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H2020-SC1-DTH-01-2019 - Catalan non-profit organization is looking for partners with expertise in software development and data analysis in the health sector, national and regional health services institutions and oncological hospitals

Country of Origin: Spain
Reference Number: RDES20190111001
Publication Date: 11 January 2019

Summary

A Catalan non-profit association is writing a project proposal for the call SC1-DTH-01-2019 which aims to provide a system for managing the evolution of risks, as a continuous evolution tool for the actions oriented to improve the quality of life of the cancer post therapy, giving a risk prediction for undesired evolutions. They are looking for companies with expertise in software development and data analysis, national/regional health services institutions and oncological hospitals.

Description

Cancer is one of the most prevalent and serious complex of diseases, affecting nearly one in three individuals at some point in their life. In the last years, cancer survival has augmented and still increases steadily by ~3% each year, which in turn increases long-term chronic health problems and comorbidity. Understanding, predicting and avoiding cancer-related worsening of life quality and appearance of comorbidity is thus one of the key challenges of cancer management in the upcoming years.

The SITRAQ project (SImulator of TRAjectories of Quality of Life) faces this need by aiming at these objectives:
- Exploiting the available clinical data to understand the life quality and comorbidity trajectory of patients diagnosed and treated with cancer.
- Prospectively classifying cancer patients according to their life quality and comorbidity trajectory through a machine learning-based classification algorithm.
- Determining intervention points to avoid life quality worsening and appearance of expected comorbidities according to patient profile
- Through a piloting phase in major hospitals, estimating the improvement of patient satisfaction and health systems savings derived from the application of the classification algorithm + intervention points.

To achieve these objectives, the consortium wants to provide a system for managing the evolution of risks, as a continuous evolution tool for the actions oriented to improve the quality of life of the cancer post therapy, giving a risk prediction for the undesired evolutions.

It will be radically different from existing technologies that have been tested for a while and have been demonstrated as difficult to apply to real world problems: using genomics to personalize, or using wearables and apps to monitor, implies generating low quality data and a small day to day impact in the quality perceived by the patients.

For this reason, they will focus on assigning each patient in a cluster for which the evolution of the disease is known. The clustering is built from data from diverse and complex sources: tumour registry, medical prescriptions, basic history from all the healthcare levels (primary aid, emergency departments, hospital, mental health) and data from ad-hoc polls on the perceived quality of life.

The temporal evolution of these complex patterns provide them state trajectories that patients tend to follow. These allow to modulate the monitoring and prevention actions to avoid an undesired evolution due to complications. The set of forthcoming likely statuses for a patient who is in a given state today is the key knowledge for choosing action. This evolution is analysed by a state model simulation that also allows to compare variability among regions, as well as factor in the influence the of clinical, social, and therapeutical variables.

Predict to prevent is the reason of the project. It pursues constructing evolution models adapted to each territory and able to place the patients in a state of the frequent trajectories to adequate the treatment in function of their risks.

To complete the consortium, they are now looking for companies with expertise in software development and data analysis in the health sector, national and regional health services institutions and oncological hospitals. They are also looking for an institution with expertise in the management of H2020 European projects as a coordinator of the proposal.

Call: H2020- SC1-DTH-01-2019 - Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment.
Call deadline: 24 April 2019
Deadline for EOIS: 8 February 2019

Stage Of Development

Proposal under development

Requested partner

The entity is looking for:

- National / regional health services: Role and tasks to be performed: Demographic analysis providing the minimum basic data set (MBDS) 2014-2017, codified in ICD.

- Expert institutions (e.g. Oncological associations): Role and tasks to be performed: Clinical documentation, Evaluation support, Dissemination plan.

- Non-Spanish Software SME: Role and tasks to be performed: Web development: user interface for MD’s access to analysis algorithms in hospital.

- European Oncological hospital: Role and tasks to be performed: Expertise and data providers for the pilot project

Cooperation offer ist closed for requests