Columbia University’s Learning Health System (LHS) initiative is supporting its first two pilot projects. The first will use machine learning to identify sepsis more quickly, and the second will create a pediatric equity and quality dashboard.
“This initiative combines the expertise of world-class physicians and researchers from NewYork-Presbyterian [NYP] and Columbia to harness technology to improve the quality of care for all,” explained Laureen Hill, MD, MBA, Senior Group Vice President and Chief Operating Officer of NYP/Columbia University Irving Medical Center (CUIMC) , in a press release. “We are excited to work together to develop innovative tools to advance care and health equity for our patients.”
The LHS initiative draws on years of expertise generated in clinical care, informatics, health systems research, policy, engineering and industrial operations, health computational science, behavioral science, and most importantly, translational science excellence at CUIMC to solve clinical practice and provider challenges by feeding researchers real-time data from these same sources.
“At ColumbiaDoctors, we are accelerating the path to bringing innovation to the point of care,” said Timothy J. Crimmins, MD, chief medical information officer for CUIMC, in a statement. “Connecting our world-class physician-scientists to world-class patient care through a dynamic learning healthcare system is driving the transformation needed to deliver the best experience and outcomes for our patients, staff and our suppliers.
Selected projects will leverage the breadth of expertise and experience within the unique NewYork-Presbyterian/CUIMC environment and the full weight of institutions’ awareness and commitment to bridging disparities. in health care.
Using Machine Learning Algorithms to Quickly Identify Sepsis
Sepsis, a disease caused by the body’s dysfunctional response to infection, is a leading cause of death for hospitalized patients. Once the condition sets in, every hour of delay in sepsis treatment is associated with increased mortality.
At NewYork-Presbyterian and in hospitals around the world, sepsis is identified using a set of criteria that rely on abnormal vital signs and laboratory tests. However, machine learning algorithms pulling data from the electronic health record can detect sepsis more quickly.
The research team will use a methodology that uses learning with observational data, a recently described approach that has not been used for sepsis. The hope is that their work will lead to improved care for patients who contract sepsis at the NYP and, potentially, to a larger federal study.
Identifying and correcting inequities in pediatric emergency care
Equity dashboards dynamically track real-time quality metrics stratified by socio-demographic characteristics to identify inequities and have the potential to inform and ultimately improve rapid-cycle quality improvement initiatives focused on reducing inequalities in health care.
A team of pediatricians from CUIMC will research and lead the development of a Pediatric Equity and Quality Implementation Dashboard and Roadmap in the Emergency Department at Morgan Stanley Children’s Hospital . The NYP Dalio Center for Health Justice will host and maintain the dashboard.
The pilot dashboard will show inequalities in a single patient-centric measure – length of stay in the emergency department – with disparities documented in the literature. The team expects the scorecard and roadmap to reduce inequities in length of stay in pediatric EDs, identify effective strategies that could be tested at other sites, and create a platform for recognize and evaluate meaningful pediatric equity measures and local infrastructure to support pediatric population health initiatives.
Columbia Learning Health System Initiative
The Columbia University LHS initiative is a collaboration between ColumbiaDoctors, NYP, CUIMC, Columbia Engineering, New York State Psychiatric Institute, and the Irving Institute for Clinical and Translational Research, along with other collaborators on Columbia campuses.
Last fall, these stakeholders came together for the first LHS symposium. Pilot awards were announced at this symposium and ideas or teams from this session were encouraged to apply. Pilot prize research teams are paired with experts from Columbia Engineering, who will advise the teams on dynamic optimization, network development, risk analysis and IT support.
The LHS initiative will eventually form a network of faculty working groups to help overcome barriers to implementation in the learning health system cycle. The overarching goal is to capitalize on Columbia University’s world-class academics to integrate computer science, implementation science, and other point-of-care methodologies to improve quality and accelerate the translation of scientific discoveries into practice.
The LHS Pilots are the first in a series of Strategic Priority Pilot Awards created by the Irving Institute. Home to the center of CU’s Clinical and Translational Sciences Fellowship (CTSA) program, the Irving Institute is one of more than 60 medical research institutions across the country working together to accelerate the translation of research discoveries into improved patient care.
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