Literature DB >> 11418545

Derivation and evaluation of a document-naming nomenclature.

S H Brown1, M Lincoln, S Hardenbrook, O N Petukhova, S T Rosenbloom, P Carpenter, P Elkin.   

Abstract

OBJECTIVE: The Computerized Patient Record System is deployed at all 173 Veterans Affairs (VA) medical centers. Providers access clinical notes in the system from a note title menu. Following its implementation at the Nashville VA Medical Center, users expressed dissatisfaction with the time required find notes among hundreds of irregularly structured titles. The authors' objective was to develop a document-naming nomenclature (DNN) that creates informative, structured note titles that improve information access.
DESIGN: One thousand ninety-four unique note titles from two VA medical centers were reviewed. A note-naming nomenclature and compositional syntax were derived. Compositional order was determined by user preference survey. MEASUREMENTS: The DNN was evaluated by modeling note titles from the Salt Lake City VA Medical Center (n=877), Vanderbilt University Medical Center (n=554), and the Mayo Clinic (n=42). A preliminary usability evaluation was conducted on a structured title display and sorting application.
RESULTS: Classes of note title components were found by inspection. Components describe characteristics of the author, the health care event, and the organizational unit providing care. Terms were taken from VA medical center information systems and national standards. The DNN model accurately described 97 to 99 percent of note titles from the test sites. The DNN term coverage varied, depending on component and site. Users found the DNN title format useful and the DNN-based title sorting and note review application easy to learn and quick to use.
CONCLUSION: The DNN accurately models note titles at five medical centers. Preliminary usability data indicate that DNN integration with title parsing and sorting software enhances information access.

Entities:  

Mesh:

Year:  2001        PMID: 11418545      PMCID: PMC130083          DOI: 10.1136/jamia.2001.0080379

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


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  16 in total

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Authors:  Thomas H Payne; Barak Gaster; Durline Mineer; Jim Mazurk; Nancy Dunnington; Jacquie Zehner; Bill Lober; Erik Van Eaton; Wayne McCormick
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  Experience in implementing inpatient clinical note capture via a provider order entry system.

Authors:  S Trent Rosenbloom; Jonathan Grande; Antoine Geissbuhler; Randolph A Miller
Journal:  J Am Med Inform Assoc       Date:  2004-04-02       Impact factor: 4.497

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Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

4.  Evolution and use of a note classification scheme in an electronic medical record.

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5.  Document ontology: supporting narrative documents in electronic health records.

Authors:  Jason S Shapiro; Suzanne Bakken; Sookyung Hyun; Genevieve B Melton; Cara Schlegel; Stephen B Johnson
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6.  Managing the life cycle of electronic clinical documents.

Authors:  Thomas H Payne; Gail Graham
Journal:  J Am Med Inform Assoc       Date:  2006-04-18       Impact factor: 4.497

7.  LOINC codes for hospital information systems documents: a case study.

Authors:  Martin Dugas; Sylvia Thun; Thomas Frankewitsch; Kai U Heitmann
Journal:  J Am Med Inform Assoc       Date:  2009-03-04       Impact factor: 4.497

8.  Standardizing Clinical Document Names Using the HL7/LOINC Document Ontology and LOINC Codes.

Authors:  Elizabeth S Chen; Genevieve B Melton; Mark E Engelstad; Indra Neil Sarkar
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

9.  Survey-based naming conventions for use in OBO Foundry ontology development.

Authors:  Daniel Schober; Barry Smith; Suzanna E Lewis; Waclaw Kusnierczyk; Jane Lomax; Chris Mungall; Chris F Taylor; Philippe Rocca-Serra; Susanna-Assunta Sansone
Journal:  BMC Bioinformatics       Date:  2009-04-27       Impact factor: 3.169

10.  Developing a manually annotated clinical document corpus to identify phenotypic information for inflammatory bowel disease.

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Journal:  BMC Bioinformatics       Date:  2009-09-17       Impact factor: 3.169

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