Whether you’re navigating compliance with the HTI-1 Final Rule, adapting to the new version of USCDI, or implementing advanced analytics, the right terminology management solution is essential. But with so many data strategies and tools available on the market, how do you choose the best one for your organization?
This article will walk you through six key questions to ask when evaluating data quality solutions for healthcare data normalization and terminology services. Armed with these insights, you’ll be equipped to identify a tool that aligns with your organization’s needs and goals while supporting data accuracy, collaboration, and streamlined workflows.
Why evaluating health data normalization solutions matters
Investing in the right terminology management solution isn’t just about compliance. Poorly managed systems can lead to coding errors, data inconsistencies, and lost insights about how care was delivered due to inaccurate analytics. Such gaps not only disrupt critical operations and create data interoperability challenges but also undermine the quality of patient care.
Instead, a robust, well-designed terminology service ensures:
- Accurate clinical decision-making
- Seamless data sharing across systems
- A trusted data foundation for AI and machine learning models
- Reduced time-to-value through faster integration of new data sources
Choosing the right solution means carefully evaluating how it easy it is to use to improve data quality, fosters collaboration, and adapts to evolving healthcare standards. To make this process easier, start with these six critical questions.
Six key questions to ask when choosing the right clinical terminology management vendor
1. Is the solution designed around industry standards or proprietary content?
When considering tools that help you clean your data, it’s essential to differentiate between solutions built on industry-standard codes and those that rely on proprietary content.
Why it matters:
- Interoperability between healthcare systems requires data normalized to terminologies like SNOMED CT, ICD-10, or USCDI value sets.
- Proprietary content can lead to inaccuracies in analytics and create ongoing challenges when integrating data with external systems or platforms.
What to look for:
- Rapid updates following changes by standards bodies (e.g., updates deployed within seven days of release).
- A commitment to ensuring data normalization aligns with industry-approved coding frameworks.
By focusing on solutions which prioritize standardized terminologies over proprietary mappings, you can avoid data fragmentation and inaccuracies while supporting seamless analytics.
2. How does the solution ensure clinical accuracy?
Clinical accuracy is non-negotiable in healthcare terminology management. Misleading mappings or errors in value sets can result in misdiagnoses, care delays, or inaccurate analytics.
Why it matters:
- Accurate coding directly impacts patient safety, treatment plans, and decision-making.
- AI-only approaches can result in false positives or misclassifications, ultimately eroding confidence in data quality.
What to look for:
- Multi-step review workflows that include expert manual verification alongside automated processes.
- Collaborative processes that allow clients to review and refine mappings.
- Deep clinical and terminology experience and expertise.
3. How comprehensive is the value set management?
Value set management is one of the most challenging and critical aspects of data management and standardization process. Mismanaged value sets can lead to compliance risks and inconsistent data.
Why it matters:
- Robust value set management reduces data discrepancies, ensures alignment with HTI-1 requirements, and lowers the risk of coding errors.
What to look for:
- Tools offering frequent updates (e.g., weekly refreshes of therapeutic classes and RxNorm value sets).
- Advanced features for categorization and comprehensive coverage across medications, diagnoses, and procedures.
- Time-saving workflows that simplify ongoing maintenance and updates.
4. How Does the Solution Support Version Control and Team Collaboration?
Terminology management isn’t just about technical accuracy; it’s also about human collaboration. Tools that lack proper version control and team collaboration features often cause misalignment and operational inefficiencies.
Why it matters:
- Version control ensures changes are consistent and traceable across the organization, rather than with just one person.
- Collaborative workflows improve alignment between clinical, IT, and analytics teams.
What to look for:
- Clear, intuitive version histories that track updates and prevent conflicting changes.
- Features that facilitate communication and collaboration between departments and stakeholders.
- Solutions that offer flexible tooling which fosters efficient collaboration and version control, reducing errors and implementation delays.
5. Is the user interface intuitive and accessible?
Even the most powerful solution will underperform if team members find it too difficult to use. A cumbersome interface not only slows down adoption but also frustrates users, leading to poor ROI.
Why it matters:
- A user-friendly design ensures faster onboarding for technical and non-technical users alike.
- Teams with varying levels of expertise can focus on their tasks without being bogged down by complicated workflows.
What to look for:
- Interfaces that balance simplicity with advanced capabilities, offering intuitive navigation for all users.
- Solutions that consistently receive positive usability feedback.
6. How quickly can the solution be implemented?
Lengthy implementation timelines can disrupt operations and delay results, especially when compliance deadlines like HTI-1 are fast approaching.
Why it matters:
- Rapid deployment allows your organization to meet compliance deadlines without costly delays.
- Faster implementation reduces time-to-value, letting your team benefit from powerful out-of-the-box functionality sooner.
What to look for:
- Solutions known for significantly faster turnaround times compared to other tools that often require months of fine-tuning.
- Out-of-the-box capabilities that minimize the need for extensive customization while still delivering high levels of accuracy.
Future-proof your terminology management
Selecting the right tool for normalizing and standardizing health data isn’t just about ticking boxes for compliance. You need a strong data foundation for operational excellence and future-proofing your organization’s ability to deliver exceptional care. By asking the six questions outlined above, you will be able to identify a solution that not only meets your data management needs but also unlocks new opportunities for innovation and growth.
The healthcare industry is evolving rapidly, and compliance deadlines for data interoperability are closer than you think. Don’t wait until it is too late. Schedule a consultation with Health Language data experts today and learn how we can enhance your terminology management workflows, ensure compliance, and set your organization up for success.
