A fully online, 12-credit program launching in fall 2025 helps nurses turn real-world evidence into impactful clinical and administrative solutions.
Baltimore, Md. - The University of Maryland School of Nursing (UMSON) is launching a new Real-World Data and Pragmatic Research (RWD-PR) Certificate in fall 2025. The 12-credit, fully online program is designed to equip nurses and health care leaders with the tools to drive meaningful, evidence-based improvements in care.
Health care is facing urgent challenges: rising costs, workforce shortages, and the growing demand for high-quality, efficient care delivery. Nurses — often at the forefront of patient care — need advanced skills to evaluate and improve systems using real-world evidence. Traditional research methods, while foundational, can fall short in fast-paced clinical settings. That’s where pragmatic research and real-world data come in.
Real-world data refers to data collected from routine health care practices and patient interactions, rather than from traditional clinical trials. This data comes from various sources like electronic health records (EHRs), insurance claims, patient-reported outcomes, and wearable devices. RWD provides insights into how therapies perform in real-world settings and can be used to complement clinical trials.
“Generating nursing knowledge is only the beginning,” said Eun-Shim Nahm, PhD ’03, RN, FAAN, FGSA, professor and associate dean for the PhD program. “Today’s nurse scientists and leaders must also be able to implement evidence and scale its impact. This certificate program empowers nurses to harness real-world data to drive meaningful, evidence-based change in individual and population health.”
In an ongoing Nurse Support Program II implementation project, funded by the Health Services Cost Review Commission and administered by the Maryland Higher Education Commission, UMSON identified a need to increase student expertise in managing RWD from different sources and foster interprofessional student collaboration to understand the data and ensure plausibility and feasibility.