Document Type


Publication Date

Spring 2021

Date of Final Presentation

Spring 3-12-2021

Committee Chair

Teresa Serratt, RN, Ph.D.

Committee Member


Coordinator/ Chair of DNP Program

Pamela Gehrke, EdD, RN

Abstract/ Executive Summary

Background: Nurse patient assignments on an adult medical surgical unit at a community hospital are often accomplished with inconsistent processes and rationales. Each charge nurse utilizes individualized processes to determine which patients will be best teamed-up and assigned to the available nurses. There are frequently no acuity measurements system or set criteria by which the number or types of patients can or should be assigned to any given nurse, nor are staff skill or competency considered in the assignment process.

Project Design: A pilot project was conducted on a medical/surgical unit. The project utilized the American Association of Critical Care Nurses (AACN) Synergy Model to guide the assessment of staff competency levels and patient complexity scores. The Synergy Model adapted for use in the medical surgical environment incorporates the analysis of patient complexity and the competency of the nurses’ assignment.

Results: Improvement was made in the number of medications given on time, as scheduled. Feedback from staff was positive and they felt that team assignments were more balanced. The Synergy Model also validated the nurse’s feelings of often being busier than usual. Expected improvements to staff and patient satisfaction were not realized during the sixteen-week measurement period of the project.

Recommendations and Conclusions: The AACN Synergy Model provides evidence-based structure and processes for charge nurses to incorporate elements of each patient’s individual situation to build a patient team that is aligned with each nurse’s level of capabilities. The scholarly project demonstrated the positive impact of using evidence-based practice tools, processes, and principles to improve patient care and outcomes.


Author Dedication: It is with much gratitude for the patience and support of my mentor Teresa Serratt and my wife Jeanne McEwan. They have contributed so much to my Doctoral progress.