News Release

Additional data, advanced analytics improve performance of machine learning referral app

Uppstroms incorporates personal and population-level social determinants of health

Peer-Reviewed Publication

Regenstrief Institute

Uppstroms Incorporates Personal And Population-Level Social Determinants Of Health

image: Research scientists from Regenstrief Institute and Indiana University have further improved the performance of Uppstroms, a machine learning application that identifies patients who may need referrals to wraparound services, by incorporating additional personal and population-level data sources and advanced analytical approaches. view more 

Credit: Regenstrief Institute

INDIANAPOLIS -- Research scientists from Regenstrief Institute and Indiana University have further improved the performance of Uppstroms, a machine learning application that identifies patients who may need referrals to wraparound services, by incorporating additional personal and population-level data sources and advanced analytical approaches.

Research team affiliations include Regenstrief, IU Fairbanks School of Public Health at IUPUI, IU School of Medicine and Eskenazi Health.

Uppstroms has been in use at nine clinics associated with a safety net hospital in Indianapolis. The algorithm identifies primary care patients with social risks such as behavioral health or struggles with food or housing. This allows clinicians to offer these patients referrals to specialized services such as a dietician, behavioral health or a social worker, with the goal of addressing the need before it turns into a crisis.

Evidence suggests that at least one in four adults, and possibly as many as one in two, have a need driven by social determinants of health.

"These wraparound services can enhance primary care delivery by addressing socioeconomic, behavioral and financial needs that cannot be addressed by primary care providers," said Suranga Kasthurirathne, PhD, first author on the paper, Regenstrief research scientist and assistant professor of pediatrics at IU School of Medicine. "To make it more useful in the clinical setting, we incorporated a wide spectrum of patient-level data and more granular population health data to improve the precision of the app, leading to fewer false positives."

Innovations to prior approaches

Additional data added to the algorithm included patient-level social determinants of health, insurance, medication history and behavioral health history. These data came from Eskenazi Health's electronic health record system and the Indiana Network for Patient Care, which is managed by the Indiana Health Information Exchange. Population-level social determinants of health measured at census-tract area, which is smaller than the area encompassed by a zip code, were derived from the U.S. Census Bureau, the Marion County Public Health Department and community health surveys.

The research team assessed the new decision models and found that they outperformed previous models. The new patient-level data and advanced analytical approaches played a key role in improving the precision.

"So much of what affects health happens outside of a doctor's office," said senior author Joshua R. Vest, PhD, MPH, Regenstrief research scientist and professor and director of the Center for Health Policy at IU Fairbanks School of Public Health at IUPUI. "Health systems are working to integrate those social determinants of health into the EHR. This study shows the benefit of capturing social factors in the EHR during clinical visits and leveraging them for clinical decision making."

In addition to the added data elements, the study team adapted the application to be vendor neutral, meaning it can be implemented into any electronic health record system.

The next steps for the researchers are to develop a way to harness unstructured data in the EHR and include it in the algorithm.

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"Precision Health-Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation" was published online in JMIR Medical Informatics. This study was funded by a grant from the Robert Wood Johnson Foundation.

In addition to Dr. Kasthurirathne and Dr. Vest, other authors of the paper are Shaun Grannis, M.D., M.S., of Regenstrief Institute and IU School of Medicine; Paul K. Halverson, DrPH, of Fairbanks School of Public Health; Nir Menachemi, PhD, MPH of Regenstrief and Fairbanks School of Public Health; and Justin Morea, D.O., MBA, M.S. of IU School of Medicine and Eskenazi Health.

About Regenstrief Institute

Founded in 1969 in Indianapolis, the Regenstrief Institute is a local, national and global leader dedicated to a world where better information empowers people to end disease and realize true health. A key research partner to Indiana University, Regenstrief and its research scientists are responsible for a growing number of major healthcare innovations and studies. Examples range from the development of global health information technology standards that enable the use and interoperability of electronic health records to improving patient-physician communications, to creating models of care that inform practice and improve the lives of patients around the globe.

Sam Regenstrief, a nationally successful entrepreneur from Connersville, Indiana, founded the institute with the goal of making healthcare more efficient and accessible for everyone. His vision continues to guide the institute's research mission.

About the Richard M. Fairbanks School of Public Health at IUPUI

Located on Indiana's premier research and health sciences campus, the Richard M. Fairbanks School of Public Health at IUPUI is committed to advancing the public's health and well-being through education, innovation and leadership. The Fairbanks School of Public Health is known for its expertise in biostatistics, epidemiology, cancer research, community health, environmental public health, global health, health policy and health services administration.

About IU School of Medicine

IU School of Medicine is the largest medical school in the U.S. and is annually ranked among the top medical schools in the nation by U.S. News & World Report. The school offers high-quality medical education, access to leading medical research and rich campus life in nine Indiana cities, including rural and urban locations consistently recognized for livability.

About Suranga Kasthurirathne, PhD

In addition to being a research scientist at Regenstrief Institute, Suranga Kasthurirathne, PhD, is an assistant professor in the Department of Pediatrics at the Indiana University School of Medicine.

About Joshua R. Vest, PhD, MPH

In addition to being a research scientist with Regenstrief Institute, Joshua R. Vest, PhD, MPH, is the director of the Center for Health Policy and a professor of health policy & management at the Indiana University Richard M. Fairbanks School of Public Health at IUPUI.


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