eHealth in Home Dialysis
Patients on home dialysis (HD) have higher quality of life, less risk comorbidities and improved outcomes. HD is also the most cost-effective
dialysis modality. Increasing home dialysis has however been difficult and slow, but eHealth could reduce barriers for home therapies and increase patient safety. The main study locale is Helsinki University Hospital (HUS). The study will apply for approval by the ethics committee of the HUS and all studies will operate under informed consent, as required by the committee. HUS will study how to improve the follow-up and measurements between clinical visits in predialysis and HD patients through novel physiological (e.g. blood pressure) and clinical measurement methods. Fluid volume status estimation will be improved by bioimpedance measurement, and patients´ physical activity and sleep will be studied. New PROMS for this patient groups will also be developed.The outcome will be new methods for patient follow-up at home. VTT will use their expertise of hybrid electronics for the development of a new, wearable, multi-parameter wireless sensor patch for biosignal analysis outside clinical settings for the monitoring HD patients. Helsinki University Social and Behavioral Science will investigate the current treatment pathway and identify to what extent it is in line with evidence on supporting self-management behaviors and uptake of HD. The proposed program will further study how additional psychosocial support can be applied to support patients in their care.
Qualitative methods, such as interviews and observational studies, will be combined with previously acquired quantitative data to reach the research goals. Aalto University Department of Computer Science studies the design of eHealth solutions for home care by involving both patients’ and clinicians’ perspectives. The study will utilize a range of human-centered design methods (e.g. co-design and usability evaluation). The aim is to contribute to the design and customization of eHealth solutions for improved user experience. Aalto University Department of Industrial Engineering and Management will use real world data from registries detailing resource consumption, clinical outcomes, reimbursements, costs and prices; and expert interviews to model and analyze clinical pathways and patient journeys. System dynamic models and simulations will be used to estimate cost-benefits and scale effects in various design solutions.
Collaborating in consortium
Helsinki University, Helsinki University Hospital
VTT Technical Research Centre of Finland
Aalto University the Department of Computer Science
Helsinki University Social and Behavioral Science
Aalto University Department of Industrial Engineering and Management
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