The Congenital Cardiology Cloud - optimizing long-term care by connecting ambulatory and hospital medical attendance via telemedicine.

BACKGROUND: Patients with complex congenital heart disease frequently undergo a life-long ambulatory therapy with the need for repeated hospital interventions. To optimize this manifold interplay, we designed and implemented a tele-medical service, the Congenital Cardiology Cloud (CCC). This study aims to analyse the requirements for its implementation through the comprehensive assessment of design, installation and impact on patient´s care. METHODS: CCC's development comprised the analysis of historically raised admission and discharge management and the definition of technical and organizational requirements. Elaboration of procedural flow charts, description of data formats and technical processes as well as distribution of patient structure formed part of this process. RESULTS: Analysis of existing workflows uncovered a need for the rebuilding of admission and discharge process and decision making for further treatment. The CCC reduces conference-meetings in general and repetitive meetings up to less than a third. Real-time dispatch of discharge documents guarantees an instantaneous access to patient-related data. Comparative analyses show a more complex patient group to be involved in tele-medical services. CONCLUSIONS: The CCC enables the sharing of complex clinical information by overcoming sectoral barriers and improves mutual patient advice. Implementation of a tele-medical network requires willingness, perseverance and professional engagement. Future application analysis and possible introduction of refinancing concepts will show its long-term feasibility.

LinSets.zip: Compressing Linear Set Diagrams.

Linear diagrams are used to visualize set systems by depicting set memberships as horizontal line segments in a matrix, where each set is represented as a row and each element as a column. Each such line segment of a set is shown in a contiguous horizontal range of cells of the matrix indicating that the corresponding elements in the columns belong to the set. As each set occupies its own row in the matrix, the total height of the resulting visualization is as large as the number of sets in the instance. Such a linear diagram can be visually sparse and intersecting sets containing the same element might be represented by distant rows. To alleviate such undesirable effects, we present LinSets.zip, a new approach that achieves a more space-efficient representation of linear diagrams. First, we minimize the total number of gaps in the horizontal segments by reordering columns, a criterion that has been shown to increase readability in linear diagrams. The main difference of LinSets.zip to linear diagrams is that multiple non-intersecting sets can be positioned in the same row of the matrix. Furthermore, we present several different rendering variations for a matrix-based representation that utilize the proposed row compression. We implemented the different steps of our approach in a visualization pipeline using integer-linear programming, and suitable heuristics aiming at sufficiently fast computations in practice. We conducted both a quantitative evaluation and a small-scale user experiment to compare the effects of compressing linear diagrams.