Abstract
Purpose: The aim of this study was to quantify clinical nurse specialist (CNS) work and determine if competencies are associated with personal characteristics, priorities, and quality outcomes.
Background: The work of a CNS is difficult to quantify. Nurse leaders need quantifiable data to understand the impact of CNS work.
Design: A prospective, single-center, correlational study with a convenience sample was conducted.
Setting and Sample: The study was conducted in a 1200-bed quaternary care medical center in Northeast Ohio, using CNSs.
Methods: The investigator-developed Role Tracker Tool (software) and a CNS questionnaire were used to collect baseline and monthly data for 5 months. Characteristics of the CNSs were summarized using descriptive statistics. Correlational statistics were used to measure associations. After mutually exclusive groups were created, tests for differences were completed using a Welch 2-sample t test and analysis of variance. Regression models were used to determine if relationships existed over time between competencies, priority ranking of competencies, and nursing characteristics.
Findings: Among 14 CNSs, mean (SD) age was 45 (10.11) years; mean (SD) CNS experience was 5.57 (7.87) years. Of 6 competencies, CNSs ranked quality as most important, followed by clinical work. Research ranked low. Mean (SD) time spent in hours/8.5-hour workday over 5 months was highest for clinical work, at 1.9 (1) hours, and lowest for professional self-development, at 0.4 (0.4) hours. Time spent on specific competencies varied by specialty, years as a CNS and at current employer, and comfort in competencies and spheres after controlling for nurse characteristics and monthly trends. Of 9 quality initiative focuses, mean (SD) time in hours/8.5-hour workday was highest for heart failure, with 0.7(0.8) hours. Time spent on quality initiatives was not associated with changes in quality improvement outcomes. Clinical nurse specialist competency priorities, quality initiative focuses, and quality outcomes varied over time.
Implications: The work of CNSs can be captured and analyzed to enhance understanding of unique and varied CNS contributions in the healthcare matrix.