The U.S. Department of Health and Human Services recently named the first six Qualified Health Information Networks (QHINs) under the Trusted Exchange Framework and Common Agreement (TEFCA), marking a major step forward in health data interoperability.

While many anticipate a surge of information with increased interoperability, Micky Tripathi, National Coordinator for Health IT, recognizes the difficulties of sharing information between organizations and the resulting “operational friction in interoperability.” The QHINs were established to alleviate this challenge.

Searching for Diagnostically Relevant Data

The increased flow of healthcare information between systems may create a challenge for clinicians to find diagnostically relevant information among a flood of incoming data. Healthcare information is currently classified into separate domains using different terminologies and coding systems, making it difficult for clinicians to see how well a patient’s condition is being managed.

Clinicians are already challenged to find clinically relevant information in EHRs, especially when managing multiple conditions, under value-based care. To address this issue, they require systems that not only support coding of diagnoses and transactions but also filter information at the point of care and present clinically actionable views. We refer to this capability as “diagnostic interoperability.”

New Tools for New Challenges

The implementation of the 21st Century Cures Act, TEFCA, and the establishment of QHINs will finally bring interoperability to healthcare systems. As a result, a multitude of codes and notes will be exchanged between systems––requiring the clinician-facing systems to help users make sense of it all. This creates an opportunity for new tools that enable clinicians to easily access diagnostically relevant information at the point of care. These tools should allow clinicians to select any problem or clinical issue for a patient and instantly view the key indicators for that issue.

TEFCA, QHINs, FHIR, and terminology standards will facilitate the transmission and reception of health data. However, the challenge for clinicians will be to quickly find the necessary information for assessing, evaluating, managing, and treating a specific condition. With the advent of interoperability, health data will be in different terminologies and formats that were not designed to work together to present a comprehensive view of a condition––or to be used by clinicians at the point of care.

EHRs organize this information into separate sections or tabs, making it time-consuming for clinicians to navigate and find the relevant details. Although the EHR may contain all necessary information for informed clinical decision-making, finding all of the precise details is not always easy.

A Better Way Forward

Value-based care requires that all relevant information for a diagnosis be instantly available to clinicians at the point of care to effectively monitor and manage chronic conditions. Clinicians need a clinical toolset that allows them to select any condition and immediately see a diagnostically organized view of all the relevant details.

Medicomp’s Clinical Data Relevancy Engine, which is at the core of everything we provide, helps to organize data diagnostically––in the way that clinicians think and work. So, a clinician simply clicks on a problem in the EHR, and sees everything related to it longitudinally, and in clinical context. It’s really that easy.

Quippe ties all this disparate information together at the point of care to diagnostically filter text, codes, and everything else to make it actionable and usable either at the point of care or in a review mode. This is especially important as value-based care and interoperability continue to gain prominence.

Getting information into a patient record is getting easier, thanks to advances in artificial intelligence, NLP, and other technologies – but regardless of how the data gets into the record, clinicians need the ability to quickly see information relevant to a specific condition, without searching for it.

Diagnostically connected information is the key to chronic condition management, achieving compliance with value-based care workflows, and satisfying documentation requirements. The next step in interoperability is diagnostic interoperability, which could be the impetus for value-based care success and the transformation of EHRs from clinician burden to essential tools.