TY - JOUR
AU - M. Ainslie
AU - E. Bahalkeh
AU - M. B. Bigley
A1 - 
AB - BACKGROUND: As the fastest growing segment of the healthcare workforce, understanding NP enrollment is vital. PURPOSE: This work aimed to guide healthcare workforce forethought, academic planning, and policy initiatives. METHOD: This secondary data analysis investigated nurse practitioner (NP) program enrollment trends from 2013 to 2022, including sub-analyses of master's versus doctoral enrollment, clinical tracks (acute care, primary care, psychiatric mental health), and enrollment status (part-time vs. full-time). An autoregressive integrated moving average (ARIMA) projection modeling is used to forecast enrollment for four years, 2023-2026. RESULTS: CONCLUSION: Increased enrollments in doctoral NP programs, visible in DNP NP program and enrollment growth, may offer advantages for the healthcare workforce. Part-time enrollment prevalence requires attention in workforce planning due to the potential for extended graduation timelines. These findings hopefully will lead to an effective healthcare response to meet the demand for high-quality care in a changing landscape.
AD - Department of Nursing, University of New Hampshire, 4 Library Way, Hewitt Hall, #241, Durham, NH 03824, United States of America. Electronic address: marcy.ainslie@unh.edu.; Department of Health Management and Policy, University of New Hampshire, United States of America.; National Organization of Nurse Practitioner Faculties, United States of America.
AN - 39667896
BT - J Prof Nurs
C5 - Education & Workforce
DA - Nov-Dec
DO - 10.1016/j.profnurs.2024.09.007
DP - NLM
ET - 20240912
JF - J Prof Nurs
LA - eng
N2 - BACKGROUND: As the fastest growing segment of the healthcare workforce, understanding NP enrollment is vital. PURPOSE: This work aimed to guide healthcare workforce forethought, academic planning, and policy initiatives. METHOD: This secondary data analysis investigated nurse practitioner (NP) program enrollment trends from 2013 to 2022, including sub-analyses of master's versus doctoral enrollment, clinical tracks (acute care, primary care, psychiatric mental health), and enrollment status (part-time vs. full-time). An autoregressive integrated moving average (ARIMA) projection modeling is used to forecast enrollment for four years, 2023-2026. RESULTS: CONCLUSION: Increased enrollments in doctoral NP programs, visible in DNP NP program and enrollment growth, may offer advantages for the healthcare workforce. Part-time enrollment prevalence requires attention in workforce planning due to the potential for extended graduation timelines. These findings hopefully will lead to an effective healthcare response to meet the demand for high-quality care in a changing landscape.
PY - 2024
SN - 8755-7223
SP - 97
EP - 104+
ST - Nurse practitioner program enrollment trends and predictions
T1 - Nurse practitioner program enrollment trends and predictions
T2 - J Prof Nurs
TI - Nurse practitioner program enrollment trends and predictions
U1 - Education & Workforce
U3 - 10.1016/j.profnurs.2024.09.007
VL - 55
VO - 8755-7223
Y1 - 2024
ER -