School of Nursing A Research Powerhouse

Christine E. Kasper

According to Christine E. Kasper, dean of the School of Nursing, data collection and analysis have always been part of the nursing profession—going back to Florence Nightingale, who was one of the first public health researchers.

“During the Crimean War, nurses did not just care for wounded soldiers,” says Kasper. “Florence Nightingale was collecting lots of data. Her work dramatically cut the death rate.”

That fundamental focus on applying data to practice has made Pitt Nursing a research powerhouse. Among other standout facts, Pitt Nursing ranked number seven nationally in 2022 National Institutes of Health funding to nursing schools. 

“Research here covers a very large scope, from big data to practice and basic science to behavioral science,” says Kasper. “Work here is happening simultaneously in clinical, acute, and tertiary care; genomics; public health; geriatrics; and anesthesia. We run the gamut of health science research.” 

Salah Al-Zaiti

Salah Al-Zaiti, associate professor in the Department of Acute and Tertiary Care in the School of Nursing, works at the juncture of big data and practice, developing technology to rapidly diagnose heart attacks by using biomedical informatics and machine learning. A recent paper in Nature Medicine demonstrated that the machine learning model he developed with collaborators could diagnose and classify heart attacks faster and more accurately than standard emergency room practice.

“That paper sums up 10 years of work,” says Al-Zaiti. He and co-author Christian Martin-Gill, associate professor of emergency medicine and chief of Emergency Medical Services at UPMC, worked with a wide range of collaborators at Pitt and beyond to build a machine learning model with electrocardiogram data from 4,026 patients at three hospitals in Pittsburgh, data that did not reveal how the patients had initially been classified. Tested against standard diagnostic practices—clinician interpretation, commercial algorithms, and risk factors—the model outperformed all three in accurately reclassifying one in three patients as low, intermediate, or high risk. The next stage for the model will be real-time testing in the field. 

Al-Zaiti is interested in applying this diagnostic tool beyond the United States. He recently received a Fulbright U.S. Scholar Award to work for nine months with refugees in Jordan. “The rate of heart attacks among refugees is high,” Al-Zaiti says. “And the average age of first heart attacks among refugees is in the 40s. In the United States, the average age of the first heart attack is in the 60s.” He will continue to work on Pitt projects while collaborating with United Nations clinics and the University of Jordan.