A critical impediment to taking full advantage of electronic health record (EHR) systems is the human computer interface (HCI). The project's core aim is to design, implement, and evaluate several new HCI features for clinical decision support (CDS) systems that have the potential for directly impacting point-of-care treatment and improving care for patients suffering from long-term illness. Some of the primary HCI features proposed include: 1) Visually enhanced interactive functions for EHR systems such as treatment trend maps and data indicators, 2) Patient data summary of critical data elements in a dashboard format, 3) Access to evidence-based recommendations relevant to individual patients, and, 4) Display of co-morbid conditions explicitly to encourage review and analysis in the context of routine patient care. The proposed work will explore the use of visual analytics to process patient and comparative population medical profile data to generate data summaries in the form of interactive visualizations (data views). The data views will be designed to provide physicians with the capability to filter patient data based on key data elements such as medications and co-morbid conditions, and to compare patient treatment trends with established evidence-based guidelines to identify treatment gaps and options. As part of the usability evaluation, the proposed work will engage end-users (i.e., care providers) directly in requirement generation, implementation, evaluation, and refinement of the CDS HCI. The broad impact of the proposed work include disseminating the outcome and findings through the network of Clinical Translational Science Awardees (60 academic medical centers) that are involved in developing novel informatics solutions to accelerate the translation of medical treatments and prevention strategies. Additionally, the MindsEye software will be distributed with appropriate documentation to contribute to health IT education and training and to spur practical IT engagements and new research activities.
