Babson Diagnostics and ClosedLoop Team Selected as 1st Place Winner of ‘Help with Hemolysis’ Data Analytics Challenge

ClosedLoop and Babson Diagnostics have been named the winners of “Help with Hemolysis,” a data analytics challenge hosted by AACC and Washington University in St. Louis. Participants developed an algorithm for retraining phlebotomists to reduce sample errors from hemolysis.

Second Annual Competition Co-Hosted by Washington University in St. Louis and American Association for Clinical Chemistry (AACC) Challenges Participants to Solve Real-World Clinical Laboratory Challenges Using Data Science

AUSTIN, Texas–(BUSINESS WIRE)–Babson Diagnostics, a science-first healthcare technology company, and ClosedLoop, the leading healthcare data science platform, today announced their team was selected as the first-place winner of the ‘Help with Hemolysis’ Data Analytics Challenge. As winners, the Babson and ClosedLoop team will present their approach for using data science to solve the real-world laboratory challenge of hemolysis during a scientific session titled “Blood & Bytes: Reducing sample quality errors in clinical laboratories using data science” at the 2023 AACC Annual Scientific Meeting & Clinical Lab Expo in Anaheim on July 23-27, 2023.

Babson Diagnostics and ClosedLoop have worked together closely since 2021, when the two companies collaborated to develop artificial intelligence solutions, which help detect and prevent sample quality errors that can occur when working with capillary blood samples. So it was a natural fit for the companies to team up to tackle the ‘Help with Hemolysis’ challenge.

The second annual data analytics competition, co-hosted by the Washington University in St. Louis Section of Pathology Informatics and the AACC Data Analytics Steering Committee, invited participants to test their analytics skills by developing an algorithm for retraining phlebotomists to reduce sample errors from hemolysis. The winning team was led by Babson’s Founder, Chairman and Chief Operating Officer Eric Olson, his son Ethan Olson, and ClosedLoop’s Chief Technology Officer and Co-Founder Dave DeCaprio – and placed first out of 17 teams from across the United States.

“Hemolysis is one of the biggest sample quality problems that clinical laboratories face whether they are working with venous or capillary blood samples,” Eric Olson said. “Combining Babson’s expertise in hemolysis and sample quality with ClosedLoop’s experience in artificial intelligence and machine learning enabled us to work the problem biologically and computationally at the same time. We appreciate the opportunity to collaborate with the teams at Washington University in St. Louis and the AACC to tackle a challenge with real impacts on people’s lives.”

In vitro hemolysis is the breaking open of red blood cells during blood specimen collection – and is the most common preanalytical laboratory error and the most common cause of sample rejection – leading to delays in clinical results, increased costs, and decreased patient satisfaction. Educational interventions, which have been shown to reduce hemolysis rates, are often resource-intensive.

This challenge invited participants to rank all blood specimen collectors at a major tertiary care center based on how much money would be saved over the following year by re-educating that collector on hemolysis prevention techniques. The goal of the solution would be to maximize the reduction in hemolysis costs by targeting all available educational resources in the most effective way possible.

In vitro hemolysis can affect up to 3.3% of all routine samples, leading to sample rejections that delay critical results and increase patient and institutional costs,” said Dave DeCaprio. “We felt uniquely positioned to solve this challenge with our partners at Babson Diagnostics. We combined Babson Diagnostics’ expertise in maximizing the clinical utility of blood testing with ClosedLoop’s AI/ML platform to build a predictive model that identified precisely which individuals should receive education.”

The winning data models developed by this competition will directly inform institutions to spend their educational resources more efficiently to maximally prevent in vitro hemolysis to ultimately improve patient care and decrease costs.

About Babson Diagnostics

Babson Diagnostics is a healthcare technology company rooted in science reimagining the entire diagnostic blood testing experience. Babson’s mission is to make routine blood testing less invasive, more convenient, and affordable, empowering people to take charge of their health.

Babson will bring medically accurate blood testing to the retail pharmacy by using patented technologies and a first-of-its-kind ecosystem that requires only one-tenth the sample volume of traditional venipuncture methods without sacrificing quality, accuracy, or menu breadth.

The company has received key patents in the United States, European Union, and China related to its unique end-to-end technological ecosystem and the ability to maximize the clinical utility of microsamples of blood collected from a fingertip. In addition, Babson has fully validated a broad set of miniaturized assays that are ready for commercial use in its CLIA-certified laboratory.‍

Babson, based in Austin, Texas, was founded by individuals with deep experience in healthcare, diagnostics, engineering, and laboratory technologies. It is named in honor of Art Babson, whose legacy of scientific innovation and excellence is the foundation on which the company is built.

About ClosedLoop

ClosedLoop is healthcare’s data science platform. We make it easy for healthcare organizations to use AI to improve outcomes and reduce costs. Purpose-built and dedicated to healthcare, ClosedLoop combines an intuitive end-to-end machine learning platform with a comprehensive library of healthcare-specific features and model templates. Customers use ClosedLoop’s Explainable AI to drive clinical excellence, operational efficiency, value-based contracts, and enhanced revenue. Winner of the CMS AI Health Outcomes Challenge and named Best in KLAS for Healthcare AI: Data Science Solutions in 2022 and 2023, ClosedLoop is headquartered in Austin, Texas.


Four Steps to Measure and Mitigate Algorithmic Bias in Healthcare

Artificial intelligence (AI) and machine learning (ML) are increasingly used in healthcare to combat unsustainable spending and produce better outcome...

13 min read

How You Can Develop and Launch a Strategy to Prioritize Health Equity

Implementing a comprehensive strategy to advance health equity is a moral and financial imperative for healthcare organizations (HCOs). ‍Persistent...

12 min read

How COVID-19 Exacerbated Health Disparities

COVID-19 simultaneously exacerbated existing health disparities and introduced entirely new ones. The pandemic disproportionately impacted people of c...

11 min read

Make AI/ML a core element of your care strategy.

Get in touch today to see the ClosedLoop platform in action.