User Modeling of Disabled Persons for Generating Instructions to Medical First Responders
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Methodological Review: The Technology Acceptance Model: Its past and its future in health care
Journal of Biomedical Informatics
Personalized emergency medical assistance for disabled people
User Modeling and User-Adapted Interaction
Implementing an Integrative Multi-agent Clinical Decision Support System with Open Source Software
Journal of Medical Systems
A systematic analysis of medical decisions: how to store knowledge and experience in decision tables
KR4HC'11 Proceedings of the 3rd international conference on Knowledge Representation for Health-Care
Journal of Biomedical Informatics
Commentary: Clinical decision support: Converging toward an integrated architecture
Journal of Biomedical Informatics
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Objective: Computer-based clinical decision support systems (CDSSs) vary greatly in design and function. Using a taxonomy that we had previously developed, we describe the characteristics of CDSSs reported in the literature. Methods: We searched PubMed and the Cochrane Library for randomized controlled trials (RCTs) published in English between 1998 and 2003 that evaluated CDSSs. We coded each CDSS using our taxonomy. Results: 58 studies met our inclusion criteria. The 74 reported CDSSs varied greatly in context of use, knowledge and data sources, nature of decision support offered, information delivery, and workflow impact. Two distinct subsets of CDSSs were seen: patient-directed systems that provided decision support for preventive care or health-related behaviors via mail or phone (38% of systems), and inpatient systems targeting clinicians with online decision support and direct online execution of the recommendations (18%). 84% of the CDSSs required extra staffing for handling CDSS-related input or output. Conclusion: Reported CDSSs are heterogeneous along many dimensions. Caution should be taken in generalizing the results of CDSS RCTs to different clinical or workflow settings.