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LifeBridge Health Selects Bayesian Health’s Research-Backed AI Platform to Help Diagnose and Treat Pressure Injury, Sepsis, and Patient Deterioration
NEW YORK, OCTOBER 20, 2021—Bayesian Health today announced that LifeBridge Health will be deploying its AI-based clinical decision support platform to help diagnose and treat pressure injury, sepsis, and patient deterioration. Bayesian Health’s platform operates within Epic and Cerner electronic medical records (EMR), deploying state-of-the-art artificial intelligence and machine learning (AI/ML) strategies to detect patient complications early.
Bayesian Health’s research-based AI platform takes existing EMR data, analyzing patient, clinical and third-party data with its industry-leading AI/ML models. The platform sends accurate and actionable clinical signals within existing workflows when a critical condition is detected, helping physicians and care team members accurately diagnose, intervene, and deliver timely care. The technology also includes a performance optimization engine which helps secure long-term physician, nurse and care team engagement with the tool.
“Like all health systems, our physicians must navigate large amounts of health data as they make decisions about patient care. As we look for ways to support our teams, we are interested to see how this new tool may work within the current workflow while allowing for some customization to augment the decision-making process for each provider or practice,” says Tressa Springmann, senior vice president and chief information officer at LifeBridge Health.
“LifeBridge has always looked for new and innovative ways to deliver high quality, compassionate care, and Bayesian Health’s research-backed platform will help LifeBridge Health’s physicians and care team members deliver on this mission,” said Suchi Saria, CEO of Bayesian Health. “I’m also thrilled to welcome Lee and Gary to Bayesian Health as founding members of our advisory board. They recognize the immense opportunity for health systems to improve patient outcomes and save lives by leveraging the Bayesian platform to augment physician and nurse decision-making with crucial data.”
Lee Sacks, MD, is the former Chief Medical Officer at Advocate Aurora, responsible for safety, quality, population health, insurance, claims, risk management, research, and medical education. He previously served as Executive Vice President, Chief Medical Officer of Advocate Health Care as well as the founding CEO of Advocate Physician Partners.
“Health Systems remain under market pressure to improve outcomes while reducing costs,” said Lee Sacks, MD. “Though health systems have made substantial investments in their EMR over the last decades, most are struggling to leverage their data in a way that supports clinicians in improving outcomes. Bayesian Health’s evidence-based AI/machine learning platform applied to sepsis outperforms what has been in the marketplace, and as a platform solution applied to many clinical areas, I believe it will enable health systems to achieve the dual goals of improving outcomes while reducing costs.”
Gary E. Bisbee, Jr., PhD, is founder, chairman and CEO of Think Medium, a digital media company focused on healthcare leadership, and sits on the Cerner board of directors. Prior to Think Medium, Bisbee was co-founder, chairman and CEO of The Health Management Academy, and he served as CEO and in various board of directors roles at ReGen Biologics, Inc., Aros Corporation, and APACHE Medical Systems, Inc.
Said Gary E. Bisbee, Jr, PhD, “Building technology that can adeptly analyze and manage messy EMR and healthcare data is hard. Building technology that physicians and nurses want to use day in and day out is even harder. Bayesian’s platform is uniquely positioned to bridge the gap between basic data and information a clinician needs to support a care decision. Accurate and actionable clinical decision support–that physicians want to use–is long overdue in the space, and the impact Bayesian Health will have on patient outcomes will be substantial.”
With a research-first foundation of over 21 patents and peer-reviewed research papers, Bayesian Health is approaching the market with a transparent and results focused strategy. It recently published a large, five site study analyzing use and practice impact over two years for Bayesian’s sepsis module. The platform drove 1.85 hour faster antibiotic treatment and demonstrated high, sustained adoption by physicians and nurses (89% adoption), driven by the sensitivity and precision of the insights and user experience of the software.
Bayesian Health’s technology overcomes common hurdles faced by many in the field by using cutting edge strategies to increase precision, make the models stronger, and encourage behavior change and on-going use. As a result, Bayesian’s technology accuracy is 10x higher than other solutions in the marketplace, driving tangible patient outcomes. To learn more about Bayesian Health, visit bayesianhealth.com.
Bayesian Health is on a mission to make healthcare proactive by empowering physicians and care team members with real-time data to save lives. Just like the best physicians continually incorporate new data to refine their prognostication of what’s going on with a patient, Bayesian Health’s research-based AI platform integrates every piece of available data to equip physicians and nurses with accurate and actionable clinical signals that empower them to accurately diagnose, intervene, and deliver proactive, higher quality care.
Bayesian Health, a health data startup created by Johns Hopkins researcher Suchi Saria, PhD, launched its artificial intelligence-powered clinical decision support platform on the commercial market July 12, according to a news release. READ MORE
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Platform shows high sensitivity, precision and physician adoption; recent study demonstrates 1.85h earlier recognition and treatment of sepsis, driven by 89% physician adoption
NEW YORK, JULY 12, 2021—Bayesian Health, an AI-based clinical decision support platform enabling health systems to provide safer and higher quality care, today launched its solution to the commercial market. Serving health systems on leading electronic medical record (EMR) vendors, Bayesian’s platform makes the EMR proactive—dynamic and predictive—to catch life threatening disease complications early.
Bayesian’s AI platform sits within the EMR, analyzing patient data with industry-leading AI/machine learning models. The platform sends accurate and actionable clinical signals within existing workflows when a critical moment is detected, helping physicians and care team members accurately diagnose, intervene, and deliver timely care.
With a research-first foundation of over 21 patents and peer-reviewed research papers, Bayesian’s platform is based on technology licensed from the Johns Hopkins University. The platform is configured to scale within health systems, and targets high-priority areas with specific modules such as clinical deterioration, sepsis, pressure injury, and transitions of care.
“Creating an AI solution that can achieve high sensitivity and precision isn’t easy,” said Doug Given, MD, PhD, Managing Partner at Health2047 Capital Partners and Bayesian Health investor. “Bayesian’s platform was developed using the highest quality data, and tested by top physicians and clinicians. This, combined with the team’s technical expertise and research-first mentality, has allowed them to create an AI platform that can be applied to many safety and quality endpoints to transform care delivery in the hospital setting for the better.”
A recent large, five site study analyzing use and practice impact over two years for Bayesian’s sepsis module showed the platform drove 1.85 hour faster antibiotic treatment for sepsis where timely treatment directly impacts mortality rate. The platform also demonstrated high, sustained adoption by physicians and nurses (89% adoption), driven by the sensitivity and precision of the insights and user experience of the software.
Additionally, a single-site study showed a 14% reduction in ICU admissions, a 12% reduction in ICU length of stay, and a 10% reduction in need of supportive therapies. These improvements resulted in a $2.5M annualized benefit for the 250 bed study site hospital, from decreased ICU utilization, earlier accurate diagnoses, and fewer hospital acquired conditions. Further studies validating outcomes including measuring mortality and length of stay reduction will be completed later this year.
With an estimated 400,000 preventable deaths a year, costing over $17B, patients, physicians, and health systems are all suffering as a result of reactive care. Patients are dying from preventable health events. Physicians and care team members are at risk of burnout with data overload and increased caseloads. Health systems are dealing with tighter staffing ratios, reduced operating margins, and increased value-based contracts.
“The number of data points being generated every single day for any given patient in a hospital is enormous, and continues to rise. And yet most physicians have never interacted with any AI technology that actually helps them analyze these data, or gives them any clinical insights,” said Dr. Vineeta Agarwala MD PhD, an internal medicine physician and General Partner at Andreessen Horowitz. “Early results from the real-world use of Bayesian Health’s platform is showing us that it can fit into our workflow, and augment how clinicians triage and diagnose patients.”
Historically, clinical decision support tools have been associated with high alert fatigue and have failed to build trust with physicians. Using cutting edge AI/ML strategies such as a wait and watch strategy and real-time feedback loops to increase precision, and strategies to make the models stronger, Bayesian’s technology accuracy is 10x higher than other solutions in the marketplace. Further, context and transparency with each clinical signal builds confidence among experts in the user experience.
“Having spent over two decades in AI and machine learning research, I know there’s immense potential to create AI tools to drive better care outcomes,” said Suchi Saria, PhD, founder and CEO of Bayesian Health. “Health data are messy, and it requires deep AI expertise to deliver strategies that can successfully analyze this data. But what’s even harder is what happens after the model is created; even with great models, you still need the solution to be adopted and trusted to realize better outcomes. We’re doing it differently, being one of the first solutions to deliver accurate and actionable clinical signals that physicians and nurses are actually acting upon.”
Bayesian Health and Dr. Saria have been highlighted by press, such as Bloomberg News and PBS, for the development of the platform, and has won several awards for excellence in care delivery, including The Armstrong Award for Excellence in Quality and Safety at Johns Hopkins Medicine; Node.Health’s Best in Class Digital Health Intervention Award; and Society of Critical Care Medicine’s Annual Scientific Award.
Advisory and investor team members to the company include Julie Yoo, General Partner at Andreessen Horowitz and Bayesian Health Board Member; Tasso Argyros, Founder & CEO, ActionIQ and Bayesian Health Board Member; Vijay Pande, PhD, General Partner, Andreessen Horowitz; Doug Given, MD, PhD, Managing Partner at Health2047 Capital Partners; and R. Jacob Vogelstein, PhD, Co-Founder & Managing Partner of Catalio Capital Management, LP.
Bayesian Health has raised $15 million in venture funding led by Andreessen Horowitz. Health 2047 Capital Partners, Lifeforce Capital, and Catalio Capital Management, LP also participated in the round of funding.
Bayesian Health is on a mission to make healthcare proactive by empowering physicians with real-time data to save lives. Just like the best physicians continually incorporate new data to refine their prognostication of what’s going on with a patient, Bayesian Health’s research-backed AI platform integrates every piece of available data to equip physicians with accurate and actionable clinical signals that empower them to accurately diagnose, intervene, and deliver proactive, higher quality care.