Patient-specific, data-evidence-driven treatment pathways

Host Institution: Median

Department that hosts the PhD: Department of Quality and Innovation

Supervisors involved: Dr. Golenia, Dr. Schröter, Dr. Bongers

Project description

The goal of this project is to improve the quality of rehabilitation care by developing patient-specific data-driven treatment pathways. The key task is to develop a model to predict patient-specific, evidence-based treatment pathways by exploiting machine learning techniques. Employing machine learning techniques enables to show the interactions between different components affecting the outcome of a treatment, in line with a systems approach.

In the first phase of the project, retrospective analyses will be performed which aim at linking sociodemographic data, data on the therapy units delivered and outcome parameters to identify superior therapy combinations. Outcome parameters and sociodemographic data have been collected since the beginning of 2019, providing a solid database. Outcome parameter reliability and interactions between different parameters and the sociodemographic data will also be tested. Employing machine learning techniques will enable to show the interactions between different components affecting the outcome of a treatment, in line with a systems approach.

In the second phase the identified superior therapy combinations will be tested in prospective studies. The focus is on integrating the findings into everyday clinical practice in order to guarantee patients the best possible therapy tailored to their individual needs and therewith integrating the systems approach into medical practice. All of this aims at

answers the question of what the model is relating the outcome parameters with sociodemographic data so that the type and duration of the treatment for individual patients can be predicted at the beginning of the rehabilitation stay.

This innovative approach will strengthen rehabilitation care as a cost-reducing and quality-enhancing third pillar of the health care system in the supply chain alongside physicians in private practice and inpatient acute medicine.

About ESR13-Chiara Basaglia

I was born in Bolzano, Northern Italy, and I am currently living in Berlin, Germany. I completed both my BSc and MSc at the University of Verona, Italy, where I graduated in Medical Bioinformatics. My thesis was on the study of clustering and optimization algorithms to be applied on diffusion magnetic resonance imaging data coming from neural tissues to study brain connectivity in vivo. I am now working as an early stage researcher at Median headquarters, and my project seeks to strengthen the role of rehabilitation as the third pillar of the German healthcare system, alongside primary and secondary care, by quantifying the socioeconomic benefits of rehabilitation. By evaluating internal data from rehabilitation and follow-up care, the project aims to provide concrete evidence of the economic and social value of this service, thereby enhancing its recognition and support within society and the healthcare sector. 

During my free time I love reading historical books, training, hanging out with friends, discovering new spots and learning new things about East Asian culture. Especially in the summer you can find me scuba diving or playing beach volley.