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Related Experiment Video

Updated: Jun 18, 2026

Using Learning Outcome Measures to assess Doctoral Nursing Education

Using Learning Outcome Measures to assess Doctoral Nursing Education

Published on: June 21, 2010

A database for nurse practitioner clinical education.

Deborah Cullen¹, Deborah Stiffler, Julie Settles

¹Department of Family Health, Indiana University School of Nursing, Indianapolis, IN, USA. dcullen@iupui.edu

Computers, Informatics, Nursing : CIN

|November 27, 2009

Summary

This summary is machine-generated.

A clinical education database enhances nurse practitioner training by improving informatics skills and enabling data-driven curriculum adjustments. This system supports student assessment and educational reform through evidence-based practice.

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Area of Science:

Nursing Education
Health Informatics
Educational Technology

Background:

The Indiana University School of Nursing sought to enhance its nurse practitioner (NP) clinical education tracking.
Alignment with the Technology Informatics Guiding Educational Reform (TIGER) strategic agenda is crucial for modernizing nursing education.
Effective management of clinical data is essential for evaluating learning experiences and demonstrating program value.

Purpose of the Study:

To present the utility and lessons learned from subscribing to a database service for tracking NP clinical education.
To illustrate how clinical database management supports the evaluation of teaching and learning.
To highlight the role of informatics in nursing education and clinical practice.

Main Methods:

Subscription to a dedicated database service for clinical education tracking.
Descriptive reporting and analysis of clinical database management functionalities.
Utilization of aggregated patient encounter data for faculty assessment and curriculum refinement.

Main Results:

The database system facilitates the practice and mastery of informatics capabilities for students.
Faculty can effectively coordinate and assess students in clinical settings using data analysis.
Tailoring of learning experiences based on aggregated patient encounter data is achievable.
Data analysis supports an evidence-informed approach to student progress and curriculum development.

Conclusions:

Clinical database systems are valuable tools for documenting and evaluating NP clinical education.
Implementing such systems enhances student informatics skills and faculty's ability to assess and guide learning.
The use of data analysis promotes an evidence-based approach to curriculum development and student evaluation.