QH+C2C+Summary+of+Recommendations

Abstract
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Background

 * Summary of the problem of concept mapping (1 para)
 * Summary of the problem of concept mapping as it relates to distributed query networks (like query health) (1-2 para)

Scope
In order to investigate the issues of concept mappings related to the Query Health initiative, the initiative formed its Concepts to Code (C2C) sub-workgroup on. Over a six week period, the identified sources of related expertise and engaged them to deliver testimony on the state of art in concept mapping. The goal of this effort was to create a summary document to inform the Query Health community of the best available practices for the implementation of a concept mapping component within a distributed query network such as Query Health. It is our hope that the information gained and conclusions reached may provide guidance to other concept mapping efforts in healthcare.

Concepts
"A noun is a person, place, thing, or idea. Codes are used to identify these various concepts. The concept may be very discrere (as in a specific medication in specific packaging with a given set of active ingredients, or it may be broad, describing a particular class of disorders. "Coding systems use different ways to define the boundaries of the concepts represented by a particular code.
 * The HL7 Version 3 vocabularies provide a human readable definition for the concepts that they represent.
 * ICD-9-CM and ICD-10-CM provide a collection of terms that can be used to determine whether a concept is included or excluded from the idea represented by a particular code.
 * LOINC describes laboratory tests by describing the (usually chemical) component being measured, the substance being analyzed, data type of the measurement produced, the specific laboratory method used to generate the result, and a number of other attributes to completely define a code.
 * SNOMED CT provides a number of preferred and alternative terms (synonyms) for a concept, and also uses the position of the concept in the code hierarchy to define the meaning of the concept.
 * Finally, UCUM uses the rules of mathematics to define the meaning of its coded concepts." (Boone, 2011)

Codes
"A code identifies a unique concept in a coding system. Multiple codes may represent the same concept, but this is rarely used in coding systems. "Codes can be opaque identifiers, meaning that the code value itself has no human interpretable structure. SNOMED CT and UMLS use opaque identifiers. These types of coding systems require some sort of human interface to select appropriate codes for a concept. Some organizations develop interface vocabularies for these coding systems. These provide readily understood and easily remembered phrases to locate codes. "Codes can also have an interpretable structure. The ICD-9-CM and ICD-10-CM coding systems are organized hierarchically. The code has different recognizable chunks that make it easy for humans to remember code values. Human coders can often code several clinical documents using ICD-9-CM without needing to look up any codes because of the structure of the code system. The structure of the coding system is the human interface into it." (Boone, 2011)

Coding Systems
"A coding system is a collection of codes. Coding systems can be simple lists of terms that are not explicitly related to each other (e.g., LOINC), or they can be organized in a hierarchy (e.g., ICD-9-CM and ICD-10-CM), or through a variety of different relationships (e.g., SNOMED CT). "The numbers of concepts that coding system(s) can represent may be finite in length (e.g., LOINC and ICD-9-CM), or have infinite length via post-coordination (e.g., SNOMED CT) or code construction rules (e.g., UCUM). "Coding systems can have multiple versions. Best practice for coding indicates that a code is never reused in different versions to represent different concepts, but this is not always adhered to in all coding systems (e.g., ICD-9-CM). For coding systems such as these, sending the coding system version is important in the communication, since it could not otherwise be clear which definition of a code was being used. "Each code in a coding system identifies a unique concept. A code can be atomic, representing a single simple concept or it can represent a complex concept that is made up of smaller concepts." (Boone, 2011)

Value Set
"A value set is a collection of codes from possibly more than one coding system representing a set of (usually) distinct concepts. Value Sets can represent subsets of a coding system used for a specific purpose, and are commonly used as a way to constrain the legal values appearing in an implementation guide. "An extensional value set is defined by enumerating each code found in it. Intentional value sets are defined by providing the rules (an algorithm) to determine whether a code is a member of the set. Value sets can have subsets which are also value sets, and these can also be defined intentionally or extensionally. "Intentional Value sets can be dynamic, which means that the set of values produced by it can vary as the underlying code system(s) are updated, or they can be static, using a fixed code system version. Extensional value sets are always static." (Boone, 2011)

Concept Mapping


Methods

 * List what we did to investigate the problem
 * Convened workgroup
 * identified sources of expertise
 * Defined semi-structured interview with workgroup (questions to be asked)
 * heard presentations from sources of expertise
 * Asked follow-up questions on central themes
 * reviewed evidence and extracted key themes
 * synthesized (in this document) and gained consensus on this work

Results

 * Table 1: List of organizations a) identified during the initial scan, b) who presented at a SWG meeting.
 * List questions asked

Sub-sections

 * have a subsection for each presentation with the following:
 * General summary of the organization
 * Summary of the tool, framework, or standard presented
 * Key points from the presentation

Discussion

 * Overall findings of the work effort
 * Each framework, standard, or tool we felt we should recommend and why
 * Each framework, standard, or tool we felt we should not recommend and why
 * Places we felt our methods may have missed data
 * thoughts on future work we could do

Conclusions

 * A bullet list of the framework, standards, and tools we recommend that QH implement