HIV Archives - Healthentia

Enhancing HIV Patient Care through Healthentia

System — Tue, 19 Mar 2024 14:48:57 +0000

People living with HIV infection (PLWH), particularly those with immunodeficiency and immune dysregulation, may be at increased risk in various cases where access to hospital environment might introduce risks to their health. Although the literature data do not appear to be in complete agreement, several papers have documented an increased risk of severe disease and death associated with HIV cofactor.

Our research paper titled “HIV Patients’ Tracer for Clinical Assistance and Research during the COVID-19 Epidemic: A Paradigm for Chronic Conditions” has been published in the Special Issue Reprint titled “Advances in AI for Health and Medical Applications“.

This publication shares insights derived from the INTERFACE study; a collaborative effort conducted by Healthentia that provided support to HIV patients during the 1^st wave of the Covid-19 pandemic.

The INTERFACE study focused on leveraging e-health and remote monitoring to enhance care for people living with HIV/AIDS (PLWHA), especially during the SARS-CoV-2 pandemic period. Using Healthentia, a mobile application with decision-making algorithms, the study collected data on symptoms, treatment adherence, and quality of life, processed through an innovative e-Clinical platform. Machine learning algorithms aimed to create a digital composite biomarker for HIV-related alerts. With over 1500 stable HIV patients in a university hospital, the study aimed to improve patient care beyond the pandemic, showing promising results in monthly data for learning predictive models.

INTERFACE, an interventional research initiative, collected real-world data (RWD) on patient outcomes. Voluntarily enrolled patients provide informed consent through the app or eConsent process. Operating within Gemelli Generator Real-World Data (G2 RWD), the study integrated Healthentia data into a tailored e-Clinical environment provided by Innovation Sprint. Healthentia combined traditional electronic patient-reported outcomes with lifestyle, behavioral, and health-related data, employing AI and machine learning to predict outcomes and generate prevention alarms, supporting clinical decision-making during trials.

This comprehensive approach proved crucial for managing HIV patients during the COVID-19 pandemic, addressing physical and mental health challenges. The e-health system identified health issues, tailored interventions, and served as a pre-screening tool for chronic patients during the epidemic. Preliminary evidence indicated effective prediction of alerts, with ongoing data collection and integration enhancing accuracy. Future development involves SHAP analysis, assessing the machine learning system’s impact on health indicators, and evaluating its application in advanced chronicity management. The study aimed to provide tailored and effective care for individuals living with HIV, especially in challenging times like the COVID-19 pandemic.

Explore the INTERFACE study for detailed insights into how Healthentia offered assistance to individuals with HIV during the Covid-19 pandemic.

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HIV Patients’ Tracer for Clinical Assistance and Research during the COVID-19 Epidemic (INTERFACE): A Paradigm for Chronic Conditions

System — Tue, 12 Mar 2024 13:55:30 +0000

CATEGORY: Advances in AI for Health and Medical Applications

SOURCE: MDPI Open Access Journals, Information, February 2022, 13(2), 76; https://doi.org/10.3390/info13020076

HIV Patients’ Tracer for Clinical Assistance and Research during the COVID-19 Epidemic (INTERFACE): A Paradigm for Chronic Conditions

Antonella Cingolani^1,2 , Konstantina Kostopoulou³, Alice Luraschi^1,4, Aristodemos Pnevmatikakis³, Silvia Lamonica¹, Sofoklis Kyriazakos^3,5, Chiara Lacomini^1,4, Francesco Vladimiro Segala², Giulia Micheli², Cristina Seguiti², Stathis Kanavos³, Alfredo Cesario^1,3, Enrica Tamburrini ^1,3, Stefano Pararnello², Vincenzo Valentini ^1,2,4 and Roberto Cauda ^1,4

¹Fondazione Policlinico A. Gemelli IRCCS, 00168 Rome, Italy

²Infectious Diseases Department, Università Cattolica del Sacro Cuore, 00168 Rome, Italy

³Innovation Sprint, 1200 Brussels, Belgium

⁴Gemelli Generator, Fondazione Policlinico A. Gemelli IRCCS, 00168 Rome, Italy

⁵BTECH, Department of Business Development and Technology, Aarhus University, 7400 Herning, Denmark

^*Author to whom correspondence should be addressed.

Abstract

The health emergency linked to the SARS-CoV-2 pandemic has highlighted problems in the health management of chronic patients due to their risk of infection, suggesting the need of new methods to monitor patients. People living with HIV/AIDS (PLWHA) represent a paradigm of chronic patients where an e-health-based remote monitoring could have a significant impact in maintaining an adequate standard of care. The key objective of the study is to provide both an efficient operating model to “follow” the patient, capture the evolution of their disease, and establish proximity and relief through a remote collaborative model. These dimensions are collected through a dedicated mobile application that triggers questionnaires on the basis of decision-making algorithms, tagging patients and sending alerts to staff in order to tailor interventions. All outcomes and alerts are monitored and processed through an innovative e-Clinical platform. The processing of the collected data aims into learning and evaluating predictive models for the possible upcoming alerts on the basis of past data, using machine learning algorithms. The models will be clinically validated as the study collects more data, and, if successful, the resulting multidimensional vector of past attributes will act as a digital composite biomarker capable of predicting HIV-related alerts. Design: All PLWH > 18 sears old and stable disease followed at the outpatient services of a university hospital (n = 1500) will be enrolled in the interventional study. The study is ongoing, and patients are currently being recruited. Preliminary results are yielding monthly data to facilitate learning of predictive models for the alerts of interest. Such models are learnt for one or two months of history of the questionnaire data. In this manuscript, the protocol—including the rationale, detailed technical aspects underlying the study, and some preliminary results—are described. Conclusions: The management of HIV-infected patients in the pandemic era represents a challenge for future patient management beyond the pandemic period. The application of artificial intelligence and machine learning systems as described in this study could enable remote patient management that takes into account the real needs of the patient and the monitoring of the most relevant aspects of PLWH management today.

Keywords: HIV; COVID-19; e-Clinical assistance; outcome prediction

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Innovation Radar Prize 2022 – Disruptive Health

System — Tue, 18 Oct 2022 14:13:03 +0000

We are excited that Innovation Sprint is short-listed for the Innovation Radar Award on Disruptive Health, together with 9 other companies.

Since 2015 the European Commission has been awarding the annual Innovation Radar Prize to great EU-funded innovators, putting a spotlight on the high-potential innovations they are trying to get "out of the lab and into the market". Intelligence gathered by the Innovation Radar is used to identify innovators who can then compete for the prize.

The top innovation finalists are grouped into 3 categories of 10 each, out of a tremendous number of applications for the 2022 Innovation Radar Prize. The 3 categories are:

Disruptive Health
Purpose-driven & Green
Kickstarter

The Innovation Radar Prize 2022 includes voting from the public, which will assist the jury in their search for the best innovation of 2022.

Innovation Sprint is one of the 10 candidates for the Innovation Prize of Disruptive Health and we are looking forward to receiving your vote here.

Vote for Innovation Sprint

Why have we been selected as finalists?

Sofoklis Kyriazakos, CEO of Innovation Sprint, explains the reasons that brought Innovation Sprint to the final of the Innovation Radar Prize 2022.

Innovation is part of our company name, but foremost it is part of our DNA. Our purpose to improve health outcomes and outperform existing therapeutic care-paths using innovative technologies, has been an exciting and long journey from the day we started until where we are now commercializing our novel MedTech product in this highly regulated and challenging domain. Our product Healthentia, is a certified Software as Medical Device that uses best of breed of Internet, IoT, AI, and Big Data technologies together with clinical and regulatory knowledge to support healthcare professionals to monitor their patients, through digital clinical pathways addressing chronic conditions. Healthentia has been used so far in patient cohorts with cancer, heart failure, COPD, Covid-19, HIV, and other conditions. The clinical evidence that has been captured so far demonstrates increased adherence to treatment and Quality of Life, while we are currently running clinical studies, in which we monitor endpoints like mortality and rehospitalization. In Belgium, we are already at level 2 of the mHealthBELGIUM pyramid link, which paves the way towards reimbursement. We have market authorization for Europe and we have finalized the PreSub evaluation from FDA for 510(k) clearance. This journey was strongly influenced by our research activities, many of them performed under EC R&D projects, which contributed to the inclusion of key innovations in Healthentia and bringing the product to another level; a level that is backed up by science. We are committed to continuously improving Healthentia to disrupt health, by outperforming traditional treatments, thus contributing to Good Health and Wellbeing, one of the key sustainability goals of the UN. In this trajectory, we will continue to improve Healthentia in a way to address demanding market needs, regulatory challenges, while implementing our purpose to use innovative technologies to improve health outcomes and outperform existing therapeutic care paths.

What are the key innovations so far?

Aristodemos Pnevmatikakis, R&D Director of Innovation Sprint, explains Healthentia smart services and the role of EU co-funded projects in implementing them.

Healthentia is a secure big data platform for patient data, providing two applications to its two categories of end-users: a) Patients use the mobile app to facilitate the collection of their data and delivery of info and feedback, and b) healthcare professionals use the portal app to setup studies or programs to monitor their patients both as a cohort, or as individuals. Both applications are empowered by smart services: On the one hand, clinicians can handle patients in clusters and get insights from inference on models learnt on patients’ data. On the other hand, patients benefit from feedback on important attributes in their data, as these attributes are highlighted by explainable AI techniques.

EU co-funded projects have been playing a dual role in Healthentia. Looking back at our origins, the company started as the exploitation output of the eWALL project. Many more recent and ongoing projects have been instrumental in the implementation of our smart services. They allow us to run studies across Europe, increasing our volume and diversity of subjects, thus reducing the bias in the models we can learn from the collected data. They also facilitate early testing of our models in prototypes of our smart services. Last but not least, they facilitate our scientific output, by providing us with collaboration opportunities and funding for publications.

At Innovation Sprint we commit to providing patients and professionals with continuously improved smart services, aiming at helping the former improve the life of the latter.

How do we combine innovation with needs?

Konstantina Kostopoulou, Chief Product Officer of Innovation Sprint, explains how Healthentia has evolved into the solution it is today by combining innovation with the different stakeholder’s needs from the market.

Healthentia has been developed through participatory design and evaluation from stakeholders. Both the application for the patients and the portal for the clinicians are co-designed with patient focus groups and workshops with clinicians. In this product development journey, we have done user studies and interviewed patient focus groups after asking them to accomplish a set of tasks on the mobile app. They have evaluated the easiness and experience of using Healthentia. For similar tasks their valuable feedback is collected for feature optimizations. Regarding the clinician portal, regular sessions are taking place to collect feedback from clinicians to address their needs and optimize the assessment of a patients’ health state. We work together with clinicians from customizing their dashboards or enhance their patient record with selected clinical date from a hospital’s EMR. The Healthcare market include a great range of Stakeholders including but not limiting to, patients, caregivers, doctors, nurses, patient organizations, government, insurance companies, communities and pharmaceutical firms. Our collaborations within this market influence our product roadmap to meet the needs and expectations in this changing environment of digital Health.

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