Browse by author
Lookup NU author(s): Dr Neil Jenkings, Professor Rob WilsonORCiD, Professor Ian Purves
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
The paper provides detailed descriptions of general practitioners (GPs') interactions, both with their computers and their patients, with the aim of facilitating the detailed understanding of how GPs use their computers while in consultation with patients. The focus is on the coordinated activities of the doctor and patient and the multitasking that is required during consultation. The data consists of primary care doctor-patient consultations for asthma and angina where clinical scenarios, supported by dummy electronic and paper records for use by the doctor, were played out. Although not 'naturally occurring', the mock scenario is a traditional medical training technique. Objective and methods: This paper describes and demonstrates a data transcription methodology, involving seven discrete levels of activities, developed to account for the intricate multitasking that occurs in a GP consultation. The transcription method, developed to support the evaluation of a prototype medical prescribing decision support system (Prodigy) for use by general practitioners in consultation with patients, builds on data description techniques from conversation analysis (CA) and video analysis (VA). Conclusions: It is suggested that the methodology described could also be applicable to other scenarios involving the observation of human-computer-human interaction. © 2005 Elsevier Ireland Ltd. All rights reserved.
Author(s): Gibson M, Jenkings KN, Wilson RG, Purves IN
Publication type: Article
Publication status: Published
Journal: International Journal of Medical Informatics
Year: 2005
Volume: 74
Issue: 6
Pages: 425-436
Print publication date: 01/07/2005
ISSN (print): 1386-5056
ISSN (electronic): 1872-8243
URL: http://dx.doi.org/10.1016/j.ijmedinf.2005.04.002
DOI: 10.1016/j.ijmedinf.2005.04.002
PubMed id: 15914080
Altmetrics provided by Altmetric
