Data Mapping Best Practices
Introducing the AHIMA Compendium http://compendium.ahima.org Throughout this brief, sentences marked with the † symbol indicate AHIMA best practices in health information management. These practices are collected in the new AHIMA Compendium, offering health information management professionals “just in time” guidance as they research and address practice challenges.
THE HEALTHCARE INDUSTRY collects vast amounts of elec- tronic data. ;ese data are captured in a wide variety of formats using various collection methods. Using and reusing health data for multiple purposes can maximize e;ciency, minimize discrepancies and errors caused by multiple data entry process- es, reduce costs of data acquisition and storage, and support health information exchange and interoperability. When data re collected in a speci;c format or coding system and the same or similar information is needed for a di;erent purpose, data maps from one system to another facilitate the reuse of data. In order for the data to be useful for all their intended purpos- es, semantic interoperability is required to achieve meaningful
exchange across settings, data sets, and standards. Maps are one
approach organizations are considering to achieve this goal.
;e International Organization for Standardization’s preferred
de;nition of mapping is “the process of associating concepts or
terms from one coding system to concepts or terms in another
coding system and de;ning their equivalence in accordance
with a documented rationale and a given purpose.” 1 ;e term
“coding system” is used to depict encoded data, generically including clinical terminologies, administrative codes, vocabularies, classi;cation systems, and any type of schema used to represent data in health information systems.
;is practice brief de;nes key data mapping concepts and
outlines best practices related to the development and use of
data maps.
Basic Mapping Concepts
Mapping features a number of terms such as source, target, forward, and reverse or backward maps (e.g., General Equivalence
Mappings). In order to understand mapping, it is important to
understand these terms.
;e source is the origin of the map or the data set from which
one is mapping. ;e target is the data set in which one is attempting to ;nd equivalence or de;ne the relationship.
Like other types of maps, there is a starting place and a ;nal
destination for each data item linked in the process. A map linking codes from ICD-9-CM to ICD-10-CM indicates that ICD-9-
CM is the source and ICD-10-CM the target. ;is type of map
is called a forward map because it maps an older version of a
code set to a newer version. A reverse map links two systems in
the opposite direction, going from the newer version of a code
set to the older version. 2
Each map produces unique results due to the disparity between the two versions of the systems. It is important to know
the map’s direction (forward or reverse) since the results depend on the direction.
Mapping Relationships
A map should describe how the source and target are related.
Degree of equivalency, match rating, and a rating scale using
numbers with designated values are used to describe the relationship between the source and the target.
Equivalence describes the relationship between the source
and target and informs users how close or distant the two systems are. A map’s degree of equivalence a;ects its utility and
reliability.
While one source code may map to one target code, the two
codes may not have the exact same meaning. ;is is especially
true when mapping a terminology to a classi;cation. Map developers must identify the degree of equivalence for each map
and document how it was determined.† When using maps for
clinical care the designation of equivalence is a critical element
so all ambiguity of the closeness of the match is eliminated.
From a data integrity perspective it is equally important for
the statement of equivalence to be easily understood and consistently applied by all map users. Because the map developer
generates this documentation, the exact terms may vary; however, the general concept is the same. Common terms include:
; No match, no map, no code
; Approximate match, approximate map, related match
; Exact match, exact map, equivalent match, equivalent
map, equal
;e International Organization for Standardization’s techni-
cal report illustrates a 1 to 5 rating scale to determine the de-
gree of equivalence. 3 For example, “no match or map” means
a concept exists in one of the coding systems without a similar
concept in the other system. In the rating scale, “ 1” represents
equivalent meaning, while “ 5” indicates that no map is possible
between the source and target.
