title: Automated discovery of patient-specific clinician information needs using clinical information system log files.
abstract: Knowledge about users and their information needs can contribute to better user interface design and organization of information in clinical information systems. This can lead to quicker access to desired information, which may facilitate the decision-making process. Qualitative methods such as interviews, observations and surveys have been commonly used to gain an understanding of clinician information needs. We introduce clinical information system (CIS) log analysis as a method for identifying patient-specific information needs and CIS log mining as an automated technique for discovering such needs in CIS log files. We have applied this method to WebCIS (Web-based Clinical Information System) log files to discover patterns of usage. The results can be used to guide design and development of relevant clinical information systems. This paper discusses the motivation behind the development of this method, describes CIS log analysis and mining, presents preliminary results and summarizes how the results can be applied.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, NY, USA.
authors.forename: Elizabeth S
authors.initials: ES
authors.lastname: Chen
authors.forename: James J
authors.initials: JJ
authors.lastname: Cimino
mesh_terms: D019091:Critical Pathways; D003625:Data Collection; D020000:Decision Support Systems, Clinical; D001330:Electronic Data Processing; D006751:Hospital Information Systems; D006801:Humans; D016247:Information Storage and Retrieval; D020407:Internet; D016347:Medical Records Systems, Computerized; D014584:User-Computer Interface