A new white paper from AHIMA, “Data Mapping and Its Impact on Data Integrity,” offers recommendations to help users think through the risks and unintended consequences of data map use before any projects are planned.

Written by a team of AHIMA volunteers and staff, the paper provides guidance to avoid adverse outcomes involving the use of maps, including tips for map maintenance, mapping process and tools affecting data integrity, and best practices to avoid data mapping errors.

The authors note that “Information management projects are data-centric projects. Data mapping requires knowledge of information technology, the data sets being mapped, and project management, which often requires a diverse team approach. Health information management (HIM) professionals are frequently involved in planning and developing data maps that utilize code sets, as there is a need for competency in both the source and target systems involved in the mapping projects. The source is the origin of the map or the data set from which one is mapping.”

The paper states that “the increased demands for data sharing and interoperability, especially across different practice settings and classification systems, increase reliance on data mapping tools and techniques.” But it’s important for those who use data maps to understand their role and context, as well as their strengths and weaknesses, to ensure the reliability of the data the maps provide.

The increase in data mapping projects “is the result of the need to link disparate electronic data systems in a rapidly changing environment,” the paper says. “Mapping projects are valuable in a variety of situations where data elements from one code or data set are compared to another set and evaluated for equivalence of meaning.”

The paper identifies examples of data integrity involving data mapping, where due diligence is required:

  • Trustworthiness of mapped information over its life cycle and use
  • Integrity is accomplished by validation and regular “checkups” of the data flow and map performance
  • Mapped entries reflect current content through the entire workflow, consistent with the use case for the map
  • The intended content of a validated map is maintained, in case the mapped data structure changes through data processing

 

The white paper also identifies issues inherent in electronic workflows that can present challenges to data integrity, such as drop-down pick lists for recording clinical facts generated from maps, computer-assisted encoding software automation that submits codes that misrepresent the facts of the encounter, and maps that are not consistently updated when the systems on which they are based change.

To optimize the use of data maps, the white paper recommends the following best practices:

  • Document the map heuristics and standing business rules surrounding the development of each map, including use cases for each map, applications that would use the map, and documentation to explain how mapping rules are created and deployed
  • Create a program and process to test the validity and reproducibility of the map, from development to end-user testing and acceptance
  • Create and implement a maintenance program, as code sets used in a map may be subject to updates, discontinuation, or major version changes

 

Read the white paper at http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_050525.pdf.