Developing a measure of facilitators and barriers to rapid response team activation

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Developing a measure of facilitators and barriers to rapid response team activation Kim Schafer Astroth, PhD, RN Wendy Mann Woith, PhD, RN, FAAN Sheryl Henry Jenkins, PhD, APN Matthew Hesson- McInnis, PhD

Disclosures No conflict of interest exists for any of the authors (Schafer Astroth, Mann Woith, Henry Jenkins, Hesson-McInnis, all employed at Illinois State University) Travel for the first 3 authors is partially supported by Xi Pi chapter of STTI, and Mennonite College of Nursing at Illinois State University Learner objectives Explain how the Lens Model of Cognition directs the development of an instrument to measure factors that influence nurse activation of rapid response teams. Describe the process of testing an instrument to measure facilitators and barriers related to nurse activation of rapid response teams.

Background Rapid response team (RRT) comprised of critical care experts Respond to the bedside of deteriorating patients Prevent cardiac arrest (Brown et al., 2012) Underutilization associated with: Poor patient outcomes (Beckett et al., 2013) Increased healthcare costs (Beckett et al., 2013) Facilitators and barriers to nurse activation of RRT are under investigation (Braaten, 2015; Astroth et al., 2013)

Purpose To develop and test an instrument that identifies specific facilitators and barriers to RRT activation

Theoretical Framework Lens Model of Cognition (Hammond et al., 1964) People make decisions based on Cues and the significance attached to those cues Input from colleagues Available resources For our research purposes Cues and input from colleagues correspond to nursing unit culture and RRT member characteristics Available resources correspond to member characteristics and RRT knowledge.

Previous Research Qualitative study (Astroth et al., 2013) Facilitators and barriers related to Nursing unit culture, RRT member characteristics, and Continuing RRT education Pilot study (Jenkins et al., in press) Initial instrument based on Review of the literature Findings of our qualitative study (Astroth et al., 2013)

Method: Initial Instrument 32-item 5 point Likert Scale Subscale facilitators: unit culture, team characteristics, RRT knowledge Subscale barriers: unit culture, team characteristics, RRT knowledge Face and content validity established Setting & Sample Electronic survey of 50 RNs in non-icu settings at a community hospital Findings Over all Cronbach s alpha coefficient = 0.84 Subscales ranged from 0.67-0.90 Except for barriers: education = 0.07 Further revision based on scale reliability testing One item deleted Two items reworded Five items added

Method: Revised Instrument 36-item 5 point Likert Scale Subscale facilitators: unit culture, team characteristics, RRT knowledge Subscale barriers: unit culture, team characteristics, RRT knowledge Setting & Sample Electronic survey of 194 RNs from 4 hospitals Female: 75% Mean age: 39 (SD 12) years Mean experience: 14 (SD 12) years Education: 48% BSN Most recent RRT education: 0-4 years

Method: Revised Instrument Findings Overall Cronbach s alpha coefficient = 0.73 Facilitators Subscale: unit culture = 0.83 Subscale: RRT team characteristics = 0.83 Subscale: RRT education = 0.81 Barriers Subscale: unit culture = 0.81 Subscale: RRT team characteristics = 0.92 Subscale: RRT = 0.13 Confirmatory Factor Analysis: LISREL 8.80 Chi-square (579, N=194) = 812.80

Limitations Small convenience sample Recruitment by email did not capture those who don t read email No respondents from one hospital site

Conclusions Instrument shows promise for identifying facilitators and barriers to RRT Facilitators and barriers may vary across institutions Internal consistency of all subscales except education barriers reflects good reliability Future work Identify micro-structures within each factor Break factors apart using hierarchical cluster analysis and further item analysis techniques

References Astroth, K. S., Woith, W. M., Stapleton, S. J., Degitz, R. J., & Jenkins, S. H. (2013). Qualitative exploration of nurses decisions to activate rapid response teams. Journal of Clinical Nursing, 22, 2876-2882 Beckett, D. J. et al. (2013). Reducing cardiac arrests in the acute admissions unit: a quality improvement journey. BMJ Quality & Safety, 0, 1-7 doi:10.1136/bmjqs 2012 001404 Braaten, S. (2015). Hospital system barriers to RRT activation: A cognitive work analysis. AJN, 115(2), 22-32 Brown, S., Anderson, M. A., & Hill, P. (2012). Rapid response team in a rural hospital. Clinical Nurse Specialist, March/April, 95-102 DeVellis, R. F. (2012). Scale development: Theory and applications, 3 rd Ed. LA: Sage Hammond, K., Hursch, C., & Todd, F. (1964). Analyzing the components of clinical inference. Psychological Review, 71, 438-456. Jenkins, S. H., Astroth, K. S., Woith, W. M. (In press). Non-critical care nurses perceptions of facilitators and barriers to RRT activation. Journal for Nurses in Professional Development.