Is the Health Level 7/LOINC document ontology adequate for representing nursing documents?
The use of nursing documents from different electronic health record (EHR) systems is challenging due to inconsistency in document naming across systems and institutions. Mapping each local document name to standard document ontology may enable health care professionals to navigate and retrieve documents efficiently for multiple purposes such as quality assurance, outcomes research or public health reporting. The purpose of this study was to evaluate the sufficiency of the Health Level 7 (HL7)/Logical Observation Identifiers, Names, and Codes (LOINC) document ontology for representing nursing document names. We collected 94 nursing document types from the Eclipsys Clinical Information System (CIS) and the Columbia Medical Entities Dictionary (MED) and mapped them to the components of the HL7/LOINC document ontology. Seventy-five (79.8%) nursing document names were completely represented and 19 (20.2%) document names were partially represented. In order for the HL7/LOINC document ontology to be of more use in implementing EHRs that support nursing documentation, Subject Matter Domain and Type of Service axes require extension and clarification.
Hyun
Sookyung
S
School of Nursing, Columbia University, New York, NY 10032, USA. sh2138@columbia.edu
Ventura
Rosemary
R
Johnson
Stephen B
SB
Bakken
Suzanne
S
D006801:Humans; D016347:Medical Records Systems, Computerized / Q000458:organization & administration / Q000592:standards*; D009732:Nursing Care