Digital Infrastructure for Robust and Scalable Patient Monitoring in Pandemic Response Situations

  • Funded by Research Council of Norway (RCN)
  • Total publications:0 publications

Grant number: unknown

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Key facts

  • Disease

  • Start & end year

  • Known Financial Commitments (USD)

  • Funder

    Research Council of Norway (RCN)
  • Principle Investigator

  • Research Location

    Norway, Europe
  • Lead Research Institution

    University of Agder
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Supportive care, processes of care and management

  • Special Interest Tags


  • Study Subject


  • Clinical Trial Details


  • Broad Policy Alignment


  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable


A digital solution for home-monitoring of patients with suspected COVID-19 has been operational since March 19th in the region of Agder. Patients' self-reporting of symptoms are transferred to clinicians who follow up the progression of the disease. This is made possible by leveraging the existing platform for digital home monitoring of patients with chronic diseases. However, the situation of a pandemic poses certain novel demands to the solution. Our overall research question ("which novel capabilities are required when designing home-monitoring services for forward triaging and remote care in a pandemic usage situation?") will be answered through both evaluative and exploratory research. A systematic evaluation of the current home monitoring solutions and services will be conducted in order to provide quality assurance and identify areas for improvement. A digitally integrated service across the organizational levels will be designed. Further, digital home monitoring allows systematic capture of unique, patient-reported, early-phase disease data. We propose to systematically capture these data for both short-term optimization of the response to the pandemic, to create a data resource for research oriented towards knowledge building, e.g. on long-term health outcomes. This unique data source will also be a crucial resource for the project's further ambitions: to explore the possibility to strengthen monitoring with e.g. predictive models, assistive intelligence and AI-enabled automation. We will explore the potential for innovation and improvement of the underlying ICT platform, to be able to accommodate third-party solutions and for the platform to be scalable and flexible. Such third-party solutions are e.g. new data sources (from other monitoring technologies such as IoT devices and wearables), and solutions that support analysis. The potential for AI-assisted monitoring and diagnostic tasks will be explored in co-operation with the industry.