title: A framework for analyzing the cognitive complexity of computer-assisted clinical ordering.
abstract: Computer-assisted provider order entry is a technology that is designed to expedite medical ordering and to reduce the frequency of preventable errors. This paper presents a multifaceted cognitive methodology for the characterization of cognitive demands of a medical information system. Our investigation was informed by the distributed resources (DR) model, a novel approach designed to describe the dimensions of user interfaces that introduce unnecessary cognitive complexity. This method evaluates the relative distribution of external (system) and internal (user) representations embodied in system interaction. We conducted an expert walkthrough evaluation of a commercial order entry system, followed by a simulated clinical ordering task performed by seven clinicians. The DR model was employed to explain variation in user performance and to characterize the relationship of resource distribution and ordering errors. The analysis revealed that the configuration of resources in this ordering application placed unnecessarily heavy cognitive demands on the user, especially on those who lacked a robust conceptual model of the system. The resources model also provided some insight into clinicians' interactive strategies and patterns of associated errors. Implications for user training and interface design based on the principles of human-computer interaction in the medical domain are discussed.
authors.affiliation: Laboratory of Decision Making and Cognition, Department of Biomedical Informatics, Columbia University, 622 West 168th Street, New York, NY 10032, USA. horsky@dbmi.columbia.edu
authors.forename: Jan
authors.initials: J
authors.lastname: Horsky
authors.forename: David R
authors.initials: DR
authors.lastname: Kaufman
authors.forename: Michael I
authors.initials: MI
authors.lastname: Oppenheim
authors.forename: Vimla L
authors.initials: VL
authors.lastname: Patel
mesh_terms: D003071:Cognition / Q000502:physiology*; D003628:Database Management Systems; D016208:Databases, Factual; D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D019300:Medical Errors / Q000517:prevention & control*; D016347:Medical Records Systems, Computerized; D010343:Patient Admission; D012986:Software Validation; D013223:Statistics as Topic / Q000379:methods; D013647:Task Performance and Analysis; D014584:User-Computer Interface