查看文章

Clinical registries are powerful tools for collecting uniform data longitudinally, thus making it possible to evaluate the outcome of patients affected by a specific pathology. In the context of total joint arthroplasty, registries serve also as post-market surveillance. Adoption of registries is a heavy burden for clinical settings in terms of resources and infrastructures. Excessive workload leads to incomplete data collection which undermines the effectiveness of a registry and consequently the workload needs to be optimised.

Starting from the use case of the Istituto Ortopedico Galeazzi, the time and personnel dedicated to the registry was estimated. Analysis of the data collected in the first years enabled us to propose a methodology for workload reduction. Different Machine Learning models were leveraged to predict patients with excellent satisfaction to reduce the number of assessments in their clinical …