You can toggle between the regular table listing for the search results or our new tree search results (button on right hand side of screen). When you are in tree search mode, the search results are displayed in the context of their hierarchy, which can help you see the relevant tests in an order. Here’s a screenshot of a search for “thyroid bld” in its tree context:

Regenstrief Institute analyzed data from the regional health information exchange called the Indiana Network for Patient Care (INPC) and derived a list of LOINC codes that comprise 99.8% of the laboratory tests that were performed.  The full results of this analysis are presented in a paper published in the AMIA 2007 Proceedings.

Within RELMA, we created a new search restriction called "Common tests 99.+ %tile". When this search restriction is enforced the search results will only contain LOINC codes that are members of this empirically derived common test list.

The Intelligent Mapper (IM), is an automated tool within RELMA for producing a ranked list of candidate LOINC terms for each local term in a submission file. IM identifies candidate LOINC codes by counting the number of matches between words in the local term name and words (or synonyms) in the formal LOINC term names. Before doing the matching, it expands the words in the local term name into a tree of synonyms. For example, “CHEST MRA” becomes “CHEST, (MRI ANGIO, MRA).” IM counts exact-string word matches for all possible combinations of words and synonyms (e.g., “CHEST, MRI ANGIO” and “CHEST, MRA” are counted separately), and then uses the best count as the first part of its match score. IM ranks the candidate LOINC terms for relevance first by the number of words matched (the more the better), and second on the total number of words in the LOINC term (the fewer the better). If no words in the local term match to any in LOINC, IM does not return any candidate terms.