title: Word frequency analysis of dictated clinical data: a user-centered approach to the design of a structured data entry interface.
abstract: The design of a functional interface for direct entry of physical exam data by physicians remains a formidable challenge for developers of clinical information systems. Many developers use a theoretical approach, basing the interface on a model of the structure of the information and of the user-system interaction that is developed with one or more clinical domain expert(s). We explored the use of empirical analysis as a basis for the design of a structured data entry (SDE) interface. A collection of physical examination data from actual trauma patients, dictated by trauma surgeons, was used for the analysis. Using simple parsers written in Visual BASIC, we used word frequency analysis (WFA) and manual editing to identify the frequencies of unique terms used by physicians in recording 688 HEENT and 712 LUNG physical exams. A second-pass WFA was used to determine associated descriptive terms. A simple SDE interface was created based on the results of these analyses. The interface was then evaluated by assessing the extent to which the HEENT and LUNG segments of similar physical exams could be fully recorded using the empirically-based SDE interface. Using this interface, 68% of 200 trial HEENT exams, and 85% of 200 trial LUNG exams could be fully recorded. The interface was also considered helpful in recording substantial portions of the remainder of the exams. We believe that WFA can be a useful tool for finding empirical basis for SDE design.
authors.affiliation: Cornell University Medical College, USA.
authors.forename: C
authors.initials: C
authors.lastname: Kreis
authors.forename: P
authors.initials: P
authors.lastname: Gorman
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D016347:Medical Records Systems, Computerized; D008722:Methods; D010808:Physical Examination; D009626:Terminology as Topic; D014194:Traumatology; D014584:User-Computer Interface