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VA Awards Regenstrief Institute Learning Health System Fellowship

A new fellowship funded by the VA will focus on the learning health system model of clinical decision support.

The Department of Veterans Affairs (VA) has awarded Regenstrief Institute and the VA Health Services Research and Development (HSR&D) Center for Health Information and Communication (CHIC) a VA fellowship in health services research and development that will focus on learning health systems.

The VA HSR&D Office of Academic Affiliations Advance Fellowship program provides two years of post-residency, post-doctoral research, education, and clinical learning opportunities.

Teresa Damush, PhD, and Marianne Matthias, PhD, who are both Regenstrief research scientists and investigators with the VA HSR&D CHIC, will lead the new fellowship.

The program will leverage local leadership support from the Richard L. Roudebush VA Medical Center and the expertise of the VA HSR&D CHIC and Regenstrief Center for Health Services Research.

The fellowship is set to provide future medical professionals with advanced training opportunities in health services research, implementation science, healthcare system improvement, bioethics, and data analytics, all of which are crucial to creating learning health systems.

These systems utilize data analytics to identify organizational opportunities, engage leadership, and employ quality improvement methods to sustain medical best practices.

“Our new LHS fellowship aligns well with the Veterans Health Administration’s aim to transform into a high reliability organization,” Damush, who also serves as a senior research professor of medicine at Indiana University School of Medicine, said in a public statement.

“Through this program, we plan to develop the critical skills of the next generation of health services researchers within the Veteran Health Administration, an integrated, national Learning Health System,” Damush added.

The program will recruit two fellows to begin training in July 2022. Linda Collins, the CHIC administrative officer, will be the program coordinator. Several Regenstrief research scientists helped create the proposal and will serve as mentors.

“Regenstrief and CHIC have an excellent combination of experienced mentors and expertise, making this an ideal setting for this program,” said Matthias, who is also an associate research professor of medicine at Indiana University School of Medicine. “The fellows will receive rigorous scientific methods training and practical application of LHS concepts in healthcare.”

Learning health systems have shown to be an effective method of clinical decision support.

For example, healthcare stakeholders recently leveraged a learning health system to develop and implement agile COVID-19 clinical guidelines, according to a Health Affairs blog post.

The C19 Healthcare Consortium, led by Mayo and MITRE, convened a workgroup to develop a clinical guideline for COVID-19 severity classification.

While it usually takes years for healthcare stakeholders to implement clinical guidelines, the learning health system model allowed the group to put out COVID-19 severity classification guidelines within weeks.

“A guideline approved by top emergency physicians meant that each facility treating COVID-19 patients didn’t have to start from scratch learning how to triage for this emerging infection through empirical observation; instead, the data and knowledge from tens of thousands of COVID-19 cases was brought to bear in a guideline that clinicians could trust,” the authors wrote.

Since the start of the pandemic brought few studies related to COVID-19 to reference, the stakeholders reviewed Italian and other European outbreak data and resulting studies on how clinicians quantified COVID-19 severity to create an initial framework for the learning health system.

From this framework, the work group drafted digital representations of clinical guidance. As more evidence emerged and real-world patient data poured in, the guideline and its digital representation sharpened.

Health IT vendors then put the recommendations into a digital format by engineering interoperable computable practice guidelines (CPGs) for clinician workflow integration.

The computable guidelines are continuously updated based on data collected from patients who were treated using the recommendations.

“The COVID-19 guidelines prove that it is possible to create point-of-care decision support based on the latest clinical best-practice guidance in an agile fashion, which initiates a true learning feedback loop,” the authors concluded.

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