title: Identifying logical clinical context clusters in nursing orders for the purpose of information retrieval.
abstract: Nurses information needs relate to nursing orders and nursing orders have many contexts including body systems, safety practices and other clinical categories. When searching for information related to orders one search term might retrieve documents related to multiple orders. We clustered nursing orders into sets that are related by the same logical clinical context. We then generated clusters and their search terms from a data set of 636 orders obtained from a CIS/CPOE system at an academic medical center. We refined those cluster search terms by searching an electronic nursing procedure manual to retrieve resources that could answer one of six generic nursing questions. Sixty-three cluster search terms were identified. The search terms for 100 (16%) of the orders were validated in a second hospitals electronic nursing procedure manual; precision was 32.5%.. Our process of identifying cluster search terms may be a useful method to obtain clinically relevant information resources.
authors.affiliation: Columbia University School of Nursing, New York, NY, USA.
authors.forename: Sarah
authors.initials: S
authors.lastname: Collins
authors.forename: Suzanne
authors.initials: S
authors.lastname: Bakken
authors.forename: James J
authors.initials: JJ
authors.lastname: Cimino
authors.forename: Leanne M
authors.initials: LM
authors.lastname: Currie
mesh_terms: D001185:Artificial Intelligence; D016000:Cluster Analysis; D004282:Documentation / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D009518:New York; D048108:Nursing Informatics / Q000379:methods*; D009736:Nursing Process / Q000145:classification* / Q000458:organization & administration*; D009737:Nursing Records; D010363:Pattern Recognition, Automated / Q000379:methods*