Biofourmis, a Singapore-based health analytics platform, has entered into a collaboration with Brigham and Women’s Hospital in Boston, US to co-develop improvements to their proprietary analytics engine, Biovitals™ for Brigham’s Home Hospital Programme.
Patients are cared for in their home instead of the hospital in Brigham’s Home Hospital Programme, with the aim of providing the right care to the patient at the right time and place. The Programme started in November 2016 and about 200 patients have been cared for from home so far.
After a patient has been discharged from the hospital, a doctor or nurse meets the patient at his or her home and all diagnostic work are performed at home, such as blood tests, X-rays and ultrasounds. The patient’s vitals including heart and respiratory rate, as well as movement are monitored 24/7 with wireless monitoring technology.
The patient is given an electronic tablet that allows him or her to communicate anytime with medical staff via phone, text or on-demand video. Many treatments, including medications, are administered at a patient’s bedside. Preliminary pilot data of nine patients who were randomised to receive care at home showed that the average direct cost for acute care episodes for home patients was up to half of the cost of the control patients cared for in the hospital.
The collaboration between Biofourmis and Brigham and Women’s Hospital will harness and clinically utilise the vast quantity of biometric data that the home hospital team collects. The team plans use the Biovitals™ analytics engine and further innovate around new predictive algorithms. Unlike traditional threshold-based physiology monitoring, Biovitals™ uses advanced machine learning to learn a patient’s physiology and then dynamically build a personalised physiology signature that can detect subtle physiological changes that may predict a patient’s health. The programme would also use Biofourmis’ RhythmAnalytics™ platform to detect dozens of different cardiac arrhythmias.
“Current remote monitoring systems are based on univariate physiology analysis and have shown high false alarm burden and no early intervention, especially while monitoring patients in an ambulatory setting. This collaboration would enable us to enhance and co-develop new predictive models for monitoring acutely ill patients’ suffering from multiple conditions like heart failure, pneumonia, COPD, and atrial fibrillation at-home, enabling clinicians to intervene early and improve the level of safety of patients,” said Kuldeep Singh Rajput, Founder & CEO of Biofourmis.
“Our home hospital team is hoping to improve care for our patients by creating a suite of highly clinically-useful algorithms that can predict deterioration and improvement for those who are acutely ill,” said David Levine MD, MPH, MA, researcher and lead for Brigham and Women’s Home Hospital programme.
In December 2017, Biofourmis announced that it had raised US$5.0 million in a Series A round of funding from NSI Ventures and Aviva Ventures, the strategic corporate venture arm of international insurer, Aviva plc. The company also entered into a collaboration with Mayo Clinic, which would enable them to assess de-identified healthcare data from clinical trials and Mayo’s expert medical insights.
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