Return to search

Predicting Certification Success for the Family Nurse Practitioner

High-stakes licensure or certification examinations are required for many health professions disciplines to ensure safe entry-level practice. Accrediting agencies set a benchmark for graduates' first-time licensure or certification success as a measure of program effectiveness. Failures of graduates on licensure or certification examinations may directly affect the school's recruitment and retention of qualified students and faculty, as well as institutional financial viability. A health science university has added Health Education System, Inc. (HESI) standardized examinations using computer adaptive testing into the family nurse practitioner (FNP) master's program to support certification success, although research on these advanced practice examinations as related to certification outcomes was lacking. Guided by classical test theory, this study was an investigation of whether a relationship existed between students' performance on 4 HESI standardized examinations (Advanced Pathophysiology, Advanced Pharmacotherapeutics, Advanced Health Assessment, and the APRN/FNP Exit exam) and first-time FNP certification success. Binary logistic regression analysis of data from 117 students who graduated between 2013-2016 indicated that none of the 4 standardized HESI examinations significantly predicted FNP certification success, perhaps due to the examinations not carrying any evaluative weight within the program. The results of this project study may be used to promote positive social change by providing a means to improve first-time certification success and increasing the availability of primary care providers in the role of FNP.

Identiferoai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-6620
Date01 January 2018
CreatorsGravel, Tammy Lee
PublisherScholarWorks
Source SetsWalden University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceWalden Dissertations and Doctoral Studies

Page generated in 0.002 seconds