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6th World Nursing and Healthcare Conference

London, UK

Thomas J.B. Kropmans

Thomas J.B. Kropmans

National University of Ireland Galway, Ireland

Title: Back to the future: Online OSCE management information system for nursing OSCEs
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Biography: Thomas J.B. Kropmans


Background: The Objective Structured Clinical Examination (OSCE) is an established tool in the repertoire of clinical assessment methods in nurse education. Identified benefits of OSCE assessment include development of students’ confidence in their clinical skills and preparation for clinical practice. Objectives: To explore electronic OSCE delivery and evaluate the benefits of using an electronic OSCE management system. To explore assessors’ perceptions of and attitudes to the computer based package. Design: This study was conducted using electronic software in the management of a four station OSCE assessment with a cohort of first year undergraduate nursing students delivered over two consecutive years (n=203) in one higher education institution in Ireland. A quantitative descriptive survey methodology was used to obtain the views of the assessors on the process and outcome of using the software. Methods: OSCE documentation was converted to electronic format. Assessors were trained in the use of the OSCE management software package and laptops were procured to facilitate electronic management of the OSCE assessment. Following the OSCE assessment, assessors were invited to evaluate the experience. Results: Electronic software facilitated the storage and analysis of overall group and individual results thereby offering considerable time savings. Submission of electronic forms was allowed only when fully completed thus removing the potential for missing data. The feedback facility allowed the student to receive timely evaluation on their performance and to benchmark their performance against the class. Conclusions: Assessors’ satisfaction with the software was high. Analysis of assessment results can highlight issues around internal consistency being moderate and examiners variability. Regression analysis increases fairness of result calculations.

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