When you see each patient a million times a day...
...You see the bigger picture.
Every second, our FDA-cleared AI-based ecosystem compares 20+ physiological signals* from a wearable biosensor with data from millions of other chronic patients. The result? Powerful pattern recognition designed to help clinicians predict and prevent deterioration before it happens.
When you see each patient a million times a day... You see the bigger picture.
Every second, our FDA-cleared AI-based ecosystem compares 20+ physiological signals* from a wearable biosensor with data from millions of other chronic patients. The result? Powerful pattern recognition that helps predict and prevent deterioration before it happens.
We're powering personally predictive care...
so everyone can see better outcomes.
What if patients suffering from heart failure, COPD, chronic pain, or cancer could spend less time in hospitals and more time feeling confident and cared for at home? What if networks, clinicians, and payers could turn fewer readmissions into a higher level of care for all? And what if drug companies could more dramatically demonstrate, in real-time, the physiological impact and value of pharmacotherapy candidates?
At Biofourmis, we use patient physiology data and advanced analytics to turn those "what-ifs" into "ah-has" for some of the world's most respected healthcare providers and pharmaceutical companies—collaborators like Novartis, Chugai, Brigham and Women's Hospital, and Mayo Clinic that use our clinically validated, predictive platform to more precisely manage, intervene, and treat chronic patients in a way that's proactive and liberating. That's the power of personally predictive care.
The Biovitals® platform shows you more than patient data.
It can help show you patient futures.
Our Biovitals® platform collects and interprets vast amounts of population metadata and compares it to real-time patient physiological signals to provide a clearer picture of chronic patients and their disease trajectory—a real-time picture designed to help clinicians predict and prevent serious medical events. Its actionable insights powered by machine learning, deep neural networks, and a clinical-grade Everion® wearable.
Predict and prevent costly medical events with a modular, user-friendly platform.
Biovitals® delivers actionable information by bringing disease, data, machine-learning, and clinical-grade hardware together in one customizable ecosystem. Learn how we can tailor Biovitals® to improve real-world outcomes for the unique needs of health systems, payers and pharmaceutical companies.
Health Systems
Improve clinical outcomes by reducing readmissions and ED visits
Improve workflow efficiencies, care team capacity and ongoing communication with patients
Realize more rapid personalized treatment and communication for efficient management of patients with complex chronic conditions
Payers
Reduce overall healthcare expenditures while improving clinical outcomes
Improve quality of life for members with complex chronic conditions
Deliver members more targeted and timely intervention and engagement support based on their personalized needs
Pharmaceutical Companies
Augment drug efficacy and outcomes using drug + digital intervention
Accelerate development time frames by accelerating clinical trials using digital tools
Clinical evidence and science guides everything we do
Around the world and across multiple collaborations and studies, our Biovitals® Platform is helping clinical teams see patients like never before.
BiovitalsHF® Treatment Algorithms
Circulation, AHA Journal
This RCT demonstrated that an algorithm-drive, navigator-administered medication optimization program enhanced implementation of GDMT compared with usual care in patients with HFrEF. The data supports remote titration using our Biovitals® Treatment algorithms for personalized, sequential, stepped titration of guideline-directed heart failure medication therapies.
This RCT demonstrated substitutive home hospitalization reduced cost, healthcare use, and readmissions while increasing physical activity compared with usual hospital care. Patients were monitored using wearable biosensor patch and machine-based algorithms, which produced alarms for review by both nurse and physicians.
This study demonstrated the ability of our FDA-cleared Biovitals® Analytics Engine to detect subtle physiology changes precursor to decompensation in patients with chronic condition. The data validates its unique features – device and disease agnostic platform for continuous physiology monitoring.
RhythmAnalytics® - Deep Learning for Arrhythmia Detection
arXive.org – Cornell University
The study demonstrates the capability of our FDA-cleared RhythmAnalytics® platform to detect >15 types of cardiac arrhythmias using continuous ECG recordings. The overall performance of RhythmAnalytics® outperformed a panel of cardiologists and other industry leading detection models
Everion® biosensors for monitoring Cancer Patients
Oncology – International Journal of Cancer Research and Treatment
The study demonstrated strong feasibility and patients’ acceptance of remote monitoring using Everion® and companion app in palliative cancer patients. 83% of patients completed the whole study by wearing the Everion® biosensor and 73% used the companion app to complete daily digital questionnaires (pain and distress scale)
Comfort and acceptability of Everion® in Soldiers
IISE Transactions on Occupational Ergonomics and Human Factors
The study investigated the wearing comfort of nine devices for monitoring physiology and physical
activity in soldiers. Results concluded Everion® achieved the highest score associated with wearing
comfort and acceptability during day-to-day military training. This study was a collaboration between
Switzerland, Netherlands, United States of America and United Kingdom through NATO Panel HFM-
260.
We're proud to collaborate with some of the world's most respected healthcare organizations, research hospitals, and biopharma companies. Together, we're improving patient outcomes, advancing clinical research, reducing healthcare costs, and accelerating drug research and development.
I've seen it said before that year-ahead predictions are like weather reports: Everyone reads them, but almost no one looks back later to see whether they were accurate. Still, since when has that stopped anyone from indulging in this pastime as the calendar turns from December to January?
The clinical community will increase their use of federated learning approaches to build robust AI models across various institutions, geographies, patient demographics, and medical scanners. The sensitivity and selectivity of these models are outperforming AI models built at a single institution, even when there is copious data to train with. As an added bonus, researchers can collaborate on AI model creation without sharing confidential patient information. Federated learning is also beneficial for building AI models for areas where data is scarce, such as for pediatrics and rare diseases.
In November, when the Centers for Medicare & Medicaid Services expanded its acute hospital at home program, it granted immediate waivers to six health systems with extensive experience providing acute hospital care at home, including Brigham and Women’s Hospital in Boston. In a recent interview, David Levine, M.D., M.P.H., who leads Brigham’s program, discussed its plans to scale up and the overall impact of the CMS waiver program.
"In 2021, we'll see a continued move from 'pay-per-pill' to pay-for-value when it comes to drug therapy. This transition will be accelerated by technology such as clinical-grade wearables, remote patient monitoring, patient-facing apps, and AI-powered analytics.
We're helping some of the most respected names in healthcare deliver measurably better outcomes. Let us show you what personally predictive care can do for your organization.
