Periodic Reporting for period 1 - RETENTION (heaRt failurE paTient managEment and iNTerventIOns usiNg continuous patient monitoring outside hospitals and real world data)
Berichtszeitraum: 2021-05-01 bis 2022-10-31
RETENTION is a HORIZON 2020-SC1-BHC project, funded under the topic SC1-DTH-12-2020: "Use of Real-World Data to advance research on the management of complex chronic conditions". It has started on 01/05/2021 and will end on 31/04/2025.
In RETENTION the health condition that we are dealing with is Heart Failure (HF). HF is a chronic disease, caused by the inability of the heart muscle to pump adequate amount of blood into the circulation. Practically, the heart cannot respond adequately to its workload. This in turn leads to secondary problems, like metabolic disorders and, more importantly, to oxygen deficiency, which becomes more intense as the disease progresses and whenever the need for oxygen increases -like e.g. during physical activity. HF is associated with high mortality rates and frequent hospitalisations, imposing also a serious burden on health systems that is expected to rise in the coming years as the population ages.
The solution we are testing is technology platform consisting of two parts. In one part, the system is used to easily acquire and transmit a set of important clinical and environmental parameters from the patients’ home and present them to the physician on a regular basis or upon request. In this context, it is a telemonitoring system, that increases patient-physician interaction and is expected to improve the monitoring efficiency. On the other part, the system applies Machine learning technologies to analyse the data collected, aiming to identify patterns and correlations that would hopefully enable also the prediction of acute episodes or side effects, and allow for personalized intervention.
With regard to Real World Data (RWD), there is increasing evidence in the literature that this type of data, can play a role in clinical decision making. It is foreseen that this type of data can generate added value to the predictive models, when analysed in correlation with the clinical measurements of the patients, and lead to more safe and accurate predictions and more effective and personalized interventions to be used in the daily clinical practice.
Overall, the goal of the project is to improve the management of the disease, to support clinical decision making, to help the prevention of acute episodes and allow physicians to timely perform effective interventions before symptoms escalate. In this way, it is expected that it will have a positive impact on the primary and secondary outcomes that have been defined in the project, namely in reducing mortality and hospitalization rates, improving quality of Life as well as safety and well-being of the patients.
The RETENTION platform is going to be tested and validated in a pilot trial study in 6 hospitals in Europe, with a power of 450 patients divided in three subgroups: patients with HF, patients with LVADs and transplant patients, who will be monitored under the RETENTION study protocol for a period of 18 months.
In RETENTION the health condition that we are dealing with is Heart Failure (HF). HF is a chronic disease, caused by the inability of the heart muscle to pump adequate amount of blood into the circulation. Practically, the heart cannot respond adequately to its workload. This in turn leads to secondary problems, like metabolic disorders and, more importantly, to oxygen deficiency, which becomes more intense as the disease progresses and whenever the need for oxygen increases -like e.g. during physical activity. HF is associated with high mortality rates and frequent hospitalisations, imposing also a serious burden on health systems that is expected to rise in the coming years as the population ages.
The solution we are testing is technology platform consisting of two parts. In one part, the system is used to easily acquire and transmit a set of important clinical and environmental parameters from the patients’ home and present them to the physician on a regular basis or upon request. In this context, it is a telemonitoring system, that increases patient-physician interaction and is expected to improve the monitoring efficiency. On the other part, the system applies Machine learning technologies to analyse the data collected, aiming to identify patterns and correlations that would hopefully enable also the prediction of acute episodes or side effects, and allow for personalized intervention.
With regard to Real World Data (RWD), there is increasing evidence in the literature that this type of data, can play a role in clinical decision making. It is foreseen that this type of data can generate added value to the predictive models, when analysed in correlation with the clinical measurements of the patients, and lead to more safe and accurate predictions and more effective and personalized interventions to be used in the daily clinical practice.
Overall, the goal of the project is to improve the management of the disease, to support clinical decision making, to help the prevention of acute episodes and allow physicians to timely perform effective interventions before symptoms escalate. In this way, it is expected that it will have a positive impact on the primary and secondary outcomes that have been defined in the project, namely in reducing mortality and hospitalization rates, improving quality of Life as well as safety and well-being of the patients.
The RETENTION platform is going to be tested and validated in a pilot trial study in 6 hospitals in Europe, with a power of 450 patients divided in three subgroups: patients with HF, patients with LVADs and transplant patients, who will be monitored under the RETENTION study protocol for a period of 18 months.
In the first reporting period of the project the objectives have been related to the efficient management and coordination on the one hand and the good work progress on the other.
From the technical point of view, during this period, the user requirements were collected and the architecture of the RETENTION platform has been elaborated, using an iterative process to involve the whole consortium (clinical and technical partners). The user requirements defined the data model which was defined using widely used ontologies. The data model was used to develop the data repositories and the data transmission mechanisms. The testing and selection of the medical devices and sensors to collect the RWD was also performed early in the project. The Patient Edge devices and applications (smart home devices and mobile phone application) were developed during this period. On the clinician facing side, the Dashboard was developed, which was integrated with the Security Component, the ML training workflows and the Decision Support System. The platform is using a continuous integration process based on a micro-services architecture. The integrated platform is tested and fine-tuned in the framework of a virtual Pilot of Pilots (vPoP) process.
Apart from the technical work, the horizontal activities of a) project management, b) dissemination, communication, standardisation and sustainability and c) the ethics management related to the project implementation are running smoothly. All the essential elements for the efficient project management, work coordination and partner collaboration have been put in place early in the project. Regular dissemination activities including the development of a project web site, social media project profiles and project-related materials have been performed. The post-ethics requirements have been addressed in line with the DoA and continuous ethics monitoring is an ongoing work, overseeing all implementation choices and project steps from the ethical and GDPR compliance perspective.
From the technical point of view, during this period, the user requirements were collected and the architecture of the RETENTION platform has been elaborated, using an iterative process to involve the whole consortium (clinical and technical partners). The user requirements defined the data model which was defined using widely used ontologies. The data model was used to develop the data repositories and the data transmission mechanisms. The testing and selection of the medical devices and sensors to collect the RWD was also performed early in the project. The Patient Edge devices and applications (smart home devices and mobile phone application) were developed during this period. On the clinician facing side, the Dashboard was developed, which was integrated with the Security Component, the ML training workflows and the Decision Support System. The platform is using a continuous integration process based on a micro-services architecture. The integrated platform is tested and fine-tuned in the framework of a virtual Pilot of Pilots (vPoP) process.
Apart from the technical work, the horizontal activities of a) project management, b) dissemination, communication, standardisation and sustainability and c) the ethics management related to the project implementation are running smoothly. All the essential elements for the efficient project management, work coordination and partner collaboration have been put in place early in the project. Regular dissemination activities including the development of a project web site, social media project profiles and project-related materials have been performed. The post-ethics requirements have been addressed in line with the DoA and continuous ethics monitoring is an ongoing work, overseeing all implementation choices and project steps from the ethical and GDPR compliance perspective.
In this initial phase of the project, where the selection of the IoMT devices/sensors has been completed (after a systematic evaluation of their use), and the implementation of all services to support the project's objectives is nearing completion, no measurable impact has been noted. Still, the effective use of the platform within the pilots is expected to yield advanced data analytics and learning capabilities for large scale analysis of the comprehensive datasets collected from all pilots, as well as innovative security control techniques. These developments are expected to contribute in the research field of data analytics beyond the state of the art.
As far as the potential impacts of the project, during the first reporting period of the RETENTION project the ethical, legal and regulatory aspects have been addressed in order to pave the ground to the forthcoming clinical study, in the pilot phase. The stakeholder map has been finalised and the four main categories, namely Heart Failure patients, Healthcare professionals, Healthcare providers and financial organisations, as well as technology providers, have been targeted through specialised communication channels. The involvement of the stakeholders potentially impacted by the project results is a relevant task that is going to proceed along the project execution timeline in order to help the consortium to assess and project the results into medium-term outcomes and long term impacts relevant to patient clinical outcomes, reduction of healthcare pressure, healthcare costs' reduction and cost-efficiency in patient management compared to the usual care, improvement of satisfaction and productivity of healthcare professionals, not only in the hospitals but also at primary care level.
As far as the potential impacts of the project, during the first reporting period of the RETENTION project the ethical, legal and regulatory aspects have been addressed in order to pave the ground to the forthcoming clinical study, in the pilot phase. The stakeholder map has been finalised and the four main categories, namely Heart Failure patients, Healthcare professionals, Healthcare providers and financial organisations, as well as technology providers, have been targeted through specialised communication channels. The involvement of the stakeholders potentially impacted by the project results is a relevant task that is going to proceed along the project execution timeline in order to help the consortium to assess and project the results into medium-term outcomes and long term impacts relevant to patient clinical outcomes, reduction of healthcare pressure, healthcare costs' reduction and cost-efficiency in patient management compared to the usual care, improvement of satisfaction and productivity of healthcare professionals, not only in the hospitals but also at primary care level.