Toward a National Health Information Infrastructure: A Key Strategy for Improving Quality in Long-Term Care. E. Coding Procedures

05/01/2003

Terms from the ACOVE indicators, the domain experts, and the MDS data elements were entered into a spreadsheet, one element per row. As described above, each phrase within the MDS was considered a discrete data element for the purpose of the content coverage study, whether the phrase existed as a section header, item, or response option. Terms were then classified as administrative information, resident history, assessments, treatments, or other (terms referring to provider information, quantities (e.g., 1 to 500 cc/day) and miscellaneous activities) in order to facilitate analysis.

The terminology coding systems were imported into a database within the Mayo terminology services. This set of services is a compendium of tools that facilitate terminology indexing. There are two main divisions within the set of tools, corresponding to the server side and the client side. On the server side, there is a suite of terminology services that contain the core mechanisms for serving up and storing coded content. On the client side, there are graphical building blocks for searching and navigating the hierarchy of underlying terminologies, and for building complex coded expression if supported by the terminology system. Included within the Mayo terminology server is a basic spell checking service, a lexical variant generator (LVG), a synonym scheme, and a coding scheme service. Originally developed to support SNOMED RT, this suite of tools can be modified to accommodate other terminology coding systems.

A trained and experienced coder exhaustively searched for the best available concept or set of concepts that captured the clinical notions expressed by the target phrase from the ACOVE indicators, domain experts, and MDS. If no reasonable match was suggested by the coding tool, she further searched for matching terms from the terminology coding systems using common word processing techniques such as "find" functions. Results are presented in the next section of this paper.


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