clinicians. New interoperability solutions provide the means to unify patient data without overwhelming clinical staff in the process.

“We’ve spent a lot of time over these past years exchanging data in a document form in order to have some way of sharing information, but we need to move the needle. Clinicians need information at their fingertips and within the context of their EHR systems, presented in usable form that supports efficient workflows. On the technology side, that means we must filter out the noise as more data comes into play,” Jackson notes.

According to Thole, deduplication is a big part of the solution to the data trust equation. Putting the onus on technology rather than clinicians to integrate external data into the system of record has emerged as a top priority in the realm of healthcare interoperability.

“From the clinician’s perspective, needing to go through and manually add or reject this information is time-consuming and cumbersome,” Thole asserts. “Innovation must eliminate this effort by providing a clear history of where the data came from within the EHR system and creating new efficiencies and time savings. We know it will take time for clinicians to get to that level where they can trust external sources. But having those capabilities and that optionality to make external data a part of their workflows through capabilities of Seamless Exchange will help get us there.”

What’s more, giving clinicians power over the patient record goes a long way toward building that trust in data from outside sources. Interoperability shouldn’t stop at simply delivering a patient’s clinical record. The industry must work to improve the clinician’s user experience in the EHR through intuitive workflows for managing external data, which offer context through documentation of data provenance and precedence. Additionally, it takes collaboration between technologists and providers to understand regional nuances; which sites share trustworthy data that can be automatically incorporated into the local record, and which sites provide data that must be screened before it is accepted? This customization of trusted sources is essential to meaningfully reduce the data reconciliation burden for providers.

“We wanted to make sure that we’re getting the right information into the chart, which is why clinicians must have the ability to review and cleanse the record of erroneous information. With Seamless Exchange, we’re able to remove the noise through deduplication and surface the most timely and newest data in an actionable way. These capabilities allow us to exchange data in a way that leads to meaningful insights and improves patient outcomes,” says Jackson.

Advancing healthcare interoperability is a journey rather than a destination. For health information to improve care delivery and patient outcomes, clinicians must have not only access but also the means to view pertinent and timely information. Efforts to improve data standardization and integrity will speed the movement of data between healthcare organizations and ensure that high-quality data supports high-quality clinical decision-making — and ultimately, improve care outcomes.


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