Data mining results from an electronic clinical log for nurse practitioner students

Area of Science:

• Nursing Education
• Health Informatics
• Clinical Data Management

Background:

• Traditional clinical experience data collection methods are flawed and lack real-time capabilities.
• Difficulty in analyzing cross-sectional and longitudinal student clinical data due to non-digital formats.
• Need for improved systems to track and evaluate nursing student clinical experiences effectively.

Purpose of the Study:

• To describe the development and implementation of a web/PDA-based clinical log at Vanderbilt University School of Nursing.
• To analyze three years of collected data on student clinical experiences.
• To assess the utility of the digital log for real-time programmatic and placement adjustments.

Main Methods:

• Development of a web and Personal Digital Assistant (PDA)-based clinical logging system.
• Collection and aggregation of over 220,000 patient encounters over three academic years.
• Faculty analysis of digital log data to evaluate student experiences and inform curriculum adjustments.

Main Results:

• The digital clinical log successfully captured comprehensive data on student patient encounters.
• Analysis confirmed that students managed patients and performed services appropriate to their specialty areas.
• Student progression was observed, moving from observer roles to more independent practice, with variations in progression modes.

Conclusions:

• The digital clinical log provides a robust platform for real-time data collection and analysis of nursing student clinical experiences.
• The system facilitates timely programmatic changes and clinical placement adjustments based on empirical data.
• The findings support the effectiveness of the digital log in monitoring student development and ensuring appropriate clinical skill acquisition.