Longitudinal Panel Analysis of Nursing Registrant Data

Abstract

This paper examines the methodological advantages and limitations of applying techniques of longitudinal panel analysis to nursing registrant databases. Given that the costs for primary data collection are increasing, it is essential to take full advantage of existing data sets through secondary data analysis techniques. Nursing registrant databases (collected regularly by licensing authorities, government agencies and other organizations in many jurisdictions) provide an excellent opportunity for investigating mobility trends and patterns in nursing employment over time. This paper describes one such data set and identifies the strengths and weaknesses of applying longitudinal panel analysis techniques to the data. All registered nurses working within the profession in the province of Ontario are required to renew their registration with the College of Nurses of Ontario (CNO) on an annual basis. Each year registrants must complete a short survey focusing on the nature of their employment at the time of registration. Variables collected from the survey form include employment status (full-time, part-time or casual), place of employment (a detailed classification of the type of unit or organization nurses are employed by), primary responsibility (or practise specialty within the profession), and position type (according to status and degrees of authority within organizations), along with other information. The CNO has collected such data for many years, but has only recently (since 1984) been recording them in machine-readable form for data processing.