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Updated: Sep 30, 2025

Using Learning Outcome Measures to assess Doctoral Nursing Education
Published on: June 21, 2010
Development of the Doctor of Nursing Practice Nurse Practitioner Minimum Data Set (DNP NP MDS)
Asefeh Faraz Covelli1, Susan Weber Buchholz2, Leanne H Fowler3
1The George Washington University School of Nursing, 1919 Pennsylvania Avenue NW, Suite 500, Washington, DC 20006, USA.
Background:
While the number of Doctor of Nursing Practice (DNP) programs has grown steadily, there is limited data on how national organizations are collecting data on DNP-prepared nurse practitioners (NPs) and no standard instrument exists to collect data on DNP-prepared NPs.
Purpose:
The purpose of this study was to develop a universal minimum data set (MDS) for the DNP-prepared NP population.
Method:
Instrument development consisted of several sequential stages, including conceptualization and item generation, preliminary evaluation of items, field testing the survey, and analysis of scale development data.
Findings:
A set of 16 core variables and 19 additional variables were developed to collect standardized data on the demographics, education, and practice patterns of DNP-prepared NPs. Pilot testing revealed high correlations between the activities DNP-prepared NPs are prepared for and typically participate in a typical workweek and in their career. The MDS demonstrated high reliability in our sample.
Discussion:
The DNP NP MDS can be used for data collection by various stakeholders, including national organizations, to facilitate improved tracking of outcome data for the DNP-prepared NP workforce. It can also provide data-driven support for the need and significance of the DNP degree for NPs.
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