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Deana Nelson, DSc

Senior Vice President of Administration and Chief Strategy Officer, Lakeland Regional Health

Dissertation Title

Examining the impact of Emergency Department (ED) registered nurse (RN) staffing on ED patient experience

Dissertation Abstract

Patient experience ratings are important to healthcare organizations from both a clinical and financial perspective. Studies examining the relationship between patient experience and nurse staffing are prevalent in the inpatient setting, but not as much is known about how staffing affects these ratings in the Emergency Department (ED).

This study examined the relationships between ED RN staffing, patient expectations and patient experience ratings, using a conceptual framework adapted from Donabedian’s structure/process/outcome model, and expectancy disconfirmation theory. Nurse staffing was measured in two different ways to better assess how to reflect the true workload of an ED RN. Patient experience ratings were examined for both those patients treated and released from the ED and those who were admitted to the hospital.

Overall, the study found that the type of nurse staffing measure is important for assessing the relationship between nurse staffing and patient experience, with the measure that accounted for the total number of patients in the department throughout a shift, as opposed to the number of patients who arrived to the ED by shift, being a more robust predictor of patient experience. Moreover, the relationship between nurse staffing and patient experience is largely limited to those patients treated and released. The analysis also suggests that the relationship between ED RN staffing and patient experience may be moderated by the time of arrival (shift), the day of arrival (day of week) and the disposition of the patient.

This research indicates the important role that ED RNs play in providing a positive patient experience and the need for management to carefully examine how ED RN staff should be allocated across day of week, shift and by patient type.