By Caleb White | Date published: February 5, 2025
Dynamic Clinical Decision Support Tool Has Impact on Quality of Care
Eric Cucchi and colleagues publish promising results of its implementation
Managing seriously ill patients requires lifesaving clinical equipment and processes. As a patient’s health improves, these elements are eventually no longer required and continuing them for longer than needed could result in negative outcomes. To address this, researchers from UMass Chan Medical School/UMass Memorial Medical Center developed and investigated the use of a dynamic clinical decision support tool (CDST), which assists providers with managing important quality metrics for patients in critical care. The tool helps identify when certain elements are no longer needed to mitigate negative effects.
The study was led by Eric Cucchi, MS, PA-C, director of eICU Operations and Critical Care informatics officer, alongside co-investigators Bruce Greenberg, MD, medical director of the Memorial CCU and eICU, Nicholas Marshall, MS, PA-C, a clinical coordinator in Cardiovascular Medicine, and Joseph Burzynski, BS, MS, a student in the T.H. Chan School of Medicine Class of 2025. Their study, “A Dynamic Customized Electronic Health Record Rule Based Clinical Decision Support Tool for Standardized Adult Intensive Care Metrics,” was published in the Journal of American Medical Informatics Association in December and showed promising results for the implementation of the CDST they developed.
The tool has been used in the ICUs since October 2022, operates within Epic, and addresses 22 areas of care that need to be addressed daily and as appropriate for each patient in the ICU. It uses dynamic logic to ask questions about the care being delivered to a patient based on the relevance of a topic. “Not all patients require 22 areas of care to be addressed – for instance, a patient does not require a decision about central line need if one does not exist,” Mr. Cucchi explained. “Conversely, a patient no longer meeting the criteria for need of a central line would benefit from removing it as quickly as possible to prevent an associated bloodstream infection.”
Following their study confirming the tool’s accuracy, the next step for the researchers is to study metrics of its impact. Because the CDST identifies and alerts bedside ICU teams about the need for potential removal of devices such as central lines, urinary catheters, and endotracheal tubes, they hope to see measurable decreases in catheter burden and time on a ventilator.
“This tool has had a big impact on the quality of care within the ICUs at UMass Memorial Health,” Mr. Cucchi said. “It has been utilized throughout the system's ICUs and some aspects of the tool are being used in acute care areas. Dynamic clinical decision support tools like this one have a real potential to improve the care of our patients and the efficiency of our providers.”
Read the full journal article here.