ABSTRACT
OBJECTIVE: Create an interoperable set of nursing flowsheet assessment measures within military treatment facility electronic health records using the 3M Healthcare Data Dictionary (HDD). DESIGN: The project comprised three phases: 1) discovery included an in-depth analysis of the Essentris data to be mapped in the HDD; 2) mapping encompassed the creation of standard operating procedures, mapping heuristics, and the development of mapping tools; and 3) quality assurance incorporated validation of mappings using inter-rater agreement. RESULTS: Of 569,073 flowsheet concepts, 92% were mapped to the HDD. Of these, 31.5% represented LOINC concepts, 15% represented SNOMED CT and 1% represented both. 52.5% were mapped to HDD concepts with no standardized terminology representations. CONCLUSIONS: Nursing flowsheet data can be mapped to standard terminologies but there is not the breadth of coverage necessary to represent nursing assessments. Future work is necessary to develop a standard information model for the nursing process.
Subject(s)
Military Facilities , Nursing Assessment/standards , Nursing Records/standards , Vocabulary, Controlled , Hospitals, Military , Humans , Logical Observation Identifiers Names and Codes , Nursing Assessment/classification , Nursing Records/classification , Systematized Nomenclature of Medicine , United StatesABSTRACT
Hybrid text matching algorithms similar to those used for DNA sequencing were developed by 3M Health Information Systems to map a noisy legacy codeset to the 3M Healthcare Data Dictionary (3M HDD). Applying these techniques to map other biomedical vocabularies was briefly introduced in an earlier paper describing the algorithms. We now present results from successfully utilizing them to map different vocabularies across multiple biomedical domains, proving their generalizability.
Subject(s)
Algorithms , Natural Language Processing , Vocabulary, Controlled , Systematized Nomenclature of Medicine , Unified Medical Language SystemABSTRACT
Use of R-Mix Fresh Cells has been shown to be a rapid and sensitive method for the detection and identification of respiratory viruses. We prospectively evaluated the impact of incorporation of R-Mix shell vials on the sensitivity and time to detection of seven respiratory viruses recovered in a comprehensive culture during the course of an entire respiratory season in a high-volume clinical laboratory. In this study, R-Mix shell vials were used as part of the culture of 3803 respiratory specimens. A total of 428 respiratory viruses were recovered. Staining of R-Mix vials after overnight incubation allowed initial detection of 274 of 279 influenza viruses, 33 of 38 parainfluenza viruses, 35 of 51 adenoviruses, and 52 of 60 respiratory syncytial viruses (RSVs). The time to reporting of all positive cultures after in-lab specimen receipt was 2.9 days on average and those initially detected in R-Mix cells were reported in 2.3 days on average. A combination of direct fluorescent-antibody (DFA) staining and virus culture was performed on a subset of 711 respiratory specimens. Of 152 viruses identified, 57 were observed only with DFA testing (55 RSV and 2 influenza A viruses) and 31 were recovered only in cell culture. After overnight incubation, R-Mix cells detected 87.1% of respiratory viruses not observed by DFA testing and 96.9% of viruses positive by both methods. The sensitivities of DFA testing and R-Mix cells for identification of influenza viruses were 70.5% and 96.7%, respectively. The R-Mix method detected influenza virus in 18 samples that were negative by DFA testing.