AACC’s Society for Young Clinical Laboratorians (SYCL) focuses on the professional development of early career AACC members who are either under the age of 40 or currently registered as a Trainee Member of AACC. One of the initiatives supported by SYCL is organization of a half day workshop that takes a deeper dive into topics that will benefit early career laboratorians.

This year the SYCL workshop took place on Saturday with the theme of “Creating Value from Data: Tools and Strategies to Drive Your Lab Forward.” Clinical laboratories are engines of data, noted Brenda Suh-Lailam, PhD, chair of this year’s workshop subcommittee. “Data analytics gives us a way to make sense of this data and to use it in patient care and quality improvement,” she said. While this may be a new set of skills for laboratorians, that was part of the motivation of focusing the workshop on this topic, Suh-Lailam said.

The seven-member SYCL Workshop Subcommittee arranged for a diverse set of speakers to spend the afternoon with attendees. The workshop began with Shannon Haymond, PhD, who talked about building data analytics capacity in lab medicine.  Haymond provided an overview for why laboratorians should be concerned with data and how to start building skills and frameworks for use.  She incorporated real-time polling of the participants to gain insights into the current status of data analytics across institutions. This set the stage for the remaining speakers, including Veronica Luzzi, PhD, who addressed data-driven quality improvement, Alec Saitman, PhD, who discussed automating clinical mass spectrometry data review, and Thomas Durant, MD, the final speaker of the workshop who provided an introduction to predictive analytics for laboratorians. 

The speakers incorporated interactive group activities. The 115 attendees had the opportunity to work through a clinical concern related to critically low glucose results using the A3 process, and think through how to evaluate and implement predictive analytics tools in the laboratory.

At one point in the afternoon, workshop attendees were provided flashcards containing single words or symbols such as if/then, and/or/not, mathematical operators, and data elements such as analyte peak or retention time. They worked together to build rules that could be used to flag data as part of the process of automating data review.  

The issue of how to leverage laboratory data to improve patient care is only going to increase in importance for the clinical laboratory. In fact, it is one of the core goals of AACC’s new strategic plan to inform members about data analytics.

 “SYCL members are the future leaders of lab medicine, the ones who will train future laboratorians,” Suh-Lailam noted. “Focusing on this now will equip us with the tools we need to drive the field of lab medicine forward and stay relevant.”

To learn more about data in the laboratory, check out the data analytics track taking place this week, including two scientific sessions taking place Tuesday and two roundtable offerings, one Tuesday and one Wednesday.