The healthcare workforce is in crisis. From devastating staffing shortages to unmanageable levels of stress and burnout, today’s healthcare workers are desperate for some relief. Unfortunately, exacerbating these already significant challenges is an increasing rate of workplace violence in healthcare. 

According to the results of a study published recently in the American Journal of Preventive Medicine, about one-third of public healthcare workers have experienced at least one incident of workplace violence during the COVID-19 pandemic. And that’s just one of many reports that demonstrate the severity of the issue. 

There are some very important things that can be done to better protect healthcare workers, but at the top of that list should be elevating workplace safety to a key performance indicator (KPI) for healthcare systems. Unless there is a top-down focus on this issue, healthcare workers will continue to be putting themselves in danger simply by going to work and attempting to provide care to the people most who, according to a study in the Annals of Medicine and Surgery,  are most likely to engage in violence against them.

Nobody outside healthcare knows how bad it’s gotten

Although workplace violence in healthcare is an issue for all types of healthcare workers, it is most often nurses who bear the brunt of workplace violence. Last year, a Press Ganey analysis surprised many, stating that an average of 57 nurses are assaulted every day — that’s about 2 every hour. While terrifying incidents of shootings may make the news, every day, all across the United States (and the world), nurses are punched, spit on, kicked, and otherwise harassed. 

Too often, this is considered just “part of the job.” When examining nonfatal workplace injuries and illnesses across all sectors, healthcare workers account for about three-quarters of all incidents, according to the Bureau of Labor Statistics. Such incidents have certainly increased since the onset of the COVID-19 pandemic, but violence against healthcare workers was already trending upwards, with the rate of injuries related to workplace violence perpetrated against medical professionals growing by 63% between 2011 and 2018.

 The importance of leadership involvement in preventing hospital incivility and violence 

Leaders play a pivotal role in preventing hospital incivility and violence by sending a clear message that certain behaviors are not acceptable and will not be tolerated in the workplace. In nearly every other industry, individuals who display threatening or inappropriate behavior are removed from the workplace. However, in the healthcare industry, healthcare workers cannot simply send badly behaving patients home. Instead, leaders must develop systems and protocols to ensure the safety of everyone.

Leaders can implement policies and procedures that promote a safe and respectful workplace. For example, they can provide training for staff members on how to recognize and de-escalate potentially violent situations. This training can include techniques for communicating with agitated or aggressive patients, as well as strategies for diffusing tense situations before they escalate into violence. Leaders can also develop escalation plans that outline clear steps for dealing with violent or disruptive behavior, such as calling security or involving law enforcement.

Additionally, leaders can establish reporting systems for incidents of violence or incivility. These systems encourage staff members to report incidents without fear of retaliation and provide a clear and consistent process for addressing reports of violence or incivility. Leaders can ensure all staff members are aware of these reporting systems and that they understand the importance of reporting incidents in a timely and accurate manner.

By prioritizing workplace safety and taking an active role in preventing incivility and violence, leaders not only create a safer workplace for staff and patients but also foster a more positive work environment where employees feel valued and supported. This, in turn, can lead to increased job satisfaction, reduced turnover rates, and improved patient outcomes. 

How Digital Technology can Help

Mitigating workplace violence is not a one-and-done initiative. It is something that healthcare organizations must consciously address every day, and no single intervention or policy will solve the issue. However, digital engagement technology has the potential to improve communication between patients and the care team (and among the care team) and increase transparency around activities related to a patient’s care, giving them more insight into what is happening around them, which can help to prevent violent incidents. 

Digital health technology, via either TVs or mobile devices, can be used to provide clear prompts to patients and their families, clearly communicating that any physical or verbal violence or abuse will not be tolerated. This same technology can be used throughout the facility or specifically on high-risk units to communicate when a patient is displaying violent behavior. 

Digital signage can also be used to indicate a room where there is a potentially aggressive or violent patient, and facility-wide alerts can be sent to communicate to entire floors or units when there is an issue. These tools can be customized to hospital codes so that all staff members quickly and easily know what they should do in the event of a violent incident.    

The healthcare industry needs outside support to prevent workplace violence 

Despite advancements in digital technology and tools for healthcare workers, the issue of workplace violence remains a pressing concern for healthcare professionals. Nearly a year ago, thousands of nurses marched in Washington, D.C., asking for changes to nurse-to-patient ratios, the staffing shortage, and workplace violence. And before that, Democratic Representative Joe Courtney introduced H.R. 1195, the Workplace Violence Prevention for Health Care and Social Service Workers Act, aimed at putting processes around workplace safety. Under the act, any company, facility, or organization to employs healthcare or social service workers would be required to:

• Conduct a risk assessment 
• Develop and implement a prevention plan
• Ensure all employees receive workplace violence prevention training 
• Investigate all occurrences of workplace violence 

But the bill, which has been passed by the House of Representatives, has stalled in the Senate–

despite support from the American Nurses Association and National Nurses United, the nation’s largest nurses union. 

The bottom line is that we must  do better by nurses and other healthcare workers. We have the digital technology and tools to arm them with better ways to communicate with patients and with each other. But we need understanding and support from executive leaders. Leaders have an opportunity that is powered to a meaningful degree by technology yet centered on human connection and one that explicitly rejects the notion that violence and safety threats are “part of the job.” It is incumbent upon healthcare executives to elevate the safety of the care environment to the top of their organization’s system-wide strategic plan and make it a key performance indicator for leaders at all levels. 

About Katherine Virkstis
Katherine Virkstis is Vice President of Clinical Advisory Services, at Get Well where she leads the company’s nursing and clinical vision. Katherine has worked with hundreds of executive teams at healthcare organizations in more than 50 countries and is trained as a primary care physician.

References:

1. https://www.ajpmonline.org/article/S0749-3797(22)00507-4/fulltext
2.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206999/
3. https://www.bls.gov/iif/home.htm
4. https://www.pressganey.com/platform/ndnqi/
5. https://www.congress.gov/bill/117th-congress/house-bill/1195/text

Providing patients with a positive health outcome is always the priority for their healthcare provider. The journey to accomplishing this goal can often be an uphill challenge with many variables at play. Providers are tasked with not only delivering a positive health outcome but also with the patient experience and level of satisfaction as they make their way through their healthcare journey. Since the Covid-19 pandemic and the emergence of virtual healthcare, the healthcare industry has witnessed dramatic changes in care delivery and the patient experience.

The pandemic brought forth several issues in healthcare provisions and treatments, including staffing shortages, poor delivery of services, and disparities between the health needs of the population and the competencies of health professionals. The National Institutes of Health (NIH) reports that these challenges have halted or reduced treatments for illnesses like cardiovascular emergencies, hypertension, diabetes, and diabetes-related complications. To correct these inefficiencies – and to ensure positive patient experiences and continued satisfaction – the healthcare industry had to embrace change and implement new strategies.

Understanding the perception of virtual health care

In a survey conducted by the Cleveland Clinic, results showed patients found virtual health care to be just as impactful as in-person visits. These positive responses from patients are essential to recognize, as the survey, in its fourth iteration by the J.D. Power group, shows that telehealth usage is up nearly 30% now compared to when the study was conducted in 2019. 

Several other studies have shown optimistic statistics related to virtual health care: Perhaps the most important to acknowledge are the ones in which nearly 98% of respondents reported being satisfied with telehealth experiences and 91% satisfied with video consultations. To take that a step further, about 88% agreed that virtual consultations were more convenient than in-person visits, and more than 85% believe telemedicine has the same reliability as in-person visits. These studies all support that trust in doctors ultimately correlated with higher patient satisfaction in remote visits.

These findings are also the key to understanding the patient experience and satisfaction when evaluating virtual care. It’s also apparent when looking at how it has impacted no-show rates. According to an NIH report, the rate of missed in-office appointments is more than 35%, significantly higher than the 7.5% rate of telehealth no-show rates. Convenience seems to have a heavy impact on patients here. And when there is a reduction in missed appointments, it creates better efficiency for providers.

In a 2022 McKinsey and Company survey, respondents reported that telehealth appointments were more convenient and were much more satisfied with their care than in-person care. They also showed interest in broader digital healthcare solutions. The same survey, conducted in 2022, showed that nearly 80% of doctors already offer telehealth and in-person visits. 

Enhancing the patient experience through virtual options

Virtual care options can enhance the patient experience and satisfaction through many different avenues of care. Patients and consumers are similar in a few ways. Both expect products and services to be easy to access and obtain through any device – in a timely and convenient way. When providers can offer patients around-the-clock access to virtual care through a best-in-class platform developed with them in mind, patients are placed on the road to positive health outcomes with benefits that heighten their healthcare experience and journey.

In the 21^st century, with how connected we are, people often take to the internet as soon as they do not feel well to try to understand what their symptoms could mean. Still, while they might get hundreds of immediate “answers,” that doesn’t mean they are receiving the correct ones. Patients should instead have access to a trusted provider who can give them 24/7 consistency with the most accurate and personalized attention. Digital health solutions do this in a way that provides patients with relevant, digestible, reliable information. This gives them the confidence to access their care when they need it long-term, which will bolster their engagement. These kinds of results and level of attention to care will not come with random internet searches. 

Patient data can be accessed across both realms with frictionless movement between the physical and digital worlds within a digital platform. This gives providers instant access to essential patient data, improving their accessibility to review medical history, identify patterns and make informed recommendations. This ensures providers deliver top-notch quality care by more accurately diagnosing illnesses and lessening patient risk levels. With access to all this data and insights, structural complexities are removed, workflows are simplified, and the entire experience is streamlined. The result? The improved overall health and well-being of any patient.

All-encompassing solutions for the long-term

Utilizing digital health platforms to streamline information and processes for providers eliminates mundane administrative tasks that otherwise take hours of interpreting manual data. It frees up providers to dedicate more time to their patients. Virtual healthcare platforms can also reduce patient and provider costs, provide positive health outcomes and ensure higher patient satisfaction. 

There’s no doubt: Virtual care is a means to provide patients with affordability, convenience, and 24/7 access to medical professionals. Enabling this access to patients doesn’t just enhance each encounter; it allows them to have a more significant role in their healthcare journey. Virtual care optimizes the patient experience and satisfaction, which will bolster increased satisfaction now and in the long term.

About Keith Algozzine

Keith Algozzine is the co-founder and CEO of UCM Digital Health. A board-certified Physician Assistant, he was formerly the Chief PA of Emergency Medicine for St. Mary’s Hospital in Troy, NY, where he witnessed firsthand the challenges of the modern healthcare system. Keith was also part of the national ER startup management team for Pegasus Emergency Medicine. He represents UCM Digital Health on the American Telemedicine Association Accreditation Advisory Board and serves as an advisor to the Clinical Practice Guidelines Committees dealing with telemedicine considerations for urgent and emergency care.

What You Should Know: 

• Today, the National Institutes of Health (NIH) announced that Dionysus Digital Health, Inc. (Dionysus), a digital health company engaged in the development of precise medical insights using a proprietary digital and epigenetic analysis platform, was selected to move to the next phase of the Rapid Acceleration of Diagnostics  Technology (RADx® Tech) for Maternal Health Challenge. 
• The $8 million cash prize challenge will accelerate the development of technologies to improve maternal health outcomes for those who live in areas lacking access to maternity care. The  CDC recently reported that maternal deaths rose sharply in 2021, with the rates among Black women more than twice as high as those of White women. 
• Dionysus, having passed the Deep Dive Assessment phase, is moving into the Technology  Assessment–and final phase–of the competition, which includes proving their technology works in a real-world test during the remainder of 2023. This last phase will undergo a final review to determine the feasibility of the technology. Winners are expected to be announced in March  2024. 
• The first commercial launch is planned for Q4 2023. 

What You Should Know:

– H1, the connecting force for global healthcare provider, clinical, science, and research information, today announced the availability of indication-level diversity insights in addition to institution, provider, and patient diversity data within its Trial Landscape solution.

– Additionally, H1 has successfully onboarded its first customer – a top 20 pharmaceutical company – onto the H1 Data Network, a new solution that aggregates sponsor-contributed site and principal investigator (PI) performance data from clinical trial management systems (CTMS) to fuel transparency and clinical trial design.  

Healthcare Data Leader H1 Expands its Offerings With New Capabilities

Site feasibility and clinical operations teams at leading pharmaceutical companies use H1 Trial Landscape to discover diverse physician and patient populations and support more representative clinical trial participation. Trial Landscape is an exhaustive clinical trial intelligence repository, incorporating data from public and proprietary sources including over 10 million healthcare providers (HCPs) and over 420,000 clinical trials. It is the first solution of its kind to fully integrate diversity and inclusion insights at the site, HCP, patient, and now, the indication levels – accelerating site and PI research, validation, prioritization, diversity, and selection. 

By moving beyond the site level to include indication-level data, pharmaceutical companies can surface diversity insights on patients at a more granular level to design more inclusive clinical trials. For example, a user can now identify what percentage of breast cancer patients are African American in Georgia so, if they design a clinical trial in that state, they can recruit a representative population. With access to patient data this granular, clinical operations teams can better plan and design diverse clinical trials.

With the new H1 Data Network, pharmaceutical clients can contribute and share their CTMS data with other companies within the network and increase transparency within the industry. Unlike other networks, the H1 Data Network is open to pharmaceutical companies of all sizes, ensuring that midmarket and smaller companies have the same access to clinical trial performance data as big pharma. A top 20 pharmaceutical company is already contributing its data to the H1 Data Network, with many more planned in the near future. 

“Ensuring diversity in clinical trials is not just our mission; it’s a moral imperative and is essential for the development of effective and equitable healthcare solutions,” said Ariel Katz, CEO and co-founder of H1. “We continuously strive to improve our technology and our data to support this mission. These new capabilities are the latest advancements to equip pharmaceutical companies with the insights needed to meet this imperative by creating more diverse clinical trials and sharing that data back with the broader community.”

While the Food and Drug Administration (FDA) has encouraged clinical diversity over the past few decades, it is only now being enforced. The recently enacted 2023 Omnibus Spending Bill (Public Law 117-328) requires that diversity action plans be submitted for clinical trials used by the FDA to decide whether drugs are safe and effective. Other initiatives supporting clinical trial diversity include the National Institutes of Health’s recently released Minority Health and Health Disparities Strategic Plan 2021-2025, which focuses on improving diversity and inclusion in NIH-funded research with updated clinical trial policies and guidelines. With these laws, it will be up to pharmaceutical companies and researchers to engage and recruit diverse patient populations to take part in their trials.

The material cost of COVID-19 has been at the center of public discourse since the early days of the pandemic. In 2020, growth in federal government spending on healthcare increased 36 percent, compared to the 5.9 percent bump in 2019. While the distribution of vaccines has allowed for a version of pre-pandemic life to resume, hospitals are still not recovered from the high rates of hospitalizations that occurred in March 2020, and the indirect costs of the pandemic continue to loom over the American population as a result of strained health systems. 

During the early days, the cost of hospitalizing a patient seemed obvious: the sheer volume of long stays, expensive ventilators, a lack of one-size-fits-all treatment solutions, and the pause of elective surgeries. Now, Covid-19 continues to wreak havoc on our health systems, but in a more covert way. With only 4% of Americans fully boosted as we move into this winter’s ‘triple-demic’ – and long covid impacting the lives of as many as 16 million people on a daily basis – it’s clear that public health officials need to do more in order to support the American population and our struggling health systems. 

The Cost of Healthcare Provider Burnout 

Across the country, healthcare providers are reporting extreme rates of burnout. It is important to underscore that healthcare providers and hospital systems were stressed prior to Covid-19, but the pandemic has exacerbated it. Employment across healthcare is down 1.3 percent, or 223,000 jobs, from pre-pandemic levels. Over 90 percent of nurses said they are considering quitting their jobs by the end of 2022 in a survey, with 72 percent of nurses stating they had already experienced burnout before March 2020. In addition, the increased stress that doctors have experienced is resulting in worse patient care – with 28% of doctors who reported burnout sharing that the quality of care they are providing has significantly declined. 

We are amid a mass healthcare provider exodus, and, according to estimates, each instance of physician turnover costs healthcare organizations at least $500,000, and each instance of staff registered nurse (RN) turnover costs $46,100. Without proper staffing, hospitals are at risk of closure and patients’ health is at risk of worsening. 

The Cost of Hospital Closures 

Before the pandemic, hospitals closed for several reasons, including insufficient staffing, lack of funding, and/or having a large uninsured patient population. Since March 2020, 21 hospitals across the United States, predominantly in rural areas, have closed. Health systems are still recovering from the significant loss of revenue from canceled appointments – according to a report from The Chartis Center for Rural Health, 82 percent of the rural hospitals surveyed said suspension of outpatient services resulted in a loss of at least $5 million per month. 

So, what happens when hospitals and health systems close? 

Rural areas experience more Covid-19-related deaths than urban communities and public health experts attribute these deaths to the rampant hospital closures, as well as a general lack of healthcare providers. It is a vicious cycle: Covid-19 strains hospital systems, healthcare professionals leave, hospitals close, and more patients will die from infectious diseases like Covid-19, the flu or respiratory syncytial virus (RSV) – not to mention the other reverberating public health complications that come as a result of these closures. Vaccinations have helped these hospitals stabilize, but to keep up with covid fatigue and the ever-evolving variants we need a variety of treatments in our arsenal. 

More Covid-19 Treatments Will Bolster Struggling Health Systems  

Increasing the number of vaccinated individuals around the world, in addition to broadening access to effective non-vaccine treatments, such as antivirals and monoclonal antibody therapies, will significantly lessen the impact of the disease on individuals and lessen the burden on the healthcare system. Antiviral treatments have proven to reduce hospitalization, but diversity in treatments is essential to keep up with the ever-evolving Covid-19 variants. Dr. Andrew Pavia, chief of pediatric infectious diseases at the University of Utah Health, was quoted on the effectiveness of antivirals: “If there is anything we know about viruses and antiviral drugs is that eventually, we will see some sort of resistance.” For the time being, antivirals are effective – this is not a call to leverage one type of therapy over another – this is a call to help patients and our health systems survive by equipping healthcare professionals with as many treatments as possible. 

One such treatment that has proven highly effective when applied properly are neutralizing monoclonal antibody therapies. Like antivirals, monoclonal antibodies reduce hospitalization, the risk of death, and shorten the length of the infection – resulting in better patient outcomes and stronger health systems. 

According to Yale Medicine, it is estimated that about three percent of the United States population, or up to 25 million individuals, is considered moderately-to-severely immunocompromised, making them more at risk for serious illness if they contract Covid-19, or other viruses. Monoclonal antibodies are a highly safe and efficacious treatment, which is extremely important for this vulnerable population, especially as a complement to vaccines for prevention. An infusion can reduce the risk of hospitalization by 80 percent or more in a high-risk person, and unlike antivirals, monoclonal antibodies target specific parts of the virus spike protein leading to fewer side effects and interactions with other drugs. 

Collaboration between the government and the biotech industry will be essential for creating a portfolio of therapies to treat a variety of patient profiles who experience a range of Covid-19-related health issues. With our healthcare systems in such a precarious state, investing resources in the development of these treatments will prepare hospitals for future variants that threaten the health of our nation. The hope is that by bulking up our Covid-19 hospital response strategy, our already volatile health system will have a chance to recover, increase individuals’ access to quality healthcare, and ensure a healthier population. 

About Eugene Y. Chan, MD 

Dr. Chan is a physician-inventor. He is currently Chairman, Co-Founder of Abpro, CEO of rHEALTH, and President, CSO of DNA Medicine Institute, a medical innovation laboratory.  He has been honored as Esquire magazine’s Best and Brightest, one of MIT Technology Review’s Top 100 Innovators, and an XPRIZE winner. His work has contributed to the birth of next-generation sequencing, health monitoring in remote environments, and therapeutics. Dr. Chan holds over 60 patents and publications, with work funded by the NIH, NASA, and USAF.  Dr. Chan received an A.B. in Biochemical Sciences from Harvard College summa cum laude in 1996, received an M.D. from Harvard Medical School with honors in 2007, and trained in medicine at the Brigham and Women’s Hospital.  He is one of few individuals who has been in zero gravity. 

What You Should Know:

– Today, at RSNA, Flywheel, a leading data management platform for biomedical research and collaboration announces the creation of a federated data platform for the development of unbiased breast imaging AI.

– Funded in part by the NIH, the federated network will support breast imaging AI research and collaboration—on a scale not previously possible.

Leveraging Flywheel Discovery & Exchange

Two Flywheel technologies underpin the project. Flywheel Discovery, a cohort discovery tool, will connect with the imaging archives, mammography information systems, and EHRs of participating healthcare providers to identify relevant breast imaging data and curate it to common standards. Summaries of the datasets will then be published on Flywheel Exchange, a next-generation platform for research data sharing, where they can be browsed by researchers and licensed for secure use.

Flywheel Exchange keeps patient data in place, simplifying compliance with HIPAA and IRB requirements for researchers. Testing and improving AI through federated analysis and federated learning is accomplished through moving the algorithm(s), rather than the data, across institutional lines. Healthcare providers retain full possession of patient data, while the algorithm being trained “visits” the data where it resides and carries weighted scores back to researchers. As healthcare providers embrace this approach, federated learning has the potential to dramatically improve the amount and diversity of data available to the research community.

Unbiased Breast Imaging AI Benefits

This is crucial because more diverse data is sorely needed by AI developers. Given the shortage of breast imagers in many communities, providers need the most accurate AI tools possible to assist radiologists in increasing efficiency and quality of care.  Flywheel is uniting academic medical centers, community health systems, and essential hospitals on its network, further building the catalog of data that AI developers, life sciences companies, and other researchers can license to power their research.

 “We are creating the complete data science stack to address the all-too-common challenges of healthcare researchers and AI developers,” said Jim Olson, CEO of Flywheel. “This solution combines both federation capabilities and the data science infrastructure to capture data and ensure consistent curation. Without that, researchers spend 80% of their time on menial data-wrangling tasks. We’re creating the tools for data owners and data consumers to find each other and collaborate with unprecedented efficiency so they can make breakthroughs in care.”

What You Should Know:

– Digital health company Geneial announces a $2.3M grant from the National Human Genome Research Institute to fund the development of their secure, decentralized platform.

– Geneial will use $2.3M NIH award to build private, decentralized data platform facilitating research of genetic diseases. Geneial’s platform will connect researchers of rare genetic diseases with relevant data while preserving patient privacy. Geneial’s platform aims to help researchers leverage large datasets of rare disease populations, incentivizing custodians of biomedical data to grant researchers access to highly targeted biomedical data. This unique new award is part of a highly selective “Small Business Transition Grant for Early Career Scientists” program with fewer than ten companies funded to date. 

– In previous work, Geneial demonstrated a proof-of-concept for HIPAA-compliant privacy-preserving registry search using the Xia-Gibbs syndrome (XGS) registry at the Baylor College of Medicine Human Genome Sequencing Center (HGSC) – led by Richard A. Gibbs, AC Ph.D., a global leader in genetics. “We are honored to have the backing of the NIH and HGSC as we realize our mission of advancing genetic and personalized medicine,” shared Adam Hansen, Ph.D., CEO of Geneial and Principal Investigator of this project.

What You Should Know:

– Eko, a digital health company applying machine learning in the fight against heart and lung disease, today announced that it was awarded a $2.7M Small Business Innovation Research (SBIR) Direct Phase II grant by the National Institutes of Health’s (NIH) Department of Health and Human Services (HHS).

– The grant will fund the development of a machine learning algorithm that detects and stratifies pulmonary hypertension (PH) using phonocardiogram (PCG) and electrocardiogram (ECG) data provided by Eko’s smart stethoscopes.

Improving Clinical Decision-Making Through New Machine Learning Algorithm

Pulmonary hypertension is a severe condition that occurs when the pressure in the vessels that carry blood from the heart to the lungs is higher than normal, causing undo stress on the heart. PH affects up to 1% of the global population and is a marker of poor health outcomes.¹ PH can cause premature disability, heart failure, and death. Unfortunately, delays of over two years frequently occur between the onset of symptoms and diagnosis of severe kinds of PH.  The gold standards for diagnosing PH are echocardiography and right heart catheterization, which are costly, invasive, and require a heart specialist. ECG-based AI models have been clinically proven to improve the diagnosis of PH but are challenging to deploy.³ To address this challenge, Eko formed a research partnership with Lifespan Health System’s Cardiovascular Institute to collect real-world PCG and ECG data using the Eko DUO ECG + Digital Stethoscope. This data will help develop an algorithm that can detect PH and stratify its severity. This easy-to-deploy early identification tool aims to diagnose PH earlier and more accurately, leading to beneficial interventions that can save patients’ lives

“The major goal of this study is to determine whether an Eko algorithm based on phonocardiography coupled with electrocardiography can identify the presence and severity of pulmonary hypertension when compared to the current gold standard,” said Dr. Gaurav Choudhary, Principal Investigator and Ruth and Paul Levinger Professor of Cardiology and Director of Cardiovascular Research at the Alpert Medical School of Brown University and Lifespan Cardiovascular Institute. “This machine learning algorithm has the potential to be a low cost, easily implementable, and sustainable medical technology that assists healthcare professionals in identifying more patients with pulmonary hypertension.”

This award marks Eko’s fourth SBIR grant from the NIH, bringing their total funding to date from the NIH for cardiopulmonary machine learning development to $6M. A previous $2.7M grant, awarded to the company in July of 2020, funded the collaborative work with Northwestern Medicine Bluhm Cardiovascular Institute to validate algorithms that help healthcare professionals (HCPs) identify pathologic heart murmurs and valvular heart disease (VHD) during routine office visits. That grant for VHD directly contributed to the FDA clearance and commercialization of Eko Murmur Analysis Software (EMAS) – the first and only machine learning algorithm to assist HCPs in identifying structural heart murmurs using a smart stethoscope.

Eko is advancing how healthcare professionals detect and monitor heart and lung disease with its innovative suite of digital tools, patient and provider software, and AI-powered analysis. Its FDA-cleared platform is used by hundreds of thousands of healthcare professionals worldwide, allowing them to detect earlier and with higher accuracy, diagnose with more confidence, manage treatment effectively, and ultimately give their patients the best care possible.

More than 50 million adults in the United States – more than 20% – suffer from chronic pain, and more than 19.6 million adults have pain that interferes with their lives more days than not. The estimated cost of chronic pain is $635 billion – more than heart disease and cancer combined – due to the number of days missed from work, treatment costs, and other factors. Chronic pain is the leading cause of disability, but the current pain treatment system isn’t working. This is because it hasn’t recognized the new science around chronic pain. After decades of trying a myriad of costly, largely ineffective approaches such as surgeries, injections, and pharmaceuticals, the pain care paradigm is shifting to consider the newest science, revolutionizing the pain treatment industry.

The Outdated Pain Model

Chronic pain is one of the leading causes of waste in terms of low-value medical care in the United States due to the current “kitchen sink” approach to pain. This idea of throwing everything at the pain – such as costly and ineffective surgeries and harmful pharmaceuticals – in hopes of curing it, yet more than 50 million people are still suffering from chronic pain.

Surgeries are a continuous part of treatment plans, despite clinical data that proves their ineffectiveness. In several studies, there was no significant difference in pain among patients who participated in surgeries and procedures from those who received the placebo treatment. In a study from the University of Oxford, patients with shoulder pain were given a decompression surgery to alleviate pressure and relieve pain, a fake surgery in which there was only an incision but nothing removed, and no treatment. The groups with the placebo surgery and real surgery both saw the same pain relief.

There are many more studies that showcase the results of these costly approaches, finding the benefits are not statistically significant compared to placebo treatments in research. This is in large part due to the effect hope and expectations can have on a person’s body. Patients had hope that they would see a difference because treatment was occurring, even from placebo groups, so the study found both groups that received treatment saw relief from pain.

Medications have also traditionally been a large component of the historical treatments of pain. Most notoriously, opioids rose to popularity in the late 1990s, unknowingly causing mass addiction to the drugs for pain relief reasons, and leading to the opioid epidemic. While opioids can help with pain temporarily, they can actually increase long-term pain sensitivity, known as opioid-induced hyperalgesia.

Despite studies like these, pain treatment hasn’t changed. That is, until now. The World Health Organization recently released its newest diagnostic code, ICD-11, which allows physicians to correctly diagnose chronic primary pain – pain that arises as a result of the brain’s overzealous pain signaling. Common chronic primary pain presentations include fibromyalgia, lower back pain, shoulder pain, migraines, irritable bowel syndrome, and many arthritic presentations. In primary pain, the pain itself is the problem; whereas in secondary chronic pain, the pain is secondary to – or caused by – a problem in the body. Understanding the underlying causes of chronic pain is key to treating it more effectively.

Finding the root of pain

It’s largely believed that chronic pain is due to a structural problem in the body and that surgeries and procedures are a key way to address the problem. However, while abnormalities, such as bulging discs, can cause pain in some cases, they’re often unrelated to pain. For example, a recent study found that anatomical findings are often present in pain-free populations: 87% of pain-free necks have bulging discs, 72% of pain-free shoulders have superior labral tears, and 97% of pain-free knees show abnormalities of some kind. These body characteristics don’t always dictate pain. Instead, there are a number of changes in the brain that can cause chronic pain.

Chronic pain engages a different set of brain circuits than acute pain. Northwestern University recruited a sample of people who had recently injured their backs. 12 weeks after their injury, the pain showed itself in the typical areas of the brain where pain is processed. After that point, half of the patients recovered, while the other half of patients went on to experience chronic pain one year later. In these patients, other areas of the brain were engaged. These engaged areas were areas where emotions are prominent. In this transition from acute to chronic pain, it shifted to the regions of the brain related to learning and meaning. This indicates that pain is a learned activity, causing the pain to persist independently of the pain input from the body.

The new science and life beyond pain

There are a large number of changes in the brain that can drive chronic pain, and not all chronic pain is alike. The WHO’s new diagnostic code is changing the way we treat chronic pain by differentiating primary chronic pain from all other types of pain, ensuring treatments can effectively treat the appropriate diagnosis of pain. Pain management solutions like Lin Health are relying on the latest science to provide a proper diagnosis to ensure pain is properly treated. In fact, my research in JAMA looked at pain reprocessing therapy (PRT) as a way to support that psychological treatment for chronic pain is effective with long-lasting relief. The study found that changing patients’ beliefs about the causes and threat value of pain may provide substantial and durable pain relief for people with chronic back pain. Two-thirds of chronic back pain patients were pain-free or nearly so after treatment, as compared to less than 20% of patients from the control group.

The traditional view has been that pain is a direct sensory readout of tissue damage, but there is a new model for viewing pain as a learning signal for guiding behavior. The chronic pain treatment industry is only just beginning to shift with this newest research. The more streamlined the industry can make treatment of pain, the more effective and cost-efficient it will be.

About Yoni Ashar, PhD
Yoni is a clinical advisor at Lin Health, a digital solution for chronic pain, he is also a clinical psychologist, neuroscientist, and father of three. Yoni’s research uses functional MRI brain imaging, natural language processing, and other tools to understand how mind and brain processes influence health and chronic pain. Yoni is an NIH-funded postdoctoral associate at Weill Cornell Medicine. He completed his doctorate at the University of Colorado Boulder. His research in chronic pain has been featured in several news outlets, including the Wall Street Journal, the Washington Post, and CBS.

What You Should Know:

– Mount Sinai spinout, PreciseDx, today announced that its AI-enabled digital pathology is the first proven to detect early-stage Parkinson’s disease, according to a recent research study.

– The study, conducted in collaboration with Michael J. Fox Foundation, identified that PreciseDx’s technology can accurately diagnose Parkinson’s disease in living patients prior to the severe onset of symptoms.

Challenges Diagnosing Parkinson’s Disease

Diagnosing Parkinson’s disease is challenging at all stages due to variable symptoms, comorbidities, and mimicking conditions, with definitive diagnosis only coming postmortem. This groundbreaking study found that PreciseDx’s AI-enabled technology is able to facilitate a conclusive diagnosis of Parkinson’s, providing critical information for earlier treatment.

PreciseDx’s AI Morphology Feature Array was able to detect Parkinson’s pathology in image patches from biopsy samples with 99% sensitivity and 99% specificity as compared to expert annotated ground truth. The AI edged out the human pathologist with an accuracy of 0.69 versus 0.64 in the prediction of clinical Parkinson’s disease status.

PreciseDx’s MFA approach to feature extraction and analysis enables new algorithms to be developed and validated against clinical endpoints. This is extremely valuable to create new diagnostic tests, accurate and reproducible diagnosis, prognosis, patient selection of therapy for a wide range of conditions.

“Traditionally, pathology grading systems look at a few morphology components to make a diagnosis. Unlike any human-powered grading method, PreciseDx’s AI Morphology Feature Array (MFA) can examine thousands of different features and leverage those relationships between them,” said John F. Crary, MD-PhD, a Professor in the Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health at the Icahn School of Medicine at Mount Sinai. “This industry-changing study has shown that we need to revitalize the way we think about pathology and lean into using AI to detect diseases more accurately, such as PD. This enlightens the industry to a direct case study into how computational pathology can truly advance medicine in terms of accurately identifying and detecting diseases.”

For more information about the study, visit https://pubmed.ncbi.nlm.nih.gov/35164870/

What You Should Know:

– Israeli startup Salignostics, the developer and provider of rapid saliva-based tests for early pregnancy detection, as well as COVID-19, cardiac risk, malaria, and other diseases, has closed an $8 million Series A funding round from private investors headed by angel investor Avigdor Orlinsky.

– The company has raised $16M to date to support development, commercialization, and marketing efforts for the tests in Israel and overseas. It will also support the launch of a new plant currently under construction in the Lavon Industrial Zone in Northern Israel.

Transform Saliva Into A Reliable Body-Fluid for Lateral Flow Immunoassays

Salignostics was founded in 2016 by a team of researchers at the Hebrew University of Jerusalem, (HU) who have many years of experience in cracking the secrets of saliva: Professor Aaron Palmon, a world-class researcher in saliva, and currently head of the Authority of Research Students in Experimental Sciences at HU; Dr. Omer Deutsch, who serves as CEO; Dr. Guy Krief, Deputy CEO and Director of Business Development; Dr. Raluca Cohen, Chief Scientific Officer; and Dr. Yoav Neumann, Senior Researcher.

Following years of saliva scientific research, the five founders began commercializing their intellectual property through Yissum, the HU technology transfer company, and developed user-friendly products to accurately detect a range of physiological conditions including pregnancy and COVID-19. The company also developed products to detect malaria, cardiac risk, Helicobacter pylori and other diseases.

During development of the tests, the company raised pre-seed and seed capital from private investors and received four grants from the Israel Innovation Authority.

The Salignostics’ team used their intellectual property to develop and supply SaliCov – a compact and accurate self-test kit for diagnosing COVID-19. SaliCov pilot tests demonstrated its efficiency in outbreak prevention by breaking the infection chain in the earliest stages of the disease at educational and community centers across Israel. The product is currently in use in Spain, and the company recently signed agreements for large-scale purchases with parties in other countries.

The kit has obtained Medical Devices and Accessories (AMAR) approval from Israel’s Ministry of Health for institutional Point of Care use, European CE-IVD approval to market the kit across the European Union, and a prestigious RADx (Rapid Acceleration of Diagnostics Initiative for COVID-19) grant financed by the US National Institutes of Health (NIH).

Another flagship product is SaliStick – the world’s first rapid saliva-based pregnancy test kit. The kit is based on revolutionary technology which detects the pregnancy hormone β-hCG in saliva. Salistick has obtained European CE certification and Medical Devices and Accessories approval from Israel’s Ministry of Health.

“The capital raised will enable us to leverage the full business potential of our proprietary platform, and benefit from the strong pending demand. The platform sets a new and breakthrough standard for rapid tests in general and saliva-based tests in particular. The future diagnostics world will become increasingly accessible to personal and home use, which can be done anywhere by anyone. Salignostics’ technology realizes this vision,” said Dr. Omer Deutsch, co-founder, and CEO of Salignostics.

What You Should Know:

– Selux Diagnostics, Inc., a personalized diagnostics company to combat superbug infections and fight antibiotic resistance raises $50M in Series C financing led by RA Capital Management, with participation from Sands Capital, Schooner Capital and Northpond Ventures.

– The funding will support the U.S. commercial launch of its Next-Generation Phenotyping (NGP) rapid Antimicrobial Susceptibility Testing (AST) platform.  

Precision diagnostics for infectious diseases

The U.S. Centers for Disease Control and Prevention (CDC) has cited bacterial resistance to antibiotics among the world’s deadliest and costliest health threats. Using current technologies, doctors must overprescribe powerful, broad-spectrum antibiotics for days while waiting for key diagnostic results to direct personalized therapy.

 Selux has developed a ground-breaking diagnostic tool to fight antibiotic resistance. The system enables physicians to quickly identify the most effective antibiotic for each individual patient to reduce the overuse of broad-spectrum drugs and slow the evolution of superbugs.  Selux’s NGP system provides same-shift AST results. Consequently, physicians can prescribe optimal treatment 3-5 days sooner, reducing hospital stays and halting the cycle of antibiotic overuse and the ongoing rise of superbugs. The company recently received a $2.8M award from NIH and has a milestone-based contract with BARDA worth up to $45M. Selux previously raised $25M in its Series B round.  

“This Series C funding allows us to build out our commercial team and positions Selux to transform infectious diseases patient care by establishing NGP as the new standard,” said Steve Lufkin, CEO of Selux Diagnostics. “Selux’s combination of unparalleled time to results and antibiotic test menu together with its high throughput will impact patient care and preserve the efficacy of critical antibiotics. The Selux platform will become the system of choice for healthcare providers dedicated to providing best-in-class septic and other infectious diseases patient care.”

One of the many acute challenges during the pandemic has been the departure of approximately 18% of the U.S. healthcare workforce,⁴ resulting in staffing shortages in hospitals. This has impacted the well-being of the remaining healthcare practitioners ⁵ as well as their patients – many of whom are deferring care that is vital to disease management and overall maintenance of health,^6,7 or who do not have access to timely emergency care.¹ Though such challenges may be perceived as insurmountable in the face of overcrowded emergency rooms, burnout of healthcare personnel, and patients who are reluctant to seek care, the incorporation of artificial intelligence (AI) and machine learning (ML) into healthcare systems may alleviate some of these burdens. 

AI and ML have been widely used in consumer applications across industries, yet their potential value in healthcare has been largely unrealized. As health systems continue to struggle in the grip of the pandemic, the time has come to push patient risk assessment into the future with novel tools, such as machine learning. By incorporating AI and ML into electronic healthcare record (EHR) systems, hospitals with limited resources – whether it be due to geographic isolation or staffing shortages –may improve patient care and outcomes. 

Many prognostic calculators and risk stratification tools require the use of information from patient assessment and/or clinical gestalt, which is, as of late, often being done in clinical settings that lack adequate staffing. Traditional risk scoring systems are also often cumbersome and impede clinical workflow by requiring patient data to be manually input by the examining physician.^8–10 In contrast, AI and ML risk stratification tools have the ability to harness the wealth of information contained within EHR data to provide automated risk projections using minimal amounts of patient data. These may be used to supplement clinical assessments and disrupt many of the antiquated practices in healthcare.  

Predictions made by these tools use individual health data and are reflections of an individual’s dynamic health processes. They characterize trends and stratify a patient’s risk of experiencing a particular outcome based on the individual. Despite this, AI and ML remain underutilized in healthcare. This may be due to the relative novelty of ML in medicine, a general lack of understanding about how ML works and why certain predictions are made –often called black box predictions – and perceived challenges regarding the implementation of such tools. Realistically, ML tools can be implemented quickly and with minimal training to the end-user and serve as clinical decision support (CDS) tools to optimize limited clinician time. 

In the context of the ongoing global health emergency, AI and ML-based CDS tools have the potential to emerge as an invaluable resource to overburdened care teams by facilitating prioritization of medical care for patients based on individual risk levels. In hospitals that are overcrowded or have inadequate staffing, ML-based risk assessments identify patients who are in more immediate need of care and guide the allocation of personnel and health-related resources. They can also aid with determining hospital admission or identify the need to transfer a patient to a higher level of care. Triage, in this manner, could ensure that only patients in immediate or near-immediate need of treatment are under the direct care of a healthcare provider (HCP). With ongoing staffing shortages and hospitals pushed to the brink of capacity, this could enable HCPs to provide more precise care to fewer, sicker patients, as opposed to providing less precise care to a greater number of non-urgent patients. 

Aside from staffing shortages among the general U.S. healthcare workforce, the challenges faced by rural hospitals are multi-pronged. In contrast to larger, well-funded hospital facilities, rural hospitals are experiencing a disproportionate dearth in personnel during the COVID-19 pandemic, particularly nurses.^{11 12}  Rural hospitals also frequently have limited financial resources and lack immediate access to acute-care specialists, unlike larger hospital settings where these specialists are often on staff. Health technology is a mechanism for improving health equity among these individuals who are often marginalized in terms of health access, as shown with telestroke¹³ initiatives. Telestroke is a remote system of providing expert patient assessment and managing patient care with regards to stroke. It has been incorporated into a number of rural healthcare systems and contributed to improved treatment time and outcomes for patients hospitalized with a stroke. ¹⁴ Despite these improvements, broad uptake is hindered by the high costs of telehealth interventions and difficulty retaining remote, specialized teams, which may not be reimbursable.¹⁵  

With autonomous projections based on individual data, ML and AI are critical to unlocking equitable, personalized medicine that can impact individuals in settings where access to advanced healthcare is provided on an as-needed basis. By identifying which patients are in the greatest need of acute care, healthcare providers will be better enabled to focus limited tangible and personnel resources on high-risk patients or request the services of a specialist who may not be immediately available on-site in a timely manner. Enabling healthcare providers to focus their care on high-risk patients results in resources that can be rationed and allocated for patients and procedures that require immediate attention.

It is inarguable that we have witnessed the multifaceted and detrimental impacts that COVID-19 has had on healthcare delivery and patient outcomes in the U.S. and beyond. However, it may have also inadvertently shepherded us into the future, where highly accessible, personalized medical tools are at the fingertips of healthcare providers to guide and empower clinical decision-making.  

About Andrew Pucher

Andrew serves as the Chief Executive Officer and a member of the Board of Directors at Dascena, Inc. Andrew is a strategic healthcare leader, with extensive experience in developing new product markets and scaling commercial businesses.  Prior to joining Dascena, Andrew served as Chief Corporate Development Officer at Tilray until its $3bn acquisition. Previously, Andrew was a Managing Director at Goldman Sachs, where he worked for over a decade as a healthcare investment banker financing and advising leading biotech, pharma, and medical device companies. 

References

1. Emergency Department Crowding: The Canary in the Health Care System | Catalyst non-issue content, https://catalyst.nejm.org/doi/full/10.1056/CAT.21.0217 (accessed 10 January 2022).

2. Committee on Guidance for Establishing Crisis Standards of Care for Use in Disaster Situations, Institute of Medicine. Crisis Standards of Care: A Systems Framework for Catastrophic Disaster Response. Washington (DC): National Academies Press (US), http://www.ncbi.nlm.nih.gov/books/NBK201063/ (2012, accessed 11 January 2022).

3. Hick JL, Hanfling D, Wynia MK, et al. Crisis Standards of Care and COVID-19: What Did We Learn? How Do We Ensure Equity? What Should We Do? NAM Perspect; 2021: 10.31478/202108e.

4. About 1 in 5 healthcare workers have left medicine since the pandemic began — Here’s why, https://www.beckershospitalreview.com/workforce/about-1-in-5-healthcare-workers-have-left-medicine-since-the-pandemic-began-here-s-why.html (accessed 10 January 2022).

5. Burnout in Hospital-Based Healthcare Workers during COVID-19. Ontario COVID-19 Science Advisory Table. DOI: 10.47326/ocsat.2021.02.46.1.0.

6. Delays and Disruptions in Cancer Health Care Due to COVID-19 Pandemic: Systematic Review | JCO Global Oncology, https://ascopubs.org/doi/10.1200/GO.20.00639 (accessed 10 January 2022).

7. Splinter MJ, Velek P, Ikram MK, et al. Prevalence and determinants of healthcare avoidance during the COVID-19 pandemic: A population-based cross-sectional study. PLOS Med 2021; 18: e1003854.

8. Kansal A, Green CL, Peterson ED, et al. Electronic Health Record Integration of Predictive Analytics to Select High-Risk Stable Patients With Non–ST-Segment–Elevation Myocardial Infarction for Intensive Care Unit Admission. Circ Cardiovasc Qual Outcomes 2021; 14: e007602.

9. Ebinger J, Henry T, Kim S, et al. Development and Evaluation of Novel Electronic Medical Record Tools For Avoiding Bleeding After Percutaneous Coronary Intervention. J Am Heart Assoc 2019; 8: e013954.

10. Sahay S, Tonelli AR, Selej M, et al. Risk assessment in patients with functional class II pulmonary arterial hypertension: Comparison of physician gestalt with ESC/ERS and the REVEAL 2.0 risk score. PloS One 2020; 15: e0241504.

11. Rural Hospitals Can’t Find the Nurses They Need to Fight COVID, https://pew.org/3Dw86s9 (accessed 11 January 2022).

12. Grimm CA. Hospitals Reported That the COVID-19 Pandemic Has Significantly Strained Health Care Delivery. 62.

13. Demaerschalk BM, Berg J, Chong BW, et al. American Telemedicine Association: Telestroke Guidelines. Telemed J E Health 2017; 23: 376–389.

14. Lazarus G, Permana AP, Nugroho SW, et al. Telestroke strategies to enhance acute stroke management in rural settings: A systematic review and meta‐analysis. Brain Behav 2020; 10: e01787.15. Zachrison KS, Richard JV, Mehrotra A. Paying for Telemedicine in Smaller Rural Hospitals: Extending the Technology to Those Who Benefit Most. JAMA Health Forum 2021; 2: e211570.

The clinical trial industry is, once again, at an uncertain crossroads. And while it might be assumed that the outsized impact of the COVID-19 pandemic has resulted in the inability to recruit patients for trials, it is instead, a challenge generated, over time, by the industry itself. Thankfully, there is an opportunity to change course.  

It’s no secret that research studies and clinical trial sites struggle with recruitment. In fact, the National Institutes of Health (NIH) states that of all terminated clinical trials, 55 percent were terminated due to low accrual rates. In total, around 80 percent of research studies fail to meet their enrollment goals in their projected timeframes. These kinds of delays create a significant challenge for those conducting the trials and further delay getting live-saving drugs to market. 

Without enough willing participants, research cannot be conducted properly enough to deliver meaningful results. And while the industry continues to invest billions of dollars to solve recruitment challenges,  the number of failed studies continues to increase. It can be especially discouraging when promising drugs or treatments are delayed, or worse, terminated entirely simply because the sites were unable to recruit and/or retain enough participants.

In recent years, the pharma industry has supported a more ‘patient-centered’ approach to clinical trial delivery. In theory, this methodology is brilliant, but only if every critical touchpoint across the drug delivery timeline is supporting this approach, this includes the patients’ experience at the study sites. 

Historically,  trial sites were to blame when studies failed to enroll. It’s no secret that during study feasibility, site staff often overestimate the volume of qualified patients they have in their database. And if they do have patients that meet study criteria, in many cases, the patient is not motivated to participate in a trial. 

It’s also a well-known fact that site-based clinical teams have very limited bandwidth. While the priority is to onboard and retain study participants, these same resources are also expected to mine their patient database and create a pipeline of qualified study participants. 

The clinical trial delivery model is clearly flawed, yet absolutely fixable. Successful study recruitment and retention can be achieved, only if weaknesses in the clinical trial supply chain are addressed head-on. 

Patients want — and should be — more involved when it comes to making decisions about their treatment. More importantly, clinical trials should always be a treatment consideration. The trial delivery model needs to do a better job prioritizing the patient. No patients, no trial.  As if study enrollment wasn’t challenging enough, in a post-pandemic world, as stated above, patients are taking a more active role when it comes to treatment planning. These empowered patients also have expectations that need to be met, especially when it comes to their healthcare.

In order to improve study recruitment and retention, adjustments need to be made at multiple touchpoints along the patient recruitment journey, not just the study sites.  

Nothing is more frustrating for a motivated potential study participant, who completes the study pre-qualification process, appears to be a match and selects a study site — and receives NO RESPONSE from the site. For cancer patients, these delays are not only stressful and demoralizing, but they also have the potential to be deadly. Eventually, typically within 48 – 72 hours, these patients “give up” and settle for the standard of care. The loss of this study participant is a hit to both the patient and the pharma industry at large.

Making sure that a qualified patient successfully enrolls in a study is a team effort. It should not be assumed that the study site owns the responsibility of achieving this goal. Success requires a team effort. If a cancer patient applies to a study with the aid of a clinical support team, the chances of that patient converting into a study participant increase exponentially. A lead transfer is triggered when the prospect selects their preferred study site. When a dedicated team member facilitates the transfer process they not only flag a pre-qualified lead to site staff, they establish a touchpoint. With an identified point of contact, the applicant remains engaged as they take a more active role in their fight against cancer.

Hand-delivering clinically-matched leads, ready to participate in a trial, significantly reduces the burden on site staff. With most of the pre-qualification process complete, the site can focus on getting the patient to sign the ICF.   

About Tzvia Bader

Tzvia Bader, CEO and Co-Founder of Trialjectory, is a savvy and experienced entrepreneur, with decades of experience in business development, product marketing and strategy. As a cancer survivor herself, Tzvia is currently leading the charge in developing a cutting-edge AI-powered decision assistance platform for cancer patients that matches them with advanced treatments based on their medical profile and uses big data to compare their treatment to patients like them by cancer subtype, phase, and biomarker, enabling patients and their oncologist to make the best possible treatment decisions for their cancer journey.

What You Should Know:

– Rendever, a Boston-based virtual reality (VR) platform built to help seniors overcome social isolation through shared experiences, announces that it has been awarded a $2M Phase II Grant from the National Institute on Aging (NIA), a division of the National Institutes of Health (NIH).

– This grant will fund a registered multi-site clinical trial, in conjunction with the University of California Santa Barbara, to further Rendever’s continued research on the effects of VR on seniors. The focus of the research is to evaluate the impact of VR-based virtual family engagement for seniors and the differences in effect across various levels of cognitive impairment (MCI, mild to moderate AD/ADRD).

How VR Reduces Harmful Effects of Social Isolation in Seniors

The Phase II Grant builds on Rendever’s previously awarded Small Business Technology Transfer (STTR) Phase I Grant to measure the impact of Rendever’s engagement platform. The initial pilot data confirmed the positive impact that virtual family engagement has on both residents and their family members living at a distance. Residents experienced decreased negative emotions and feelings of isolation, increased positive emotions and engagement with their family members, and overall improved quality of life. Family members reported similar mental health benefits along with significant decreases in caregiver guilt after using Rendever’s VR platform with their loved ones.

The data collection is expected to be conducted through the end of 2022 and the study will include approximately 400 participants in 12 senior living communities in the greater Boston area and central California. With uncertainty around the COVID-19 pandemic, the team is also prepared for remote collaboration for safety purposes as needed.

“We see the first-hand effects of our virtual reality platform every day through our community partners. We’re trailblazing toward a future in which communities thrive beyond the four walls of the physical building. This clinical trial is truly the first of its kind, and will help us continue to push the boundaries of what we think is possible through VR,” said Kyle Rand, Cofounder and CEO of Rendever. “The future of the industry will be enabled through technology that not only builds thriving communities, but also maintains the important social connections that exist before a resident moves in. We are incredibly grateful for the hard work and enthusiasm that is going into this study, and are eager to officially launch Phase II.”