From smartphone supported Citizen Health Science to Cooperative Citizen Test Lab

Trine Rolighed Thomsen, Ulrik Bak Kirk, Frederik Mølgaard Thaysen, Carsten Obel

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceabstrakt i proceedingForskningpeer review

Abstrakt

The wide dissemination of smartphones provides new opportunities for Citizen Health Science, based on citizen
value creation of P4 Health (Participatory, Preventive, Predictive and Personalized). In the best case this may
lead to better prediction and prevention of diseases and personalised support and treatment of citizen and
patient to great clinical benefit and cost reduction. However, there is at the same time a risk of ‘O4 medicine’
(overtesting, overdiagnosis, overtreatment, overcharging). In this workshop we contribute with our experiences
from three projects that aim to bridge personal health and population health by combining 24/7 data from
smartphones with other kinds of health data:
HealthD360 - Health data that creates value for the citizen
In HealthD360 we investigate the possibilities for creating better health for the citizens by gathering data from
the public healthcare system and linking them with data from the citizens' smartphones and wearables. The
ambition is to promote more personal, secure, and coherent treatment in collaboration with patients and
healthcare professionals.
We will share experiences with developing solutions to monitor diabetic foot ulcers and to support mental health
in schoolchildren.
FEMaLe – Finding Endometriosis using Machine Learning
The EU-funded FEMaLe project is working on a machine-learning multi-omics platform that can analyse omics
data sets and feed the information into a personalised predictive model. The focus of the project is to improve
intervention for individuals with endometriosis, a condition where tissue normally lining the uterus grows outside
the uterus. A combination of tools, such as a mobile application and augmented reality surgery software, will be
co-created, facilitating improved disease management and the delivery of precision medicine.
We will share experiences with co-creating a consensus study survey as well as the Lucy Application, which is
your personal gynecological virtual assistant, helping to take care of your female health.
CoronaLytics: A 360 degree mobile/wearable data household approach to guide shared precision health and
decision-making during the COVID-19 epidemic
In the research project CoronaLytics citizen could contribute to with personal data gathered on a smartphone.
Both automatic data collection of activity and heartrate data and data bases on questionnaires was used. The
project worked with the citizen perspective and focused on daily impact on everyday life during the pandemic.
We will share our gained experiences in how to engage patients and citizens in the design, development, and
implementation processes.
Workshop focus
Based on these experiences and those of the workshop participants, we will discuss how governance, design
and analytic methods can support the development of the citizen health science concept to secure citizen value
creation of P4 Health. We will discuss the idea of a cooperative governance model to secure data solidarity. And
how Citizen Health Science in combination with Denmark's unique potential can secure a democratic health
model, where the partnership between citizens and researchers forms a population test lab. This may be the
framework for the next generation of population-based research, including development and testing of personal
health solutions based on motivated consent and participation from Danish citizens.
OriginalsprogEngelsk
TitelEngaging Citizen Science Conference 2022 Booklet
Publikationsdato25 apr. 2022
StatusUdgivet - 25 apr. 2022
BegivenhedEngaging Citizen Science Conference 2022 - Aarhus Universitet, Aarhus, Danmark
Varighed: 25 apr. 202226 apr. 2022

Konference

KonferenceEngaging Citizen Science Conference 2022
LokationAarhus Universitet
Land/OmrådeDanmark
ByAarhus
Periode25/04/202226/04/2022

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