Project description
Big data aids in the transition from cancer patient to survivor
The transition from cancer patient to cancer survivor should be planned and coordinated to ensure patients receive high-quality, coordinated and personalised care. The EU-funded PERSIST project is developing a system that supports self-care and can identify outcomes that require professional intervention. Its system uses big data technology and novel analysis algorithms that can be easily integrated into electronic health records and other sources of clinical data. Overall, the project aims to improve the management, intervention and prevention strategies to reduce side effects and prevent secondary diseases. Its long-term goal is to reduce the socio-economic burden related to cancer survivors’ care by creating a dynamic decision support system and making maximum use of predictive models.
Objective
PERSIST aims at developing an open and interoperable ecosystem to improve the care of cancer survivors. The key results to be achieved by partners are: increased self-efficacy and satisfaction with care as well as reduced psychological stress for a better management of the consequences of the cancer treatment and the disease, resulting in an improvement in health and wellbeing and a faster integration into the labour market, where applicable, compared to usual care (KR1); increased effectiveness in cancer treatment and follow-up by providing prediction models from Big Data that will support decision-making and contribute to optimal treatment decisions with positive consequences in the QoL and the health status of survivors (KR2); and improved information and evidence to advance the efficacy of management, intervention and prevention policies/strategies in order to timely treat side effects and, if possible, avoid secondary diseases and fatal events. The long-term result will be to reduce the socio-economic burden related to cancer survivors’ care (KR3). The ecosystem proposed consists of a Big Data platform to be built on top of an open infrastructure from one of the partners and a mHealth application for patients. The main building blocks to be developed are a multimodal sensing network running on a smart phone that will collect relevant data regarding the wellbeing of the patient; predictive models from anonymised health data from thousands of breast and colorectal patients; and modules essential for the development of a decision support system, which will employ the predictive models mentioned. Furthermore, PERSIST will contribute to establish evidence on the use of liquid biopsy techniques to the follow-up of cancer patients treated with curative purposes. A pilot study involving 160 patients and 32 health care professionals will be decisive to establish a co-creation methodology ranging from the earlies phases of the project throughout its conclusion.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencescomputer and information sciencesdata sciencebig data
- medical and health sciencesclinical medicineoncology
- natural sciencesbiological sciencesecologyecosystems
- social scienceseconomics and businessbusiness and managementemployment
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
36214 VIGO
Spain