Managing chronic obstructive pulmonary disease (COPD) alongside other chronic conditions (CCs) like depression requires a comprehensive and innovative approach. As part of the RE-SAMPLE research project, Healthentia, our advanced SaMD solution, addresses this challenge by integrating real-world data (RWD) to enhance disease management and improve daily life for patients. For more information about the intended use of the device and the medical modules, please consult: https://healthentia.com/medical-device/

This research-driven initiative bridges the gap between clinical research and real-world healthcare, supporting two phases of COPD and CCs management:

• Phase 1: Healthentia collects RWD to track disease progression, uncover patterns, and predict exacerbations. These insights enable proactive care, empowering healthcare providers to anticipate and address patient needs more effectively.
• Phase 2: Through its Virtual Companionship Program (VCP), the platform delivers tailored self-management tools, including lifestyle coaching, goal-setting, and real-time medical suggestions. Patients gain the confidence to manage their health actively, while healthcare providers benefit from actionable insights via a clinical dashboard. This enables personalized, adaptive care strategies, ensuring better outcomes.

Healthentia redefines the standard of COPD care in hospitals across Europe by seamlessly integrating real-world insights with technology-driven solutions. By prioritizing both patients and providers, it transforms the approach to managing not only COPD but also co-existing chronic conditions, helping patients regain control over their health and well-being.

This World COPD Day, Healthentia reaffirms its commitment to innovation, providing hope and support for millions living with COPD.

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World Diabetes Day is an essential reminder of the global impact of diabetes. Especially type 2 diabetes affects millions of lives and continues to grow at an alarming rate. Currently, type 2 diabetes makes up more than 90% of the over 450 million adults worldwide that are living with diabetes. By 2030, this number is expected to reach 578 million. This increase not only strains healthcare systems but places a significant burden on individuals who must learn to live with and manage this chronic condition.

At Innovation Sprint, we believe in empowering patients by providing Healthentia, the patient companion app they need to effectively manage their condition at home. Healthentia is designed for chronic disease management, offering a personalized approach to each patient. By collecting data on daily habits, physical activity, and health metrics, Healthentia offers customized support and advice that aligns with the patient’s health goals and current state. For more information about the intended use of the device and the medical modules, please consult: https://healthentia.com/medical-device/.

For type 2 diabetes patients, effective management is key to preventing serious complications like heart disease and nerve damage. While healthcare professionals are essential, most daily care happens at home, requiring regular monitoring, a balanced diet, physical activity, and adherence to treatments. Many patients find this challenging, especially without personalized guidance.

In our ongoing research study with type 2 diabetes patients, we are taking this a step further. By gathering detailed data, we can provide personalized recommendations that evolve alongside the patient. For instance, if a patient’s activity level drops or they struggle with diet management, Healthentia can recognize these patterns and suggest targeted interventions that encourage gradual improvements. This constant, personalized feedback loop helps patients feel supported and more capable of taking control of their health.

On this World Diabetes Day, let’s acknowledge not only the challenges but also the strides being made in digital health to enhance self-management for millions of people worldwide. With solutions like Healthentia, we’re creating a future where living with diabetes doesn’t have to be so daunting.

“In our new study with Diabetes Mellitus Type 2 patients in the University of Thessaly we are integrating Healthentia, a digital health solution, to evaluate how digital health tools can enhance traditional healthcare. The patients thus far responded positively, embracing the mobile app for their support at home, while the healthcare professionals benefit from the web portal, which provides real-time data monitoring and insight into the tailored advice each patient receives.” 

Tamouridis Stefanos MD, MSc
Clinic of Endocrinology and Metabolic Diseases, General University Hospital of Larissa
University of Thessaly

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At Innovation Sprint, we are advancing new features for Healthentia to improve patient analysis and care. One of our key initiatives is the development of models that provide both long-term and short-term predictions for patients. In the long-term, these models forecast a patient’s health progression based on their clinical, physiological, and behavioral data, while in the short-term, they predict the most suitable next steps for intervention. A critical focus is on ensuring these intervention techniques are personalized to each patient’s unique condition, both for long-term management and immediate care. By tailoring interventions to the individual, we aim to achieve more accurate results, enhance patient outcomes, and improve the overall care process.

Our experiments indicate that model quality strongly depends on the data, both its volume and quality. Data volume is determined by the number of patients having already used Healthentia for a particular pathology. Data quality is determined by each patient’s adherence to the data collection plan. Both data volume and quality are seldom ideal. At least during the first studies Healthentia is used for a particular pathology, there are simply not enough patients to give us a satisfying volume of data. Moreover, patients are of varying degrees of capability to collaborate with Healthetnia’s mobile app. Omissions and errors can happen, and then reduce data quality.

Training with suboptimal data volume and quality leads to suboptimal models, suffering from overfitting and bias. The alternative is to reside to the knowledge of the experts, the healthcare professionals. Their knowledge is captured within rule-based expert systems. That yield the necessary analysis of the patients. At Innovation Sprint we have been experimenting with ways to combine the information the data offers and the expertise the healthcare professionals offer. The HumAIne project offers Healthentia the novel tools to achieve this combination.

HumAIne is an EU co-funded project under the topic HORIZON-CL4-2022-HUMAN-02-01 that started in October 2023. 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, Neuro-Symbolic Learning, Swarm Learning, and eXplainable AI. The HumAine OS enables AI solution creators to build advanced Human-AI collaboration systems that outperform standalone AI and individual experts’ efforts.

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. More specifically, we will be employing Neuro-Symbolic Learning to learn models not simply on data, but on the combined information of data and healthcare professionals’ expertise. We will be comparing the models learnt traditionally to those employing Neuro-Symbolic Learning, both in terms of prediction metrics but also in terms of their effectiveness in the overall behavioral change framework of Healthentia.

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Definition & importance

Real-World Data (RWD) is any data relating to a patient’s health status, collected during the routine delivery of care, as opposed to data collected within the controlled setup of clinical trials. Hence RWD does not differ so much in its type but in the process and population involved in its collection. The different types and sources of RWD can be:

• Clinical data from electronic health records (EHRs) and case report forms (EHRs). This data establishes who the subject is, providing demographics, family history, comorbidities, procedure and treatment history, and outcomes. Such data types are also common in clinical trials.
• Patient-generated data from patient-reported outcome (PRO) questionnaires, or measurements from wearables. This is data collected in everyday setting, providing insights directly from the patient, beyond clinic visits, procedures, and hospitalization. While patient-generated data is not unusual in clinical trials, it is collected in a centralized manner at the regular visits of the trial volunteers to the healthcare facilities. In the real-world context, the collection is done continuously at home.
• Public and government data including cost and utilization data. Such data provides information on the healthcare system and the different stakeholders therein.

Such information can be used to create algorithms for risk stratification or to gain insight into associations between exposures, interventions, and outcomes.

While clinical trials continue to be the main tool for studying the safety and efficacy of a new medicine, their controlled environment, and well-defined cohorts constitute experimental conditions that do not represent real-world settings. RWD is a much better tool for understanding how patients react to a medicine once approved and made available in the market, i.e., in routine medical care. The lack of highly controlled settings usually results in lower levels of confidence, but the outcomes represent a wider population of subjects. Such outcomes are better suited for understanding and taking decisions in everyday medical care, in broader settings than the controlled ones in clinical trials.

RWD: Collecting in a clinical vs. everyday setting

There can be a huge quality difference between RWD collected in a clinical versus in everyday setting. In a clinical setting, the process is carried out sporadically by professionals, with subjects following strict guidelines (like time and method of collection, or diet prior to collection). In the everyday setting, the process is continuous and carried out by the subjects themselves. Whether the data is reported by the subjects or is measured by devices the subjects operate, the continuous nature and the self-supervision can lead to low quality due to device failure (usually uncharged devices, wearables not worn when they should have been, or mobile applications left unused for too long and automatically closed down) and lack of adherence (forgetting to answer instances of repeating questionnaires, amplified decline of interest in the process). Also, clinical data can be much more specialized to the medical conditions at hand, compared to most behavioral data collected in an everyday setting.

But no matter these shortcomings when dealing with data collected in an everyday setting, it is now well-established that behavior is part of the intervention. The high specialization and quality of the sporadic clinical data is complemented by the continuous nature of the behavioral, everyday data, in much the same way a low-resolution film complements the understanding offered by the occasional high-resolution photo.

Patient-generated, everyday RWD types

The behavioral, everyday RWD are categorized in terms of collection method and content. The following collection options are used:

• Patient-reported via questionnaires: This collection model is closer to the established clinical trial approach, but this time the questionnaires are digital, pushed to subjects via some companion mobile app. They mostly have to do with self-assessment of different aspects.
• Patient-reported via widgets: Similar to questionnaires, only this time rich graphical interfaces are employed. The widgets allow manual entry, or take advantage of integration with 3^rd party devices meant for occasional use like scales or blood pressure monitors to automatically collect measurements.
• Automatically reported by wearables: Continuous measurements from wearable devices is one of the most prominent sources of RWD. Ubiquitous activity trackers or more specialized devices like sleep monitors are integrated either at device level (when a Software Development Kit is available, e.g., via Apple Health Kit) or at device cloud level (when an Application Programming Interface is available).

Using any of the above methods, the following everyday RWD types are collected:

• Physiological: Data about physical activity, continuous monitoring of vitals, sleep
• Psychological: Emotions
• Social: Interactions (phone calls, social media)
• Environmental: Living and working environment

Learning on RWD

At a raw level, RWD can lead to decisions about individuals and cohorts via analytics visualizations. But a full understanding of the context of subjects is gained via processing, using machine learning techniques. Supervised algorithms facilitate learning biomarkers, while unsupervised ones lead to phenotypes.

RWD facilitates learning digital composite biomarkers. Biomarkers are quantities characterizing some disease or outcome. Digital refers to their attributes being ubiquitously available, not only as clinical data. Composite refers to the combination of multiple attributes in an attempt to predict some outcome. ML algorithms are used to learn outcome predictors as non-linear combinations of the attributes into the digital composite biomarkers.

Phenotypes characterize the way the internal conditions of subjects manifest themselves for external observation. The different RWD attributes measured constitute the observation, and clusters of the observations correspond to different phenotypes. The clusters are learned from RWD using unsupervised ML algorithms. The clusters are then modeled for efficient representation of the phenotypes.

RWD in Healthentia

Our product Healthentia is used to collect all types of patient-generated, everyday RWD types. Our subjects employ the Healthentia mobile app to answer questionnaires and to enter data via the widgets, either manually or using devices integrated via their Software Development Kits. Data collection also employs the Healthentia big data platform and ingests more subjects’ data using the Application Programming Interfaces of other device providers.
The collected RWD is analyzed using the BI analytics available at the Healthentia portal for healthcare professionals. It is also processed using the smart services of Healthentia, namely:

• The Learning Services for training models
• The Inference Services for inferring with the help of the trained models
• The Clinical Pathway for utilizing the raw RWD and the inference results in monitoring the state of subjects, and
• The Virtual Coach for utilizing all the above in personalized advice given to the subjects.

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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. 

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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Topics: eHealth, patient reported outcomes, e-clinical platform, smart eHealth

SOURCE: Front. Digit. Health, 06 September 2021;  BOOK DOI Link, Chapter DOI Link

Discovering Composite Lifestyle Biomarkers With Artificial Intelligence From Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services

Sofoklis Kyriazakos ^1,2* ; Aristodemos Pnevmatikakis ¹ ; Alfredo Cesario ^1,3 ; Konstantina Kostopoulou ¹ ; Luca Boldrini ⁴; Vincenzo Valentini ^4,5 ; Giovanni Scambia ⁴ 

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The COVID-X Programme aims to accelerate companies with Medical Devices that have a track record with Covid-X applications and support them to introduce solutions of strong impact to the market.

Since March 2020, Innovation Sprint helps Hospitals and other Healthcare Organizations to improve their Covid-19 resilience and response by managing Covid-19 related symptoms of patients and health workers from remote and providing targeted support and care guidelines to them.

The Care4Covid solution is a remote care and remote support solution, yet it directly boosts the business continuity and operational efficiency of healthcare organizations as well. The solution was initially developed in March 2020, following the pandemic outbreak. It was developed as pivot of the Healthentia eClinical platform, which already provided symptom-tracking functionalities and used by Top5 Pharma for clinical studies. Innovation Sprint adapted its Healthentia Symptom tracker towards tracking Covid-19 symptoms and managing patients-provided Covid-19 information.

During the past months, the solution has evolved to provide remote management and support for healthcare workers, in terms of their Covid-19 related status and symptoms. As of today, Healthentia is used in several Covid-19 related clinical studies and recently it has launched its Vax version to support tracking of the vaccination programme.

Therefore, the problems that are solved by the use of Healthentia are related to:

• Preventive actions by clustering patients & healthy individuals into risk categories
• Remote monitoring and supporting of patients
• Execute workflows and clinical pathways to Covid-19 positive cases
• Business Continuity in large organizations
• Follow-up of vaccination programme

Care4Covid is leveraging the existing infrastructure of Healthentia for reporting, tracking, and analysing the symptoms of the patients, Innovation Sprint has developed a data-driven infrastructure that provides targeted care recommendations to healthcare workers and Covid-19 patients using the Healthentia Covid-19 app.

The novelty of the solution, therefore, lies in the Covid-19 profiling of different patients’ phenotypes and the provision of personalized care support and recommendations to them. Through the participation of Innovation Sprint in the COVID-X Programme, it will be feasible to extend the functionalities of the solution through the COVID-X sandbox and the accumulated knowledge of the clinical partners available, thus creating a new version of the solution, namely Healthentia Care4Covid.

*Healthentia application is a certified Class I Medical Device.

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Welcome to our blog post series “Healthentia dose” with articles and interesting reads we come across from the fast-changing industry of #ClinicalResearch and #DigitalHealth. What we read, shapes our thinking and strategy, triggers our goal settings, and even pivots our businesses.

This is an insightful journey, and we want you to be part of it.

In this Healthentia dose, we look at collaboration, gender bias and how to positively change behavior.

When your competitor becomes your collaborator

How many times have you done your marketing analysis or went mystery shopping to study well your competitor? Challenging times like these ones need a change of approach. Competition for new products or features won’t just do, to solve the world’s biggest health issues, collaboration is required. It is inspiring to hear on this podcast, giants in the most competitive arena, the Life Sciences, to sit down at the same table and try to solve problems, together. We should all look at similar opportunities. No one can do a big change alone.

Scissorhands Ladies

Talking about collaboration in problem solving, we also saw an amazing duo, when the prestigious Nobel prize of Chemistry was split between two ladies scientists. Emmanuelle Charpentier when she published her first findings, she then initiated the collaboration with Jennifer Doudna, to advance her research discoveries. Together, they were able to succeed in recreating the bacteria’s genetic scissors and simplifying them for a larger scale use. This tool has now contributed to many important discoveries in medicine and clinical trials of new cancer therapies are underway, and the dream of being able to cure inherited diseases is about to come true. “These genetic scissors have taken the life sciences into a new epoch and, in many ways, are bringing the greatest benefit to humankind.” Kudos to these amazing ladies in research.

Creating a Gender partnership not a struggle of dominance

Talking about strong partnerships, this is a great one! While a discouraging proportion of our population believes that Covid-19 is fake so that Bill Gates can put a chip on you and me, I had the chance to read the “Moment of Lift” by Melinda Gates. This book is about the work of the Bill and Melinda Gates Foundation, to empower women around the globe, from vaccines to family planning and projects to stop child marriages or education opportunities to girls. I found the storytelling in this book heartbreaking but powerful. It highlights the strength and will it takes from a few, to open up, the support and collaboration are enough to make a change. You can’t help to feel privileged of being born on this side of the planet when you hear of the struggles of women and girls to cope, care for their children, or get educated and respected.

I was convinced in this book about the importance of listening and opening up. I picked up some key points, for our journey with Healthentia. Need to listen to patients!

You can’t meet a need, you don’t know about!! 

Don’t can’t judge from the outside, you should better discuss from the inside. Change can come only through empathy

Listening is about opening up to others and it is empowering for the ones you listen

and saved the last two, to share with my girlfriends :

Every man who is a bully is scared of a group of women & a collaboration group’s intelligence is strongly correlated to gender diversity than IQ, so GO AHEAD, JOIN IN.

What does actually get people to change behavior?

We learned that change can come when you show empathy, and no matter how many times I hear or read about these behavioral change strategies it is never enough.

How many times have we tried to scare our kids of the impact of a bad behavior? “If you don’t wash your teeth they will fall off!” These threats are commonly used to visualize a future impact of a bad behavior but these freights have actually very low impact on behavior change. In this TEDx video, Tali Sharot explains scientifically why by using these three positive strategies your results will be much better. They are based on principles that drive the human mind and behavior:

Social incentives, “We are social creatures we care what other people are doing and we want to do it better.”

Immediate rewards, “We value instant gratification because the future is far. So a positive behavior is associated with a reward can become a lifestyle.”

Progress monitoring, “Highlighting the progress and not the decline.”

I think looking at how we are moving towards the new paradigm of medicine: predictive, preventive, personalized, and participatory (P4) medicine, we need to build coaching techniques that will incorporate principles that drive human behavior, as we know that lifestyle and health is connected in a two-way equation and we believe that digital biomarkers will be the driving forces to make decisions and orchestrate Digital Therapeutic DTx content.

Gender Bias in Adverse events

With the rise of real-world clinical data, like lifestyle and clinical outcomes collection, we can start seeing gender differences in disease expression, severity, and even adverse effects. Women may be better off when it comes to Covid-19, based on this latest study for example are more prone to adverse drug effects due to a wrong dosage. As a proud Columbian, I always follow the great research taking place in this plot of Manhattan land. In this article, @nicktatonetti associate professor @ColumbiaDBMI, explains how Adverse Events are sex-specific. New data mining techniques are uncovering previously hidden adverse drug effects that impact women more than men. These new methods are based on great data collaboration initiatives, that hold the key to unlocking these insights due to need of large datasets.

Visualizing aerosols

Maybe too small to see but can be lethal. I hope most people have seen this spatial visualization of aerosol spreading in different scenarios from El Pais that was all over Twitter. I will however include it as I think it is a) a piece of art, b) most crucial for all to understand the importance of good ventilation regardless of the cold and our positioning in a public space. Even though most of us are restrained at home these days, on the occasion, you need to visit a public space or use public transport, do keep these in mind. Patient 0s are all around us, could be one next to you.

We love Science, we listen to it. #Stay safe, until next time.

Konstantina Kostopoulou,

Chief Product Officer, Innovation Sprint.

The post Healthentia Dose 2 – Collaboration, gender bias and achieving behavioral change appeared first on Healthentia.

Welcome to our blog post series “Healthentia dose” with articles and interesting reads we come across from the fast-changing industry of #ClinicalResearch and #DigitalHealth. What we read, shapes our thinking and strategy, triggers our goal settings, and even pivots our businesses.

This is an insightful journey, and we want you to be part of it

In this Healthentia dose, we look at evidence-based research and health and how to live better longer.

“The Lean startup hits healthcare and Life sciences”

I wanted to start this post by sharing this interview that I came across of Steve Blank “The Lean startup hits healthcare and Life sciences” that seemed very relevant as ever since joining the team at Innovation Sprint, I have heard and used the methods for business planning from the Lean Startup book check out also our CEO’s article about it. These great tools for startups like the “business canvas” and “value proposition canvas” fit indeed very well in the Healthcare field and we have used these tools for the development of Healthentia. I loved these takeaway points “In the life sciences, finding the product-market fit is important but equally important is to understand who’s going to pay for it.” and “Clinicians and researchers are actually better at lean startups than almost any other field because, in medicine, you know what you don’t know” Do you know what you don’t know, to go and look for it?

“A heart bit is a heart bit”

Moving on, I have been researching a lot lately the digital biomarker space, and looking at the standardization required in order for digital endpoints to be equally assessed. I came across this most valuable crowdsourced list of digital endpoints from the Digital Medicine Society, collected the last few years in clinical trials. I am sure there are a lot more out there not listed here, as it is crowdsourced. They just released also a playbook as an industry guide to incorporating digital endpoints in their clinical trials. Check it out.

Population Real World Data

As the Covid pandemic has challenged the traditional Clinical trial models,  it is very optimistic to see that the industry is adopting not only the use of tools like ePROs to collect Patient Outcomes, but also considering the use of telemedicine for virtual site visits and wearable devices to collect Real World Evidence aiming to offer more streamlined patient-centric trials.  In this interactive report from IQVIA, it is stated that within the next ten years, the use of Digital Health is likely to be mainstream for most organizations delivering human health.

Symptom Tracking- What are the signs to monitor?

In the context of Real-world data collection are the following reads that are very close to our current research initiated with Healthentia Covid Symptom Tracking. From the months of April a few articles started to pop up claiming that certain research departments globally are demonstrating that digital measures can support public health. The question that people want to answer is “can we develop corona or pandemic early warning systems? What are the signs to monitor? We know, that a person infected will exhibit a fall in step count and an increase in pulse rate but is that enough? Are wearables good early warning systems?  A take away is that “Wearable researchers treat the data not as an individual measurement, but rather as a baseline — a view of what’s “normal” for your body, from which they can spot deviations.” And this is where our research is now focused. Using healthentia ML module we create a composite digital biomarker as a multidimensional vector from the collected vital signs and outcomes coming from a patient, that can detect health behavior changes something like an alerting communication engine.

Salutogenesis – Evidence-based healthcare

And there is so much unrealized potential in health care delivery today. If healthcare starts to use the insights from population health data, it can become preventive of disease and more protective and promotive of positive health. Our whole system is working for curing instead of preventing it. I came across an interesting idea of a new paradigm called Salutogenesis. A bit futuristic you might think, looking at our current pathogenic approach, but if we start collecting lifestyle and behavior evidence (RWE) we need to also change our orientation to an evidence-based healthcare and research practice. Food for thought.

Making the most of your Extra time

More food for thought on health behavioral changes in the summer break came from reading this book, for my birthday, written by Camilla Cavendish called Extra time: 10 lessons for living longer better (only still 42y). Although it seemed at first “irrelevant” I have to say that I found it very enlightening and I wanted to share with you my 5 takeaways.

1. We live in unprecedented demographic changes with global consequences and some of these takeaways can help us live a longer better life.
2. “If exercise and diet was a pill, everyone would be taking it” This is how important these two are for living longer better. Also, not only a healthy diet is keen but calorie restriction like eating until you are 80%, not starvation might be the reason behind the longevity of the some Red zone areas.
3. Keep learning “Old brains can and must learn new skills to keep in shape”
4. “Aerobic exercise, social contact (meaningful relationships) and new challenges and purpose in life seem to be vital.”
5. “We need to maintain our curiosity and venture into new areas beyond our comfort zone.”

But the best quote that I had only heard half before is that “The best time to plant a tree is 20 years ago. The second-best time is NOW”, therefore I agree with the author that it is a responsibility of our generation and as researchers in this domain, to lay the foundations of fair digital preventive health care systems.

Listen to Science

To finish off my first “Healthentia dose” since it has raised a lot of discussions about how safe young people are regarding the Covid infection and even hear about a herd immunity plan to face the Covid pandemic. I wanted to close with the quote from this journalist. “Herd immunity is an inoperable plan, teetering on a false assumption of elderly-cocooning, which encourages young people to play craps with the long-term health of their internal organs. The choice is yours. You can listen to the scientists. Or you can roll the dice with your guts” What’s your choice?

We love Science, we listen to it. #Stay safe, until next time.

Konstantina Kostopoulou,

Chief Product Officer, Innovation Sprint.

The post Healthentia Dose 1 – Evidence-based research and health and how to live better, longer appeared first on Healthentia.