Periodic Reporting for period 3 - LifeChamps (A Collective Intelligence Platform to Support Cancer Champions)
Okres sprawozdawczy: 2022-12-01 do 2023-11-30
The LifeChamps project aims to harness techniques for Big Data modelling, analysis, and aggregation under a novel context-aware data-intensive and large-scale analytics framework towards delivering an integrated, person-centered care solution for the QoL and frailty monitoring of older cancer survivors. The project addresses the underexplored understanding of the combined effect cancer and its treatment have on QoL and subsequently the frailty progression in older cancer survivors. LifeChamps aims to harness techniques for Big Data modelling, analysis, and aggregation under a novel context-aware data-intensive and large-scale analytics framework towards delivering an integrated, person-centered care solution for the QoL and frailty monitoring of older cancer survivors. The project addresses the underexplored understanding of the combined effect cancer and its treatment have on QoL and subsequently the frailty progression in older cancer survivors. Hence, with a focus on frailty in geriatric oncology, LifeChamps is designed to answer the particular needs of high quality and independent living, where integration with a personalised care pathway for long-term adjustment and health care management is essential. To achieve this objective, LifeChamps integrates ground-breaking technologies in Big Data, trustworthy AI and digital biomarkers towards delivering a smart, personalised, and secure platform that monitors health related outcomes and addresses comorbidities of cancer champions by preventing long-term effects and improving QoL.
LifeChamps digital care solution integrated and combined different data sources into computational models that provide objective evaluation of QoL in older cancer survivors. Results on correlation analysis between digital and clinical endpoints have been performed, suggesting the clinical utility that digital biomarkers might have in the monitoring of older cancer survivors.
LifeChamps aimed to create a Big Data structure composed of a data framework based on the real-time collection and processing of streaming and batch data. Main functionalities, include support of heterogeneous and multimodal data streams, handling batch/offline data loading and performance of real-time analytics and pre-processing.
LifeChamps also delivers intelligent tools for frailty monitoring and condition self-management through the mobile application, offering personalized support to patients, while continually collecting PROMs and monitoring health-related information. Simultaneously, the LifeChamps Dashboard provides healthcare professionals with a way to monitor patient progress, enabling qualitative and quantitative assessments of patients' well-being over time.
Data collection and feasibility pilots ran in Greece, Spain, Sweden and the UK, involving 148 cancer survivors after initial treatment using LifeChamps for a period of 3 months and 36 healthcare professionals. The data collection pilot ran in Greece and Sweden, with 27 patients, while the feasibility study ran in all sites with 121 cancer survivors. Overall, the study demonstrated strong participant engagement with 6.6% dropout rate and high satisfaction, acceptance and good usability. Also, the study data was used to validate the predictive models for frailty and psychological symptoms.
In terms of scientific dissemination and exploitation, LifeChamps had 15 announcements in international conferences and 12 publications in peer-reviewed journals, 9 marketable components, 22 Key Exploitable Results and 1 patent filed. Finally, LifeChamps has been recognised by the Digital Health Uptake as a best practice in the context of frailty management.
LifeChamps aimed to create a Big Data structure composed of a data framework based on the real-time collection and processing of streaming and batch data. Main functionalities, include support of heterogeneous and multimodal data streams, handling batch/offline data loading and performance of real-time analytics and pre-processing.
LifeChamps also delivers intelligent tools for frailty monitoring and condition self-management through the mobile application, offering personalized support to patients, while continually collecting PROMs and monitoring health-related information. Simultaneously, the LifeChamps Dashboard provides healthcare professionals with a way to monitor patient progress, enabling qualitative and quantitative assessments of patients' well-being over time.
Data collection and feasibility pilots ran in Greece, Spain, Sweden and the UK, involving 148 cancer survivors after initial treatment using LifeChamps for a period of 3 months and 36 healthcare professionals. The data collection pilot ran in Greece and Sweden, with 27 patients, while the feasibility study ran in all sites with 121 cancer survivors. Overall, the study demonstrated strong participant engagement with 6.6% dropout rate and high satisfaction, acceptance and good usability. Also, the study data was used to validate the predictive models for frailty and psychological symptoms.
In terms of scientific dissemination and exploitation, LifeChamps had 15 announcements in international conferences and 12 publications in peer-reviewed journals, 9 marketable components, 22 Key Exploitable Results and 1 patent filed. Finally, LifeChamps has been recognised by the Digital Health Uptake as a best practice in the context of frailty management.
LifeChamps strategic impact aspires to produce novel insights into frailty for older patients with cancer, aimed at QoL improvement after cancer treatment. Towards this end, expert knowledge has been integrated in the development of the LifeChamps solution. A list of Patient Reported Outcome Measures (PROMs) considering geriatric cancer patients and survivors’ needs have been documented and prioritized for integration within the LifeChamps mobile application. Relevant frailty prediction models and QoL digital biomarkers have been conceptualized, developed and validated utilizing heterogeneous information coming from EHRs and novel sources of data. As a societal impact, LifeChamps aims to improve the care provided to older cancer survivors by means of introducing a person-centered care model with the integration of patient-generated data. This holistic overview of patients’ experience can help healthcare professionals to better understand and address the unique needs of older cancer patients, which can ultimately lead to more effective treatment, care, and well-being. Ultimately, LifeChamps aspires to minimize equal opportunities for research participation by providing voice to more than 300 older cancer survivors around EU to shape a more inclusive cancer research agenda for the next years.
In terms of innovation impact, several technical innovations have been identified:
• Digital Biomarkers: TV usage time (measured through a smart plug) was validated as a possible predictor of the risk of anxiety or depression
• Edge Analytics Engine: The Edge Analytics Engine (EAE) is a component that supports the real time analysis of multimodal sensor data on the edge, which supports the collection of data coming from all type of sensors. The main rationale is to provide computational capabilities close to the patient with a view to benefiting from location-awareness, low latency and reduced network usage
• Clinical predictive models for risk of frailty and computer-aided monitoring system: The clinical predictive model for identification of early frailty risk is the first of its kind that utilizes multimodal real-world data for the geriatric cancer survivors
• Dashboard – cohort level monitoring: The LifeChamps Dashboard includes an exploratory analytical Interactive Process Mining tool with clinical relevance for healthcare professionals monitoring cancer patients' care processes. The tool includes results in the form of Interactive Process Indicators (IPIs) as advanced views representing current processes, allowing their analysis by HCPs
• mHealth solution for cancer survivor self-management and empowerment: Using the Adhera® Health platform educational and lifestyle support is provided to patients. The platform combines an AI-based health recommender system that offers interventions and personalized recommendations that help a person develop skills to better self-manage their condition and improve their lifestyle
• RPI based Edge platform: A GitOps based Edge platform capable of headless deployment at patients' home while different components/software can be developed and deployed remotely by different vendors. In this architecture, each Edge device has its own remote container orchestration mechanism. The applications can be deployed and updated over-the-air, by utilizing Git Operation triggers (GitOps) and a CI/CD pipeline, that, combined, allow for different (canary) deployments in different environments. For this technical component, a patent application has been filed.
• Multi-resident indoor activity monitoring (LOCs gateway): The original functionality of the LOCs System has been extended to include the identification of individuals in multi-resident residents.
In terms of innovation impact, several technical innovations have been identified:
• Digital Biomarkers: TV usage time (measured through a smart plug) was validated as a possible predictor of the risk of anxiety or depression
• Edge Analytics Engine: The Edge Analytics Engine (EAE) is a component that supports the real time analysis of multimodal sensor data on the edge, which supports the collection of data coming from all type of sensors. The main rationale is to provide computational capabilities close to the patient with a view to benefiting from location-awareness, low latency and reduced network usage
• Clinical predictive models for risk of frailty and computer-aided monitoring system: The clinical predictive model for identification of early frailty risk is the first of its kind that utilizes multimodal real-world data for the geriatric cancer survivors
• Dashboard – cohort level monitoring: The LifeChamps Dashboard includes an exploratory analytical Interactive Process Mining tool with clinical relevance for healthcare professionals monitoring cancer patients' care processes. The tool includes results in the form of Interactive Process Indicators (IPIs) as advanced views representing current processes, allowing their analysis by HCPs
• mHealth solution for cancer survivor self-management and empowerment: Using the Adhera® Health platform educational and lifestyle support is provided to patients. The platform combines an AI-based health recommender system that offers interventions and personalized recommendations that help a person develop skills to better self-manage their condition and improve their lifestyle
• RPI based Edge platform: A GitOps based Edge platform capable of headless deployment at patients' home while different components/software can be developed and deployed remotely by different vendors. In this architecture, each Edge device has its own remote container orchestration mechanism. The applications can be deployed and updated over-the-air, by utilizing Git Operation triggers (GitOps) and a CI/CD pipeline, that, combined, allow for different (canary) deployments in different environments. For this technical component, a patent application has been filed.
• Multi-resident indoor activity monitoring (LOCs gateway): The original functionality of the LOCs System has been extended to include the identification of individuals in multi-resident residents.