Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care
Kitzmiller, Rebecca R.; Vaughan, Ashley; Skeeles-Worley, Angela; Keim-Malpass, Jessica; Yap, Tracey L.; Lindberg, Curt; Kennerly, Susan; Mitchell, Claire; Tai, Robert; Sullivan, Brynne A.; Anderson, Ruth; Moorman, Joseph R.
Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; realizing expected gains remain a challenge. Methods Semistructured interviews from a cross-section of neonatal physicians (n ¼ 14) and nurses (n ¼ 8) from a single U.S. medical center were collected 18 months following the conclusion of the predictive monitoring technology randomized control trial. Following qualitative descriptive analysis, innovation attributes from Diffusion of Innovation Theory-guided thematic development. Results Results suggest that the combination of physical location as well as lack of integration into work flow or methods of using data in care decisionmaking may have delayed clinicians from routinely paying attention to the data. Once data were routinely collected, documented, and reported during patient rounds and patient handoffs, clinicians came to view data as another vital sign. Through clinicians’ observation of senior physicians and nurses, and ongoing dialogue about data trends and patient status, clinicians learned how to integrate these data in care decision making (e.g., differential diagnosis) and came to value the technology as beneficial to care delivery. Discussion The use of newly created predictive technologies that provide early warning of illness may require implementation strategies that acknowledge the risk–benefit of treatment cliniciansmust balance and take advantage of existing clinician trainingmethods.
Kitzmiller, Rebecca R., & Vaughan, Ashley, & Skeeles-Worley, Angela, & Keim-Malpass, Jessica, & Yap, Tracey L., & Lindberg, Curt, & Kennerly, Susan, & Mitchell, Claire, & Tai, Robert, & Sullivan, Brynne A., & Anderson, Ruth, & Moorman, Joseph R.. (March 2019). Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care. Applied Clinical Informatics, (10:2), p.. Retrieved from http://hdl.handle.net/10342/8063
Kitzmiller, Rebecca R., and Vaughan, Ashley, and Skeeles-Worley, Angela, and Keim-Malpass, Jessica, and Yap, Tracey L., and Lindberg, Curt, and Kennerly, Susan, and Mitchell, Claire, and Tai, Robert, and Sullivan, Brynne A., and Anderson, Ruth, and Moorman, Joseph R.. "Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care". Applied Clinical Informatics. 10:2. (.), March 2019. December 01, 2020. http://hdl.handle.net/10342/8063.
Kitzmiller, Rebecca R. and Vaughan, Ashley and Skeeles-Worley, Angela and Keim-Malpass, Jessica and Yap, Tracey L. and Lindberg, Curt and Kennerly, Susan and Mitchell, Claire and Tai, Robert and Sullivan, Brynne A. and Anderson, Ruth and Moorman, Joseph R., "Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care," Applied Clinical Informatics 10, no. 2 (March 2019), http://hdl.handle.net/10342/8063 (accessed December 01, 2020).
Kitzmiller, Rebecca R., Vaughan, Ashley, Skeeles-Worley, Angela, Keim-Malpass, Jessica, Yap, Tracey L., Lindberg, Curt, Kennerly, Susan, Mitchell, Claire, Tai, Robert, Sullivan, Brynne A., Anderson, Ruth, Moorman, Joseph R.. Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care. Applied Clinical Informatics. March 2019; 10(2) . http://hdl.handle.net/10342/8063. Accessed December 01, 2020.