Browsing by Subject "Insight"

Electronic Health Records (ERH) data is one datatype that is continuously produced by hospitals all over the world. There is multiple different applications for this data; one of them is MIMIC dataset which applications are focused on machine learning, however, there is lack of visualisation of this dataset. Topic of this thesis is visualising ERH and more specifically the MIMIC dataset to help medical students gather insights into individual patient data. Considerations implementing this dataset to an individual patient visualisation are also examined. In thesis I first familiarized myself with interactive visualisation design principles with Munzners method. In the first stage I built a preliminary visualisation and gathered feedback with user inter- views. At the second stage I built a final visualisation and gathered final feedback and insights with user interviews. Visualisation consists of a dot graph for medication, line graph for patient response and table with diagnoses. The insights were analysed with Framework Method for qualitative data analysis. From the feedback for the visualisation and the insights gathered it is concluded that there are some issues that need to be taken in account when considering this dataset for individual patient visualisations. Insights from this visualisation were mostly factual and this type of visualisation seems to be slightly too challenging to medical students for more deep insights. Medication graph part of the final visualisation was seen as possible addition to current patient visualisations used in hospitals and the idea of using this visualisation as a teaching tool could only be considered with further additions and a different dataset.