There are fundamental limitations with the usability of electronic health record (EHR) data when benchmarking clinical quality, understanding patient populations, and conducting research studies. This can be attributed to the slow integration of industry accepted data standards for the collection of disease and specialty specific variables. This lack of consensus has impacted the way physicians document clinical information (i.e., free text instead of discrete data fields). It has made the information that is captured highly variable and difficult to access and decipher for outside parties. These factors impede efforts to coordinate and unify patient care.

True interoperability and usability of EHR data will only be achieved when both technical and semantic hurdles are overcome. Medical Specialty Societies (MSSs) are often the best candidates to lead specialty-centric data standardization efforts and drive the development and adoption of new data standards for their practice areas. Their knowledge and access to deep clinical expertise, physician-centricity, and strong convening power across institutions and geographies provides them with this unique industry role. These organizations also stand to benefit from improved data standardization, as more usable data allows them to better track care quality, support value-based care contracts, and reduce the reporting burden on physicians and care staff.

Understanding the Data Standardization Process
Data standardization operates in two phases: building the standards and then disseminating them. In the building phase, the foundation of data standards is laid by soliciting feedback and fostering consensus. Driving clinical documentation standardization is a complex and resource-intensive process, but it is critical for advancing research and patient care. MSSs can bolster their standardization efforts by leveraging several strategies. These include building on pre-existing endeavors, aligning with contemporary interoperability guidelines, and collaborating with industry stakeholders. These groups may include patients, clinicians, and researchers to understand what data needs to be collected as well as directly with IT vendors to champion the widespread embrace of new standards.

Following development, the dissemination phase takes precedence, aiming to promote meaningful change across the industry. The ultimate goal is to seamlessly weave new elements into future real-world applications and practices. This dissemination phase involves getting buy-in from key stakeholders, such as EHR vendors and physicians, that can be accomplished through customized messaging regarding logistical, implementation support, and incorporation of new standards into existing workflows. To aid in this journey, below are various strategies that can help simplify the complexities associated with developing and disseminating data standards.

Four Key Strategies for Developing Data Standards

1. Simplify and Build upon Existing Efforts: Rather than reinventing the wheel, organizations should leverage ongoing initiatives led by expert committees, academic medical centers, specialty clinics and EHR vendors to develop data standards for various diseases. Understanding and utilizing existing efforts as a starting point can drive consensus and prevent unnecessary duplication, ultimately improving future data standards and promoting widespread adoption.
2. Define Use Cases to Guide Variable Selection: In addition to enhancing patient care and management, data standards should support the identification of new clinical endpoints and improved outcomes. By identifying the specific use cases for the data standards, organizations can ensure that the collected data delivers maximum value for research studies. Linking data elements to these use cases can facilitate real-world adoption and advocate for the inclusion of new standard data elements in future versions.
3. Balance Accuracy and Usability: Recognize that healthcare providers face time constraints and may be resistant to changing their existing practices. While perfect and highly detailed data may have theoretical value, it's crucial to strike a balance between the effort required to collect it and the downstream value it provides. Standards should be designed to be both accurate and usable, considering practical constraints and provider workflows.
4. Stay Aligned with Evolving Interoperability Guidelines: Regulatory standards for data capture, storage, and sharing are constantly evolving. While the current USCDI and HL7 guidelines may not cover all critical data elements for every disease or condition, MSSs should remain aware of existing and upcoming rules to ensure their standards align with evolving interoperability requirements. Regularly monitoring the regulations published by organizations like ONC and CMS can help maintain alignment and support effective interoperability.

By implementing these strategies, MSSs can:

• Play a vital role in the development and adoption of data standards, reducing reporting burdens, and promoting improved healthcare outcomes;
• Effectively disseminate data standards, ensuring widespread adoption and integration into healthcare practices;
• Take the next step of sharing these standards across the industry to build a cohesive procedure involving data.

Four Strategies for Disseminating Data Standards

1. Tailor Approaches to Different Conditions: Recognize that there is no one-size-fits-all approach to data standard adoption. Different conditions may require varying strategies. For common diseases, a widespread implementation plan is necessary, while rare diseases may only require targeting a few specialty centers for adoption.
2. Collaborate with Health IT Vendors for Direct Implementation: Engage health IT vendors to incorporate new standards directly into their platforms, rather than relying on individual sites to implement them. This approach is particularly effective for rare diseases, as it reduces the resources needed at each site. MSSs should focus on engaging patients with vendor systems in their disease area first before expanding to other platforms to maximize impact.
3. Support Adoption with Resource Sharing: Provide resources to support staff training and explain the proper use and definition of data standards. Even well-curated standards require explanation and guidance for successful adoption. MSSs can reduce the burden of change on providers by offering educational materials and support.
4. Integrate Standards into Clinical Workflows with Real-Time Data Feedback: Align the implementation of standards with provider workflows to promote adoption. Demonstrating the benefits of new standards in real-time is essential for motivating adoption and uptake. Standards can be integrated into clinical workflows through various methods, such as collecting specific data during each visit, creating discrete data fields, or modifying existing note templates. Seamless integration with existing electronic health records (EHRs) and clinical workflows is crucial, and organizations should set and implement clinical data standards accordingly.

By implementing these strategies, MSSs can:

• Play a vital role in the development and adoption of data standards, reducing reporting burdens, and promoting improved healthcare outcomes;
• Effectively disseminate data standards, ensuring widespread adoption and integration into healthcare practices;
• Take the next step of sharing these standards across the industry to build a cohesive procedure involving data.

Harnessing the Value of Clinical Data Standardization: Maximizing the Benefits
Standardizing clinical data poses numerous challenges, but even partial successes can lead to significant downstream advantages. While achieving universal adoption of data standards is unlikely, MSSs can still tailor their work to accommodate the needs or preferences of individual providers or health systems. Even with partial adoption, the implementation of data standards represents a significant accomplishment. Each step toward interoperability brings incremental gains, allowing more MSSs and providers to benefit from the availability of more usable data. Starting with the standardization of a key measure in a specific specialty or disease area provides a valuable foundation, enabling the generation and maintenance of momentum.

To determine the most effective way to develop and disseminate your health data standards while mitigating any challenges, learn more in our white paper Medical Specialty Societies Have a Key Role to Play in Driving Clinical Data Standardization Especially for Reducing Reporting Burden