Data integration between clinical research and patient care: A framework for context-depending data sharing and in silico predictions

• DOI: 10.1371/journal.pdig.0000140
• Publication Date: 2023-05-15T17:31:28Z
• Authors: Katja Hoffmann; Anne Pelz; Elena Karg; Andrea Gottschalk; Thomas Zerjatke; Silvio Schuster; Heiko Böhme; Ingmar Glauche; Ingo Roeder
• Keywords: Data Sharing

The transfer of new insights from basic or clinical research into routine is usually a lengthy and time-consuming process. Conversely, there are still many barriers to directly provide use data in the context research. In particular, no coherent software solution available that allows convenient immediate bidirectional between concrete treatment contexts settings. Here, we present generic framework integrates health (e.g., clinical, molecular) computational analytics model predictions, statistical evaluations, visualizations) which simultaneously supports both patient-specific healthcare decisions efforts, while also adhering requirements for protection quality. Specifically, our work based on recently established management concept, designed implemented web-based analysis, visualization as well computer simulation prediction with audit trail functionality regulation-compliant pseudonymization service. Within front-end application, two tailored views: (i.e., context) perspective focusing visualization, analysis outcome exploration pseudonymized data. We illustrate application by use-cases field haematology/oncology. Our implementation demonstrates feasibility an integrated generation backward propagation results predictions at individual patient level decision-making processes enabling seamless integration information system electronic record.