Standardizing clinical laboratory data for secondary use

Abstract

Clinical databases provide a rich source of data for answering clinical research questions. However, the variables recorded in clinical data systems are often identified by local, idiosyncratic, and sometimes redundant and/or ambiguous names (or codes) rather than unique, well-organized codes from standard code systems. This reality discourages research use of such databases, because researchers must invest considerable time in cleaning up the data before they can ask their first research question. Researchers at MIT developed MIMIC-II, a nearly complete collection of clinical data about intensive care patients. Because its data are drawn from existing clinical systems, it has many of the problems described above. In collaboration with the MIT researchers, we have begun a process of cleaning up the data and mapping the variable names and codes to LOINC codes. Our first step, which we describe here, was to map all of the laboratory test observations to LOINC codes. We were able to map 87% of the unique laboratory tests that cover 94% of the total number of laboratory tests results. Of the 13% of tests that we could not map, nearly 60% were due to test names whose real meaning could not be discerned and 29% represented tests that were not yet included in the LOINC table. These results suggest that LOINC codes cover most of laboratory tests used in critical care. We have delivered this work to the MIMIC-II researchers, who have included it in their standard MIMIC-II database release so that researchers who use this database in the future will not have to do this work.

Figure 1

Depiction of the MIMIC-II database structure. Note the pairs of patient result and associated data dictionary tables on the left. Details from the d_labitems and labevents tables are shown on the right. The d_chartitems and chartevents pair of tables have an analogous structure.

Figure 2

The RELMA auto-mapper takes the available local test information and returns the best matches in LOINC. In this example, the local data was “Hgb” (test name), “blood” (the specimen), and “g/dL” (the units of measure). The table of likely LOINC matches illustrates the specificity of different parameters including units, method, specimen, and statistical rank. The red box indicates the best match in this example.