Study Description

Virtual Ward study is leveraging Healthentia solution to monitor and interact with Ovarian Cancer Patients. The Phase 1 scope pertains monitoring and support through the platform for those patients who have been treated with surgery for ovarian cancer and covers the 30-days follow-up period after post-surgery discharge. This is a critical phase of the overall care pathway, with need for the patients to receive guidelines about daily habits, treatment adherence, use/state of post-surgical devices, check of wound heal, potential inflammations, etc. Likewise, the opportunity for clinical staff to have more frequent, focused remote interactions where they can capture any evolution on overall health status, mild and severe adverse symptoms, practical issues during the recovery stage, will result in better quality of care and more efficient management of the patients group.

Study Details

• Type: Virtual Ward
• Start: September 2023
• Phase 1: 30-days follow-up period, Phase 2: pre-surgery and post-surgery treatment period

Our role

Healthentia is the essential link between gynecological surgery patients and their healthcare team. It enables seamless communication, allowing patients to report symptoms, share vital data, and interact with professionals. With features like a Virtual Assistant, we provide guidance and support during the crucial post-operative phase, enhancing care effectiveness and patient experience. Through collaboration with healthcare facilities like the Gemelli Generator – Real World Data Facility, we contribute to innovative care models, ensuring personalized and timely interventions for patients.

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Study Description

COMFORTAGE is a joint effort of medical experts, social scientists and humanists, technical experts, Digital Innovation Hubs (DIHs) and Living Labs (LLs) to establish a pan European framework for Community-based, Integrated and People-Centric prevention, monitoring and progression managing solutions for dementia and frailty.

Through COMFORTAGE, care services providers will be empowered to create and implement personalized, integrated care measures against dementia and frailty, leading to significant improvements in individuals’ well-being and quality of life (QoL). The project also focuses on enhancing stakeholders’ health and digital literacy to reduce health inequalities and promote healthy aging in modern communities.

COMFORTAGE will be validated through thirteen pilot studies across eight EU member states. It combines medical/clinical innovations, cutting-edge AI technologies, DIHs, and social innovations to address various aspects of health and well-being. The project emphasizes the integration and management of different data sources, including biobanks, cohorts, medical records, and real-world data from sensors and wearables, in a standardized structure called Holistic Health Records (HHRs).

A Virtualized AI-Based Healthcare Platform (VHP) will be developed to centralize access to AI resources for risk analysis, early diagnosis, and personalized decision-making. This platform will facilitate collaboration among stakeholders and promote effective strategies for health promotion, disease prevention, and treatment, while minimizing digital literacy inequalities. The VHP will also serve as a key tool for the exploitation and sustainability of the project’s results. COMFORTAGE aims to establish an ecosystem of healthcare stakeholders and viable business models to ensure the project’s long-term impact and wider adoption.

Study Details

• Type: HORIZON-HLTH-2023-STAYHLTH-01
• Start: January 2024
• Duration: 4 years

Our role

Innovation Sprint is a technology provider within the COMFORTAGE project. Our focus lies on enhancing the functionality of Healthentia, our flagship product, with a specific emphasis on data collection, gamification, and virtual coaching. Our involvement includes various tasks across different work packages. In Work Package 4, we translate pilot requirements into precise secondary data collection and virtual coaching specifications. This involves adapting the Healthentia platform to accommodate the project’s secondary data collection needs, allowing for a deeper understanding of patients’ habits and connections, and offer content to the end-users regarding their progress towards healthier habits, through our coach companion. Furthermore, in Work Package 5, we concentrate on developing the gamification features of the Healthentia mobile app. This includes the creation of engaging elements to enhance user experience and encourage active participation. Moreover, we collaborate closely with other partners, to co-develop and host serious games designed to improve motor and cognitive skills. These games enhance the overall experience of the users and promote their skill development. Lastly, we actively contribute to the dissemination and exploitation efforts outlined in Work Package 8, ensuring that the outcomes of our work reach relevant stakeholders and are effectively utilized.

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Study Description

HLT_DTM2 is a co-sponsored Study with the University of Thessaly using Healthentia to offer personalized coaching to 30 patients with Type 2 Diabetes. The study consists of a 2-week assessment period followed by a 12 week intervention period with mandatory completion of questionnaires, weight and glucose measurement monitoring and two teleconsultations with a dietician.

Study Details

• Type:  Interventional
• Disease:  Type 2 Diabetes
• Sites: University of Thessaly
• Start:  Phase 1: Jan 2023
• Population: 30 patients
• Duration: 2 + 12-week program

Tamouridis Stefanos MD, MSc

Clinic of Endocrinology and Metabolic Diseases, General University Hospital of Larissa
University of Thessaly

Study Design & Method

Diabetes Type 2 is a chronic and complex disease, with high heterogeneity, wide variation in age of onset, varying degrees of obesity, insulin resistance and a tendency to develop complications. Its management can prevent or delay the onset of complications and maintain patients' quality of life.

The aim of the study is to investigate the effect of the use of a mobile phone application (Healthentia) by patients with DM2, which makes use of a virtual coach, educational and lifestyle interventions, regarding glycemic control, quality of life, as well as body weight and diet parameters of the patients.

Validate the effect of personalized coaching with educational and motivational content to changes in HbA1c values

Demonstrating increased physical activity, reduction in weight and changes in lifestyle habits

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Study Description

ONCODIR (Evidence-based Participatory Decision Making for Cancer Prevention through implementation) will identify risk factors associated with colorectal cancer (CRC) and will integrate multidisciplinary research methods and technologies (including health policy analytics, artificial intelligence, and decision support theories) to deliver evidence-based and personalized recommendations on colorectal cancer prevention.

Study Details

• Type: HORIZON-RIA, HORIZON-MISS-2022-CANCER-01-01
• Start: 1/6/2023
• End: 1/11/2026
• Duration: 42 months

Our Role

Innovation Sprint will be offering Healthentia for use by healthy citizens to collect data for CRC prevention. Healthentia will be offering advice on citizens’ behavior, based on the collected data and the resulting citizen understanding.

To that extend, Healthentia will be extended both in terms of functionality and content. The new functionality involves:

(1) the development of a new biomarker widget to display risk prediction results automatically collected from other modules of ONCODIR.

(2) the creation of a Kafka client, producing towards, and consuming from ONCODIR, to facilitate integration with the rest of the project.

(3) the introduction of a mechanism to wrap recommendation messages into a dialogue, facilitating both delivery and feedback towards clinicians and policy makers.

In terms of content, CRC-related questionnaires will be facilitated, and a dialogue for recommendation wrapping will be created. The resulting solution will be tested in terms of technology readiness in Laboratory Integration Test 2 and will be delivered to the large-scale pilots for use by the citizens.

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Study Description

HumAIne facilitates advanced and reliable collaboration of experts and AI towards hybrid decision making and support in a variety of industries. It delivers the HumAIne Operating System, built on four technological pillars: Active Learning (AL), Neuro-Symbolic Learning, Swarm Learning (SL), and eXplainable AI (XAI). The HumAine OS enables AI solution creators to build advanced Human-AI collaboration systems that outperform standalone AI and individual experts’ efforts.

Study Details

• Type: HORIZON-RIA, HORIZON-CL4-2022-HUMAN-02-01
• Start: 1/10/2023
• End: 1/9/2026
• Duration: 36 months

Our Role

Innovation Sprint leads the project’s efforts on defining the vision and specifications for human-AI collaboration, focusing on user requirements extraction and use case scenarios definition. These efforts lead on the needs to be covered by the technology developed in HumAIne. We also lead the healthcare pilot, where the HumAIne technology will be leveraged to enhance the AI modules in the patient understanding and advice delivery systems of Healthentia.

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Study Description

AZIMUTH model of care is delivered through Healthentia; a Software as a Service (SaaS) medical device via a mobile application for patients and a clinical dashboard for clinicians for Remote Patient Monitoring (RPM), Patient Support Programs (PSP) and Digital Therapeutics (DTx). This innovative scalable model of personalised remote heart failure care is based on good clinical practice standards and international guidelines for heart failure management and has been designed taking into consideration both the optimization of in-hospital care delivery models as well as the often unmonitored out-of-hospital and home settings

The first phase of the study has successfully validated the feasibility, patient acceptance and perceived value of the app-based model of care, demonstrating increased user engagement in patients that leads into improved adherence to treatment.

Dr. Domenico D’Amario

Senior Cardiologist at the Gemelli IRCCS Polyclinic Foundation

Study Details

• Type:  Interventional
• Disease:  Heart Failure – Chronic Ischemic Disease
• Sites: Fondazione Policlinico Gemelli
• Start:  Phase 1: Nov-March 2021, Phase 2: Jul-Jan 2023
• Population: 300 patients
• Duration: Multiphase project

Study Design & Method

Heart failure is the leading cause of death and hospitalisation in patients aged > 65 years and a major and growing medical and economic burden, with high prevalence and incidence rates worldwide. The recent pandemic crisis has made even more evident, some critical aspects in the management of complex chronic diseases, such as heart failure, and these could be exacerbated by the increased demand for care in the future. Therefore, a significant effort must be made to align services with patients’ care needs by identifying a shared model that can exploit the most advanced technologies to enhance disease deterioration, provide adequate integration between hospital and territorial services, increase appropriateness, and reduce waiting times for specialist services.

Testimonial

The care pathway for patients with heart failure includes several steps, from acute phase treatments to chronic phase patient follow-up. This requires a close dialogue between hospital cardiologists and community medicine, especially once the patient returns home, after being discharged from a third-level hospital. But at the moment this complex path is very fragmented.

Validated the feasibility, patient acceptance and perceived value of remote patient monitoring

Demonstrating increased user engagement in patients that leads into improved adherence to treatment

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Study Details

• Type: Research
• Disease: COPD and Comorbid Complex Chronic Conditions (CCCs)
• Sites: The Netherlands, Italy, Estonia
• Start: March 2021
• Population: 710 patients
• Duration: 48 months

Study Description

Shared-decision making for tailored Comorbid Complex Chronic (CCC) disease management, crossing care paths towards daily life, and early proper treatment to prevent CCC disease progression. Identify individual multi-morbid CCC exacerbations and develop tailored referrals to a multidisciplinary, adaptive virtual companionship program for COPD patients with CCCs.

The RWD from daily life measurements and existing medical knowledge-base will be integrated based on inclusive models representing e.g. patients, healthcare (providers), scientists, policymakers, and industry. The RE-SAMPLE study develop privacy-securing data management and AI prediction modeling to tailor local personalised treatment programs using accurate predictions of multi-morbid exacerbations and personalised interventions.

Study Design & Method

Patients will receive an activity tracker (i.e monitoring bracelet) that will collect at a daily basis Real-World Data like activity (i.e. steps per day), sleep, and vital signs. The device will be delivered during the recruitment, and each patient/participant will pair the device through the Healthentia application downloaded on the smartphone.

During the whole observation period, patients will report through weekly dedicated questionnaires for RWD collection and management mechanisms. Also, the study aims to implement and test the real-time predictions of the RE-SAMPLE-trained models applied to new data. 

RWD to monitor COPD symptoms beyond scheduled medical check-ups

Personalised treatment and a virtual companionship programme

Multidisciplinary approach (respiratory medicine, AI, RWD, privacy, ethics, data protection, health policy)

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Study Details

• Type: Research
• Disease: Pancreatic Cancer
• Sites: European countries
• Start: January 2021
• Population: 420 patients
• Duration: 36 months

Study Description

iHelp is a research study that delivers a novel personalised-healthcare framework. Enables the collection, integration, and management of health-related data from various sources (medical records, lifestyle, behaviours, social media interactions). The data is analysed using advanced AI techniques to draw adaptive learning models that are used to provide decision support in the form of early risk predictions as well as personalised prevention & intervention measures (alerts, behavioural nudges, consultations medications, therapies, screening, etc.) that are delivered through user-centric mobile and wearable applications.

Study Design & Method

Patients will receive a state-of -the-art wearable device (i.e monitoring bracelet) that will collect at a daily basis Real-World Data like activity (i.e. steps per day), sleep, and vital signs. The collected data are then transferred to the patient’s paired device through the Healthentia application downloaded on their smartphone. 

During the whole observation period, patients will be also asked to report their weekly wellbeing through the same application, completing dedicated questionnaires. Patient-reported outcomes together with the data coming from the wearable device are used to create lifestyle behavioral patterns of patients utilizing AI algorithms for understanding patients' habits and connections. 

Determine key risks associated with Pancreatic Cancer

Develop predictive models for identified risks

Develop adaptive models for targeted prevention and intervention measures

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