A New Methodology Informs New Efficiencies
This article was originally published in the Northwestern University Feinberg School of Medicine News Center. It has been edited and expanded for the Breakthroughs in Care audience.
In new research, Northwestern Medicine scientists utilized a data science approach to develop a novel methodology that can be used to optimize a wide variety of quality improvement strategies in clinical practices.
Using electronic medical record (EMR) information from the Northwestern Medicine Enterprise Data Warehouse (NMEDW), the team examined discrepancies between expected and observed activities and the people involved in the discharge process of heart failure patients at the Bluhm Cardiovascular Institute.
Typically, to understand how providers work together, scientists survey individuals or observe them on the floor and do a time motion study. This new methodology allows scientists to use digital data that is produced through the normal course of care delivery, which is more efficient.
“There haven’t been a lot of strategies that can make breakthroughs in quality improvement,” said Clyde Yancy, MD, MSc, chief of Cardiology and a co-author on the study. “Using this new approach we were able to look at our process of care and identify where there might be unrealized steps on streamlining admissions. By having the NMEDW we could fully capture all the variables of how many different steps and orders that affect a patient’s outcome. This presents a great opportunity to make a difference in how patients experience hospital visits.”
Nicholas Soulakis, PhD, assistant professor of Preventive Medicine in the Division of Health and Biomedical Informatics and senior author on the paper, and his team looked at the activities and providers identified on process maps, a type of flow chart, created by the cardiology staff compared to the EMR data. The team used resources from the Center for Data Science and Informatics led by Justin Starren, MD, PhD, deputy director of Northwestern University Clinical and Translational Sciences Institute and chief of Health and Biomedical Informatics in the Department of Preventive Medicine.
The data uncovered activities and providers involved in the patient’s care that was happening outside of what was in the documented discharge workflow. Gayle Kricke, a student in the Health Sciences Integrated PhD Program, said those sort of findings illustrate the value of the data for quality improvement.
“EMR data can be a tool for not just recording what is happening, but being able to improve processes,” Kricke said.
“These results demonstrate that our people are very skilled and resourceful and make smart decisions on the fly,” Soulakis explained. “Every day we make little decisions that help these processes move along.”
In a previous paper, Soulakis and his team showed the complexity of healthcare by using graphs to visualize and describe EMR usages for hospitalized patients with heart failure. The current paper expands on this project and gives guidelines for how other departments could couple digital data with process maps.
Next, Soulakis said he plans to do a similar analysis of primary care at Bluhm Cardiovascular Institute and in the emergency department.
“The goal is to have a better overview of understanding the continuum of care of heart failure patients,” Soulakis said. “As people get used to looking at maps that have diagnostics they can quickly see where they need to make changes.”
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