Current Data Healthcare Quality Research and Data Science Courses Offered
Center for Healthcare Quality Research and Data Science faculty participate in graduate education through teaching and student mentoring.
NRSG 934: Foundations of Data Science (3 hours)
This course is designed to provide students with foundational knowledge about data science and big data. Students will learn the skills to participate on and lead interprofessional teams analyzing health and other related data to build knowledge and apply findings to practice. Topics to be examined will include diverse types and sources of data, data management techniques, exploratory data analysis approaches and data visualization.
Prerequisite: Admission to the School of Nursing Ph.D. program, graduate-level research course (NSRG 754 or equivalent) or Consent of Instructor.
Other relevant courses:
NRSG 946 Measurement Principles and Practice
Classical measurement theory and related measurement concepts are the focus of the course. Various approaches to instrumentation are examined. Students use existing data to evaluate selected measures, with emphasis on reliability and validity. They also critically analyze published reports of instrumentation for research. Basic knowledge of concept analysis is expected prior to enrollment.
NRSG 953 Quantitative Research Methods and Application
The course is designed to provide students with knowledge and research application experience in quantitative research methods. Students will learn how research questions lead to different study designs, data collection procedures, and analyses in nursing and health care. The course focuses on content on methodological techniques and issues involved in generating research questions and hypotheses, designing and implementing quantitative studies, and analyzing and interpreting results. The course includes a quantitative research application experience provided through the exercise in planning, conducting, and interpreting analyses with existing data.
NRSG 811 Clinical Epidemiology
This course introduces the basic concepts of epidemiology with meaningful clinical and translational applications to the field of nursing. This course is designed to equip the students in the Doctor of Nursing Practice degree program to make informed high-quality evidence-based decisions in clinical care and to develop answerable research questions regarding health conditions. Students will be able to identify high quality evidence and make responsible clinical decisions when there is weak evidence to balance clinical knowledge, experience, and research. This course will introduce epidemiological concepts and definitions by beginning with a historical overview of epidemics to public health surveillance of interventions for pandemics.
NRSG 960: Dissemination and Implementation Science in Healthcare
This course is designed for doctoral-level learners interested in conducting dissemination and implementation (D&I) research and applying implementation strategies to improve the uptake and sustainability of evidence-based guidelines, interventions, and innovations in healthcare. Learners are introduced to the field of implementation science; theories and frameworks; research designs, measures, and analyses; implementation strategies; fidelity and adaptation; evaluation; and sustainability. Learners also examine how dissemination research and practice influences the generation, uptake, and spread of policy and guides healthcare decision making. Learners work together to co-design a dissemination or implementation science project to address a critical issue that impacts health or health systems. Leadership competencies for supporting D&I research and practice also are explored.
NRSG 939 Precision Health
In this course students focus on precision health as an emerging approach for health promotion, disease prevention and treatment that considers individual variability in genes, environment, and lifestyle (also known as the determinants of health). Students learn how to develop prevention and treatment strategies for various populations using a precision health approach.
NRSG 950 Symptom Science
In this course, students will determine personalized strategies to treat and prevent the adverse symptoms of acute and chronic illness across diverse populations and settings. Biological and behavioral dynamics of symptoms (e.g., dyspnea, fatigue, impaired sleep/insomnia, pain, depression) that can change the trajectory of chronic illnesses, and how can the dynamics be optimized and maintained to prevent symptom relapse are discussed.
NRSG 951 Biomarkers
In this course students learn about how biomarkers are molecules that indicate normal or abnormal process within the body. These biomarkers may be a sign of an underlying condition or disease such as COVID-19. Various types of molecules, such as DNA (genes), proteins or hormones, can serve as biomarkers since they all indicate something about a person's health.