Optimizing impact through the Tiered Doctor of Nursing Practice Project Model. Issue 3 (March 2020)

• Record Type: Journal Article
• Authors: Melander, Sheila; Howard, Patricia B.; Williams, Tracy E.; Tharp-Barrie, Kim; El-Mallakh, Peggy; MacCallum, Tricia
• Is Part Of: Journal of the American Association of Nurse Practitioners. Volume 32:Issue 3(2020)
• Page Start: 263
• Page End: 268
• Publication Date: 2020-03
• Subjects: Academic-practice partnership -- advising model -- practice improvement scholarship -- tiered DNP project model; Nurse practitioners -- Periodicals; Nursing -- Periodicals; 610.730692
• DOI: 10.1097/JXX.0000000000000283
• Languages: English
• ISSNs: 2327-6886

Abstract

ABSTRACT: Colleges of Nursing (CONs) and health care organizations (HCOs) are increasingly embracing academic-practice partnerships (AcaPP). An HCO's workforce development plan prompted an AcaPP agreement with a CON for the purpose of increasing the number of doctor of nursing practice (DNP) advanced practice nurses in the HCO. Over a period of 6 years, 4 consecutive cohorts of approximately 100 HCO baccalaureate prepared nurses were enrolled in the CON DNP program. The AcaPP environment facilitates large-scale DNP projects among successive cohorts of students. The purpose of this article is to describe the innovative Tiered DNP Project Model, defined as the process by which current students build on and expand select DNP projects implemented by students in initial cohorts. The tiered approach to the DNP project is facilitated by an advising model that occurs in the context of mutually agreed-upon goals and compatible with the HCO strategic plan and CON DNP program objectives. In the Tiered DNP Project Model, select studies are chosen for continuation by DNP students in subsequent cohorts based on nursing leadership guidance of alignment with HCO strategic goals. The model has resulted in driving improvements in HCO patient and systems outcomes, promoted practice scholarship, and contributed to the quality of the CON DNP program.