We have finished mapping top 35 document types to LOINC (CDO).
Here are some discussion items.
I would like to hear response from LOINC users and creators.
The studied IDR document types are described by two internal codes: document class (e.g., pathology report or radiology interpretation) and document subclass (e.g., GYN cytopathology report or chest radiograph). For lifetime EHR data spanning from 1985 to 2009, 35 document types accounted for 80% of all reports and 311 document types accounted for 99% of all reports (retired document types were included). Within the subset of 35 most frequent document types, CDO’s fully corresponding terms were indentified for 24 (69%) of them. For 7 types (20%), only a higher-granularity term was identified, and for 4 types (11%), there was no CDO’s concept found.
For example, the CDO had a code for “Prescription for durable medical equipment” (52063-5), but lacked a code for MC’s subclass of “Prescription note”. Or, CDO had 3 codes for consent for abortion, sterilization and hysterectomy (52027-0,52029-6,52028-8), but lacked a less granular code for MC’s document subclass “Consent Form (Outpatient Administrative Doc)”. In another example, MC’s document subclass “Psychiatric Telephone Note” had to be mapped to a generic telephone encounter note despite existence of psychiatry specific concepts for counseling note, consultation note, evaluation and management note and group counseling note)
The studied data contained 1323 distinct document subclasses (CDO has 528 concepts). Within the subset of 35 most frequent types, 8 subclasses mapped a set of 3 CDO codes (51852-2 Letter,34748-4 Telephone encounter note, 47045-0 Study report).
Our result of 69% full-correspondence coverage of LOINC is lower then Hyun’s results . The review of non-covered terms indicates that CDO seems to be more complete for inpatient documents (for example we did not find adequately granular concept for “Well Child Visit” document type).
1. Hyun S, Shapiro JS, Melton G, Schlegel C, Stetson PD, Johnson SB, et al. Iterative evaluation of the HL7-LOINC Document Ontology for representing clinical document names: a case report. J Am Med Inform Assoc 2009;16(3):395-9.