Development,implementation and evaluation of an information model for archetype based user responsive medical data visualization

BackgroundWhen medical data have been successfully recorded or exchanged between systems there appear a need to present the data consistently to ensure that it is clearly understood and interpreted. A standard based user interface can provide interoperability on the visual level.ObjectivesThe goal of this research was to develop, implement and evaluate an information model for building user interfaces for archetype based medical data.MethodsThe following types of knowledge were identified as important elements and were included in the information model: medical content related attributes, data type related attributes, user-related attributes, device-related attributes. In order to support flexible and efficient user interfaces an approach that represents different types of knowledge with different models separating the medical concept from a visual concept and interface realization was chosen. We evaluated the developed approach using Guideline for Good Evaluation Practice in Health Informatics (GEP-HI).ResultsWe developed a higher level information model to complement the ISO 13606 archetype model. This enabled the specification of the presentation properties at the moment of the archetypes’ definition. The model allows realizing different users’ perspectives on the data. The approach was implemented and evaluated within a functioning EHR system. The evaluation involved 30 patients of different age and IT experience and 5 doctors. One month of testing showed that the time required reading electronic health records decreased for both doctors (from average 310 to 220 s) and patients (from average 95 to 39 s). Users reported a high level of satisfaction and motivation to use the presented data visualization approach especially in comparison with their previous experience.ConclusionThe introduced information model allows separating medical knowledge and presentation knowledge. The additional presentation layer will enrich the graphical user interface’s flexibility and will allow an optimal presentation of medical data considering the different users’ perspectives and different media used for data presentation.