Description
Examining variation in clinical practice is an important step to measuring efficiency and effectiveness in care delivery. The study of practice variation by an individual nurse and patient characteristics can indicate potential opportunities to reduce costs and improve the value of health care delivery.
This didactic panel will describe the overall approach taken to examine the clinical practice of nurses linked to patients at a single pediatric hospital. This exemplary of emerging data science uses data from multiple electronic data sources, including clinical, administrative, human resources, staffing, and financial systems to identify outcomes with a new level of precision. Examples include nurse-sensitive outcomes throughout each shift, length of stay, and traditional discharge measures. Administrative outcomes include calculations of the direct cost of nursing care by nursing unit and diagnosis. Attendees will become familiar with the Nursing Value Data Model and methodology for working with big data. They will examine variation in nursing clinical practice and discuss their findings, including how it can be better supported for clinical and translational research applications.
Learning Objective: 1. Attendees will learn about the Nurse Value Data Model and methodology for implementation.
2. Attendees will learn that working with large data sets is challenging but can provide valuable information about nursing care costs, quality, performance, effectiveness, and outcomes.
3. Attendees can engage with panelists on practice variation that is supported for clinical and translational research applications.
Authors:
Ellen Harper (Presenter)
The University of Kansas School of Nursing
Amy Garcia (Presenter)
The University of Kansas School of Nursing
John Welton (Presenter)
University of Colorado
Lisa Moon (Presenter)
University of Minnesota
Presentation Materials: