Frequently Asked Questions about the Data Quality Workbench

The Health Language Data Quality Workbench is a healthcare-focused terminology management platform. Its primary purpose is to ensure your organization’s data is accurate, standardized, and high-quality for all uses – from clinical decision support and analytics to claims processing and interoperability. In essence, it serves as a centralized terminology server and reference data management solution. It enables data validation and cleansing, mapping of local codes to standard codes, and even authoring of custom terminologies, so that you maintain a single source of truth for codes and terminologies across your enterprise. By using the Workbench, healthcare organizations can trust that their data is up-to-date and fit-for-use, powering better decisions and outcomes across clinical, financial, and operational domains.

The Data Quality Workbench is used across multiple sectors of healthcare – and it provides value to any organization that needs to manage and ensure the quality of clinical or billing data. Typical users include: 

• Health Plans (Payers): For example, a health insurance company’s data governance team or analytics team would use the Workbench to normalize data coming from various provider sources, maintain code groupings for coverage policies, or update reference tables for claims. Payers use it to improve risk adjustment coding accuracy, ensure their HEDIS quality measure value sets are up to date, and to standardize data for population health analytics. 
• Healthcare Providers (Hospitals/Health Systems): In provider organizations, the clinical informatics department or HIM (Health Information Management) team might use the Workbench to map legacy codes to standards during EHR transitions, to manage the hospital’s custom procedure or problem lists alongside standards, and to feed clean data to enterprise data warehouses. Additionally, Quality improvement staff in hospitals use it to define cohorts (via value sets) for clinical analytics. 
• Health IT Vendors and Solution Providers: Many vendors (EHR, analytics platforms, population health tools) partner with Health Language to embed terminology management into their products. If you’re a vendor building a healthcare application, using Workbench capabilities (via API or as an OEM component) can accelerate your development and ensure your end-users get best-in-class terminology support without you building it from scratch. 
• Life Sciences and Research Organizations: Pharmaceutical companies or clinical research networks dealing with real-world data can use the Workbench to standardize and categorize data from different sites. For instance, normalizing clinical trial data or outcomes data that come coded differently across sources. It’s crucial in such settings to have high-quality data for research validity. 
• Public Health Agencies and HIEs: Government or regional Health Information Exchanges use it to manage public health code sets and to map data from various EMRs to a common vocabulary for centralized reporting and surveillance. 

Within these organizations, typical roles that directly engage with the Workbench include: Data Architects, Chief Data Officers (CDO), Data Governance Managers, Clinical Informaticists, Coding Managers, Terminology Analysts, and IT integration specialists. At a strategic level, CIOs and CTOs value the Workbench because it solves systemic data quality issues that otherwise hamper analytics and interoperability. They see it as foundational to initiatives like enterprise data warehousing, AI/ML projects (which require normalized data), and regulatory compliance. Product Managers in health IT firms appreciate it because it enhances their product capabilities (e.g., adding robust search or mapping features via the Workbench). 

In short, any healthcare entity that needs accurate, consistent data – whether for patient care, reporting, or innovation – can benefit. Anyone who relies on healthcare data in your organization – from a clinical quality director to a claims analyst – ultimately benefits, because the Workbench ensures that the data they use is clean, current, and meaningful. By implementing it, organizations in provider, payer, life sciences, and vendor spaces have all seen improvements in efficiency and confidence in their data. 

The Data Quality Workbench supports over 100 standard clinical terminologies and code sets out-of-the-box. 

This includes all major coding systems such as SNOMED CT, ICD-10-CM/PCS, LOINC, RxNorm, CPT, HCPCS and many more. It also encompasses value set collections (e.g. HEDIS quality measure value sets, social determinants of health codes, etc.) and crosswalks or mappings between standard code sets. 

Essentially, any widely used healthcare terminology or classification system is likely included. (For a full list, you can access our content catalog detailing all supported code sets and maps.) This comprehensive content library means you can work with diagnosis codes, procedure codes, lab test codes, medication dictionaries, public health and regulatory code sets, all within one platform.

Yes. The platform allows you to create and maintain local (proprietary) code systems, value sets, and mappings in addition to the standard terminologies. It includes authoring tools so you can define your own codes or groups of codes (for example, custom service codes or internal classifications) and map them to standard codes as needed. These tools come with built-in workflow and collaboration features, including version control and full audit trails, to govern changes to your proprietary content. Importantly, user access controls can be configured – for example, to restrict who can edit or approve internal codes – ensuring robust data governance even for your custom terminologies.

Health Language has a dedicated content infrastructure that handles the entire lifecycle of reference data. The process works as follows:

First, our proprietary system continuously monitors the official standards bodies (such as the AMA, Regenstrief, SNOMED International, CDC, etc.) for updates to relevant data. When a new release is officially available (whether it’s a scheduled update like “ICD-10-CM October release” or an unexpected emergency code update), the Health Language platform automatically ingests that update.

During ingestion, the data goes through validation against known rules (both the standards body’s rules and Health Language’s additional data quality rules) to catch any anomalies. Then Health Language applies its final quality control process: this is a rigorous QA step where the new content is checked for completeness, correctness, and consistency with prior versions. (In fact, this QA is so thorough that Health Language has occasionally identified issues in the standard content itself and worked with the standards body to get them corrected.) We pride ourselves in keeping history available for clients who desire it, assigning effective dates to all relevant data, including various additional properties, and mapping to related codes. Once validated, the new codes are transformed into the common format used by all Health Language products.

Finally, the updated content is published to the Health Language Content Portal where it’s available to customers. The Workbench will notify your users (or automatically retrieve, if configured) that new content is available. You can then access the updates via the UI, download files, or let your integrated systems call the APIs for the latest data.

This end-to-end content update mechanism ensures you always have timely access to new codes (like new lab test codes, new medications, revisions to guidelines, etc.) without having to manually load or fix data. All historical versions are retained with their validity periods, so you can always refer back or apply changes retrospectively if needed. In summary, acquisition and publishing of reference data in the Workbench is highly automated and robust, giving you confidence in the accuracy and currency of the content. 

Ensuring data quality is a core focus of the platform. Several mechanisms and processes guarantee accuracy: 

• Standards-conformant content: As described, all standard code sets are rigorously validated against official guidelines when ingested. The Workbench represents the data exactly as issued by the standards body (or with clearly documented enhancements), so you’re working with authoritative content.
• Health Language quality control: Health Language applies additional validation rules on content. For example, they verify code hierarchies, proper mappings, and even check for issues like inactive codes being inadvertently reintroduced. This QC process has, on many occasions, caught errors in the source content which were then fixed upstream.
• Data integrity constraints: Within the Workbench, reference data is stored with relational integrity. You cannot, for instance, map a code to a target that doesn’t exist, or save a concept with missing mandatory attributes.  
• Audit trails and review: Every change, especially to local content, is tracked. You can review the audit log to verify that changes were made correctly and by an authorized person. If a mistake is made in editing a local code or value set, it can be identified and rolled back because the system keeps a history .
• Automated mapping suggestions: For mapping tasks, the platform’s AI-enabled suggestions help improve accuracy by recommending likely matches. These suggestions are derived from clinical knowledge and past mappings, reducing the chance of human error or oversight. Human experts then review and approve, giving a dual layer (machine + human) of accuracy for mapping outcomes. 

The interface of the Data Quality Workbench is designed to be highly user-friendly and was built with a range of users in mind. It’s a modern web-based application that feels similar to common web productivity tools. Key aspects of its usability: 

• Intuitive Search: Users (whether a coder, analyst, or support rep) can easily search for codes or terms. The search engine supports fuzzy matching and spelling correction – for example, if a user types a partial term or a misspelling, it will still find the right code .
  It also recognizes millions of synonyms and colloquial terms. For instance, a search for “heart attack” will bring up myocardial infarction codes, even if those words aren’t typed, because of the built-in library of consumer-friendly and clinical synonyms. This means even non-experts can find what they need without knowing exact code names. 
• Code exploration: When you select a code, the UI presents all relevant details (definition, hierarchy/parents/children, mappings, etc.) in a clear layout. You can navigate hierarchies (drill down into SNOMED or ICD hierarchies, for example) with expandable tree views. This helps users understand context without getting lost. 
• Task-oriented design: Common tasks like creating a mapping, editing a value set, or checking code status are guided by the UI. Wizards or step-by-step forms are provided for complex operations. For instance, adding a new value set member might involve a pop-up search window to pick a code, which is straightforward. 
• Role-based simplicity: The interface can be customized to the user’s role. A non-technical user such as a Customer Service Representative might be given access in a “lookup” capacity – where they can search and view codes and perhaps run pre-defined reports, but not see the more complex configuration menus. This way, they see a simplified view. Meanwhile, a terminology analyst or informaticist can access the full suite of authoring and mapping tools. 
• User experience praised: Clients have cited the Health Language UI as one of the most user-friendly and feature-rich in the industry for terminology management. It’s been refined through feedback to ensure even those who are not deep terminology experts can navigate it. The learning curve for basic usage (searching, browsing) is very minimal. For advanced usage (authoring, complex mapping), Health Language provides training, but the tools themselves use familiar paradigms (forms, tables, drag-and-drop for hierarchy ordering, etc.). 
• Help and documentation: Within the application, context-sensitive help is available for each module, and field-level tooltips guide users on what to do. So if someone is unsure about a feature, help is often a click away. 

In summary, the interface is highly approachable. Clinical staff, business analysts, and IT staff alike can comfortably use the Workbench. Non-technical users in roles like data governance or quality improvement have successfully used it to retrieve and work with data because of the intuitive design.

Content updates occur very frequently – whenever standards bodies release new content. Some code systems update on a quarterly or monthly basis (even weekly for certain drug databases), and Health Language pushes those updates to the Workbench as soon as they are available and verified. In fact, for many critical code sets, updates are released on a weekly basis to ensure customers have the latest data. For example, if new COVID-related codes are released outside the usual cycle, an emergency content update would be issued. 

As for software updates to the platform (feature enhancements, bug fixes), those are typically released on a regular cycle as well. Being a cloud service, Health Language can deploy patches and upgrades with minimal disruption. Security patches or critical fixes are applied as needed, without waiting for a long release cycle, ensuring the platform remains secure and reliable. Since these updates are managed by Wolters Kluwer, your team doesn’t have to do heavy lifting – you’ll just notice new capabilities or improvements. In summary, expect a steady cadence of updates: content updates in real-time alignment with standards (often weekly or as needed), and platform application updates periodically to deliver new value and maintain top performance. 

Yes, Health Language provides a number of starter value sets and value set collections as part of the content library. These include standard value sets for common use cases – for example, the full set of HEDIS quality measure value sets, CMS Hierarchical Condition Category (HCC) groupings, social determinants of health (SDOH) value sets, and others frequently used by healthcare organizations. These ready-made groupings can save you time, as you can adopt or customize them rather than building from scratch.