Value Set Guidance | eCQI Resource Center

About
Value Set Guidance
Connect

Value Sets

Value sets are lists of codes and corresponding terms from standard clinical vocabularies (such as Current Procedural Terminology, SNOMED CT, RxNorm, and Logical Observation Identifiers Names and Codes), that define clinical concepts to support effective and interoperable health information exchange.

The Value Set Authority Center, hosted by the National Library of Medicine, serves as the central repository for the Centers for Medicare & Medicaid Services electronic clinical quality measure value sets.

This guidance is intended for value set authors. The guidance provides direction on the best practices for authoring and maintaining value sets for quality measures, electronic clinical quality improvement, and other applications.

The Value Set Workgroup (VSW) has suggested guidelines and principles to follow to name a value set. Documents related to value set use and best practices, commonly used by measure developers, measure stewards, and value set owners or are specific to the VSW:

CMS Measures Management System (MMS) Blueprint content on the CMS MMS Hub
VSW Governance Document
Health Level Seven International® Value Set Definition Document and Fast Healthcare Interoperability Resources® terminology site
Value Set Authority Center (VSAC)

The VSW's review focused on identifying guidance given in each document and comparing for similarities and differences. Based on the review, the VSW suggested principles came primarily from the CMS MMS Blueprint content and the VSAC Support Center. They were determined to be the most well-articulated best practices in value set naming and have formed the framework for VSW Value Set naming best practices and descriptions.

Value set naming best practices

Limit the value set name to as few words as possible and no more than 128 characters.

Create a short, descriptive, user-friendly title for the value set. This name does not need to be machine-processing friendly and may contain things such as punctuation and white-space.
When creating the value set name, avoid a long description yet capture critical, distinctive aspects of the membership criteria.

Create the value set name to convey the specific distinguishing characteristics of the member concepts.

Use a sufficiently descriptive name.
- The value set name "Diabetes" is not sufficiently descriptive if it only contains codes describing Type II diabetes.
- The value set name "Diabetes Type II" is a better name because it more effectively describes the scope of the value set.
- Avoid including descriptions of the intended, but not achieved, content.
- The measure developer should correct the name if not able to align the value set content with the initial name given to the value set.
- For example, if initially named "Oral Anticoagulants" when the intent was to capture only oral anticoagulants for chronic atrial fibrillation, change the name to "Oral Anticoagulants for Chronic Atrial Fibrillation" to align it with the intended purpose.

Make value set names unique. Duplicate value set names are discouraged and should be uncommon.

Due to the uniqueness of the value set purpose and content, name redundancy should not occur.
Grouping value sets may have member value sets with the same name, as these members often have the same purpose, yet their content is differentiated by specific code system content. Value sets with different metadata (purpose, intent, inclusion, and exclusion statements) should always have names reflective of this information and therefore should have a unique name.

Use correct spelling and grammar.

Separate multi-word terms by spaces and not by any other characters.
Use title case (capitalize first letters of all words, except prepositions, as in a title).
Do not include "camelCase," composite, or delimited words or phrases.

In the value set name, avoid including:

VSAC prohibits certain characters (+ * ? : -| ! " %) and provides a system warning if used.
Value set steward name – The VSAC database captures the steward name in a separate field in the metadata, which is bound to the value set.
Name of the specific data element the value set was created to support.
- Do not include the concept category that characterizes the context of use, unless it describes a primary distinguishing characteristic of the value set requirements.
- For example, only include the word “Procedure” when the context of the focus is ambiguous.
  - Appropriate Name – Insulin Dependent Diabetes Diagnoses
  - Inappropriate Name – Diabetes Condition, Diagnosis, or Health Concern
  - Appropriate Name – Mobility Related Health Concerns
  - Inappropriate Name – Mobility Health Concerns
- Quality reporting program name unless it describes a primary distinguishing characteristic of the value set.
- Names of measure types or settings (e.g., hospital measures, process measures).
- Code descriptors within the value set name.
- Abbreviations unless widely used in the medical literature, e.g., HIV.

Never use the word “other” as an alternative to another value set.

For example, do not name a value set "Other Endophthalmitis" just because a value set named "Purulent Endophthalmitis" already exists. Be as specific as possible. "Other Endophthalmitis" lacks adequate information value set consumers need.
Non-purulent Endophthalmitis could be a better name to indicate another type of Endophthalmitis.

Renaming:

Rename a published value set to add clarity to the name and version the value set.
If there is a change to the description, intent, or content, consider the need to create a new value set.

Value set description best practices

High-quality value sets provide a clear and comprehensive description of the constituent concepts of the value set including the intent or use of the value set. In the VSAC, a purpose statement has four components (clinical focus, data element scope, inclusion, and exclusion criteria) to provide information a value set user can use to understand the content, the use of the value set, and the scope or breadth of concepts for inclusion or exclusion in the value set. Currently, the VSAC does not require a purpose statement to publish a value set, however, it is best practice to include a purpose statement with all four components completed for a published value set.

If the focus or intent of the value set is changed meaningfully, the value set should be evaluated for continued appropriateness as fit for purpose. If not found consistent with the original focus or intent, creating a new value set should be considered.

Follow these guidelines for producing high-quality value sets.

Purpose Statements

Clinical Focus

Clinical Focus is a required text statement describing the general focus of the value set including a description of the intended constituent concepts. The Clinical Focus can include information about clinical relevancy, or a statement about the general focus of the value set, such as a description of types of messages, payment options, or geographic locations. The statement should be written as a full sentence with end punctuation (period). Over the course of a value set’s lifecycle, the measure developer should not change the clinical focus in any meaningful way. The VSW recommends

Format: The purpose of this value set is to [verb] concepts for/of [noun(s)].

Appropriate verbs
- Identify
- Represent
- Describe
- Define
- Group

Example: The purpose of this value set is to represent concepts for a diagnosis of type I diabetes mellitus.

Example: The purpose of this value set is to represent concepts for conjugated estrogen/medroxyprogesterone combination medications.

Example: The purpose of this value set is to represent concepts for laboratory tests measuring glucose.

Data Element Scope

Data Element Scope is a required text statement describing how the data element relates to the value set to which it is bound. This context of use often constrains the semantic type of the allowed constituent concepts. The statement should be written as a full sentence with end punctuation (period). The VSW recommends

Format: This value set may use a model element in the [QDM or other data model category].

Example: This value set may use a model element in the QDM category of Medication.

Inclusion Criteria

Inclusion Criteria is a required text statement that describes the concept or code criteria the measure developer included. The statement should be a full sentence with end punctuation (period).

Format: Includes concepts that [verb] [description].

Appropriate verbs
- Identify
- Represent
- Describe
- Define
- Group
The form of the description should follow these examples:
- a diagnosis of
- a procedure for
- an encounter for/specific to
- a medication for

Example: Includes concepts that describe a medication specific to generic, prescribable esterified estrogen medication.

Note: An optional inclusion criteria statement can be provided when a value set has members that are not currently active in the code system used to build the value set. This optional statement will allow VSAC users to have more information for the use and intent of the value set. This information may help a user determine if the value set would meet their needs or if the inclusion of inactive codes would not be appropriate for their use. The statement should be included in the inclusion criteria component of the purpose statement of the grouping value set containing the extensional with the inactive concepts. The VSW recommends using the statement "Includes concepts that may no longer be valid in the code system of choice to facilitate lookback periods" to indicate inactive concepts are in the value set:

Format: Includes concepts that may no longer be valid in the code system of choice to facilitate lookback periods.

Exclusion Criteria

Exclusion Criteria is an optional text statement that describes what specific concept(s) or code criteria the measure developer would normally include, but specifically excluded and why. The statement should include end punctuation (period). It is good practice to populate this field with “No exclusions” if there are no exclusions. The VSW recommends the format

Format: Excludes concepts that [verb] [description].

Appropriate verbs
- Identify
- Represent
- Describe
- Define
- Group

Example: Excludes concepts that describe branded and non-prescribable esterified estrogen medications in combination with other medications.

Example: Excludes concepts that represent medications used to treat diabetes mellitus but are not commonly associated with severe hypoglycemia.

Value set content best practices

In VSAC, a value set contains specific codes derived from a single code system or vocabulary, for example, RxNorm, International Classification of Diseases (ICD)-10-Clinical Modification (CM), ICD-9-CM, SNOMED CT, Logical Observation Identifiers Names and Codes, or Current Procedural Terminology. Value set users refer to codes and their descriptions as concepts in VSAC, value sets can also be grouped to combine code systems. Value set authors can create value sets using several methods:

Extensional:

A set of concept codes and descriptors in the form of an enumerated list. An extensional value set in the VSAC contains codes from only one code system.

Intensional:

A list of codes based on a logical statement that often has an algorithmic basis for the selection of concepts based on concept properties or relationships as defined within the code system. An intensional value set in the VSAC contains codes from only one code system.

Grouping:

A collection of one or more value sets that when combined meet the requirements of the grouping value set purpose. Grouping value sets in the VSAC are often used to combine member value sets from different code systems so that the grouping value set expansion set includes concepts from multiple code systems. In VSAC, grouping value sets cannot group other grouping value sets.

The standardization of value sets is important, as it improves data comparison across programs, measures, or data sets. Adherence to quality criteria facilitates the reuse of well-defined value sets to advance research studies and promotes the interoperability of health-related systems. Value set authors should clearly understand major principles that define high-quality value sets. These guidelines will help to advance data sharing by helping to standardize and define the content of extensional, intensional, and grouping value sets:

Validity:

Value set authors should ensure all included concepts correspond to the intent and purpose of the value set. Users of value sets should review and consider subtle nuances of the concepts in clinical or administrative meaning.

Metadata Completeness:

Value sets have important metadata to understand the scope of meaning for the included concepts and the intended use, identity, and ownership. It is best practice to include value set name and purpose statement.

Non-redundancy:

Where possible, each value set should have a clear purpose that fits the desired program use. Multiple value sets with the same scope and use should be avoided particularly if the redundant value sets are used by the same program.

All Value Set Codes Are Active in the Code System:

The authors should consider only currently active codes for inclusion into a value set unless inactive codes have been intentionally included in the value set to facilitate a look-back period. This ensures proper maintenance of the value sets.

Descriptors Match Code System Descriptors:

Authors should make sure any concept descriptions manually added to value sets match the descriptions in the code system to which the concepts belong. The VSAC Authoring Tool provides a descriptor match check as a built-in function. The VSAC Authoring Tool performs this validation during batch import of codes into a value set and during manual insertions of codes and descriptors.

Code List Completeness:

A value set should contain all the relevant concepts for a particular data element. Authors should ensure the lists are lean and should scrutinize large value sets.

Logical Correctness:

A value set should contain only the relevant concepts for a selected data element and the concepts contained in the value set should strictly align with the described purpose.

Terminological correctness:

Ensure the value set’s concepts align with the appropriate terminology to represent the data element. When a code system groups concepts into distinct hierarchies, the presence of codes rooted in multiple distinct hierarchies may indicate an incorrect choice of codes. In complex cases, value set authors should consult terminology experts.

Concept Property Similarity:

Value set member concepts should not vary with respect to their properties and attributes, such as semantic type and term type. For example, a value set intended for prescribable drugs should contain only drugs with the property "Prescribable." This is applicable to concepts that have such properties. The properties should be more similar than dissimilar. For complex cases, value set authors should seek guidance from terminology experts.

Code System Alignment to Standards:

Value set authors should base their value set on the code system recommended by the standards depending on the purpose of their value set and the data model (such as the Quality Data Model) to which the value set authors may be adhering.

ONC Project Tracking System - eCQM Tracker (Jira)

Measures Management System Hub

Value Set Authority Center Collaboration Tool

Contact the Value Set Workgroup at ecqm-governance@icf.com.