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Kelly Sager
General Manager & Vice
President, CDS Business Unit
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The Next Generation of CDS
In recent years, Clinical Decision Support (CDS) tools that leverage artificial intelligence (AI) have gained traction in the healthcare environment for their ability to support providers by aggregating and discerning important clinical data points. As they've been validated and refined, machine learning (ML) algorithms have been adopted by the medical community as a legitimate tool to help formulate a clear picture of a patient's health.
We believe that the implementation of research-backed AI tools in the clinical environment is a viable and necessary step towards improving patient care.
Experience our Team in Action
Blowing Up Triage
Driving care at Johns Hopkins Hospital
with AI and machine learning
Utilizing AI in Emergency Care
Demonstration of TriageGO
for the ED.
AI in Triage
Improving decision-making at
Yale New Haven Hospital.
All
Nearly a decade ago, investigation began on an electronic triage tool through a federally funded collaboration between data scientists, nurses, and physicians at The Johns Hopkins Hospital. In 2016, after being implemented in the Emergency Department, the tool was validated and results published as part of this AHRQ grant. This represented the first clinical decision support (CDS) tool leveraging artificial intelligence (AI) to generate risk-driven acuity level recommendations at triage. In 2017 the tool (then called E-triage) supplanted the 26-year standard, Emergency Severity Index (ESI) in the Johns Hopkins ED, with overwhelmingly positive results. Later that same year, with support from the NSF, the startup StoCastic was founded by those involved in the tool's genesis; Scott Levin, PhD, previously Sr Clinical Informaticist at Johns Hopkins and Principal Investigator on the AHRQ grant, and Eric Hamrock, MBA, previously a healthcare administrator at Howard County General. Jeremiah Hinson, PhD MD joined as MSN RN while Heather Gardner, RN MSN and Sophia Henry, MS RN MS joined as expert nurse-consultants.
In 2018 Levin et al. published Machine-learning Based Electronic Triage More Accurately Differentiates Patients with Respect to Clinical Outcomes Compared with the Emergency Severity Index, [https://pubmed.ncbi.nlm.nih.gov/28888332/] which solidified risk-based triage as a best practice. Over the next few years, the Danaher organization entered into several research collaborations with Johns Hopkins and StoCastic to fuel research in risk predictive AI models. Finally in 2022, Beckman Coulter (a Danaher OpCo) acquired StoCastic and the triage technology, now called TriageGO. In doing so, they formed the CDS Business Unit, absorbing the entire StoCastic team and recruiting experts in diagnostics and data science to continue building the portfolio of research-backed AI tools for Clinical Decision Support.
CDS Business Unit Leadership Team
Scott Levin, PhD
Senior Director of Research
& Innovation
Eric Hamrock
Senior Director Service &
Support
Heather Gardner, MSN RN
Clinical Consultant Nursing
Informatics & Emergency Nursing
Sophia Henry, MS RN
Clinical Consultant
Emergency Nursing - Triage
Stacy Faught
Director of Commercial
Operations
Jeremiah Hinson, PhD MD
Medical Director, Research
& Innovation
Tobin Efferen, MS MD
Senior Medical Director,
Medical Scientific Affairs
CDS in the Press
Jan. 11, 2024
Adopting AI to improve triage acuity - Mobile Health News
Sophia Henry, MS RN at Beckman Coulter Diagnostics, discusses the HIMSS AI panel she participated in regarding responsible AI, navigating ethical considerations, and using technology to decrease nurse burnout and improve patient outcomes.
Learn more ›
Nov. 9, 2023
The use of AI to support better clinical decision-making in emergency medicine – Healthcare IT News
Dr. Jeremiah Hinson speaks with Healthcare IT News about the use of AI to support better clinical decision-making in emergency medicineLearn moreDec. 6, 2023Data-Driven Approach Yields New Approach for Emergency Department Triage – ACEP NOWJeremiah Hinson, MD, PhD and Scott Levin, MD, detail how the challenging circumstances around emergency medicine are where data-driven clinical decision support (CDS) is most beneficial.
Learn more ›
Jan. 10, 2024
Moving Beyond the NYU Algorithm for Emergency Department Visit Appropriateness – JAMA Network
Jeremiah Schuur, MD references the work of Beckman Coulter CDS team members using artificial intelligence techniques to create a triage score.
Learn more ›
Jan. 12, 2024
How integrating AI and clinical decision support systems can help in the ER – Healthcare IT News
A Yale University School of Medicine ER clinical informatics expert offers a deep dive preview of his HIMSS24 educational session that will show how artificial intelligence and CDS can boost emergency care.
Learn more ›
Human-in-the-loop AI
“As the field of artificial intelligence has gained traction over the last decade, it has been well documented that the human + AI combination yields more powerful results than either alone.1 The most successful AI tools are designed to augment the human ability to aggregate information and make data-driven decisions. We are committed to building research-backed, responsible AI solutions that provide clinicians with actionable insights at the point of care, empowering them to make better decisions for their patients.”
VP/GM CDS Business Unit
Explore Our Solutions
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This product is only commercially available in the United States at this time. Please contact your Beckman Coulter sales representative for more information.
1. Sezgin E. Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers. Digit Health. 2023 Jul 2;9:20552076231186520. doi: 10.1177/20552076231186520. PMID: 37426593; PMCID: PMC10328041.
