What's Digi-FrailCare?

"Digi-FrailCare” targets digitisation and the use of digitised health data to improve health services for older people at risk of or with frailty.  

Frailty refers to age-related physical debility; a complex condition characterised by a cumulative decline across multiple physiological systems and increasing vulnerability to adverse health outcomes and death. Sustainable health services for frail older people are highly needed. We aim to develop and pilot a machine learning based model aimed at detecting factors contributing to frailty at an early stage, and synthesise findings for recommendations on a local, national and international basis. Digi-FrailCare will use a holistic approach and implement new knowledge on the interplay between risk factors for deterioration in health and function, including oral health and nutrition, general health and disease, function, polypharmacy, and cognition. We will build multidimensional risk assessment and prediction models for frailty using health data from the HUNT studies. The multidisciplinary service will be implemented in Trondheim municipality. More system knowledge is required about which type of information is important and how technical solutions fit how health care personnel collaborate in providing coordinated, proactive care and effective services. Therefore, we will assess human and non-human actors' when implementing a digitized service, and which infrastructures, systems, and groups the implementation is dependent on. Results will be synthesised and recommendations for further implementation will be developed. The project will impact future multidisciplinary work models for frailty to improve health and function in older people, for the sake of improved and sustainable future health care services.  

Three PhDs and one postdoc will work together with an interdisciplinary supervision project team from three faculties and departments to tackle the grand challenges of frailty. This will be done on a medical (MH), a technical (IE), and a societal (HF) expertise level from the three respective PhDs and their faculty affiliation, with an interdisciplinary-focused postdoc to integrate the findings across disciplines. 

The project’s focus 

Digi-FrailCare” targets digitisation and the use of digitised health data to improve health services for older people at risk of or with frailty. Frailty refers to age-related physical debility; a complex condition characterised by a cumulative decline across multiple physiological systems and increasing vulnerability to adverse health outcomes and death. Sustainable health services for frail older people are highly needed.   

 Project aim and research questions 

The overall aim of the project is to develop and pilot a machine learning based multidisciplinary primary health care model for preventing frailty and adverse events in older people with frailty.  

Digi-FrailCare has four main research questions: 

1. What are the prevalence and characteristics of oral health problems and malnutrition in older adults, and what is the association between them?  

2. How can explainable and transparent machine learning methods be used to determine key features and predict the risk for falls, fall-related fractures, dependence in daily life, in citizens either with/or at risk of frailty?   

3. How are different humans-(e.g.  professionals, technical developers, decision-makers) and non-human actors (e.g.  infrastructures, systems) impacting the implementation of a digital service model, and what are the facilitators and barriers for interdisciplinary collaboration and successful implementation?  

4. Which factors are critical for a digital multidisciplinary service model in people with/or at risk of frailty? 

Workplan – at large

Digi-FrailCare will use a holistic approach and implement new knowledge on the interplay between risk factors for deterioration in health and function including oral health and nutrition, general health, disease and function, polypharmacy, and cognition. We will build multidimensional risk assessment and prediction models for frailty using health data from large epidemiological studies, including the HUNT studies, and will prepare them for implementation and validation in HP, and for use as real-time digital multidisciplinary tools. The multidisciplinary service will be implemented in Trondheim municipality. More system knowledge is required about which type of information is important and how technical solutions fit how health care personnel collaborate in providing coordinated, proactive care and effective services. Therefore, we will assess human and non-human actors' impact when implementing HP, and which infrastructures, systems, and groups the implementation is dependent on. Results will be synthesised and recommendations for further implementation will be developed. However, just introducing the system without also developing the services using the system may lead to merely a digitalising of an existing offline workflow without facilitating new and more sustainable ways of working. Thus, we approach this change rather as digitalisation, which also changes practices and users in the sociotechnical network.   

PhD 1: Oral health and nutrition	PhD 2: Artificial Intelligence for Understanding Health Risks in Elderly	PhD 3:
The project aims to investigate the oral health of the older adult (≥70 years) population in Norway. Additionally, it seeks to explore whether oral health in this population group is related to malnutrition, frailty, and mortality. To conduct this investigation, data from the HUNT 70+ (HUNT4) and HUNT AiT surveys will be utilized	The project aims to develop a method for detecting frailty using a range of medical data. Emphasis will be placed on the method's comprehensibility so that it can be used in real-life situations. The project will focus on the Norwegian population and will use the PROMs database.

Post dr. project 

Project aim: 

The project aims to synthesize the knowledge on the prevalence of oral health problems and nutritional status, risk factors for frailty and its progression, and health professional’s sociotechnical perspectives, and to develop and describe a cross disciplinary digital service model for detecting and intervening on risk of frailty in older persons. We will use individual health data from Helseplattformen to support development of the digital service model.