Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care
Author
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.
Abstract
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.
Date
2019-03-18
Citation:
APA:
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.
,
(),
-
. Retrieved from
http://hdl.handle.net/10342/8063
MLA:
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". .
. (),
March 2019.
October 03, 2023.
http://hdl.handle.net/10342/8063.
Chicago:
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," , no.
(March 2019),
http://hdl.handle.net/10342/8063 (accessed
October 03, 2023).
AMA:
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. .
March 2019;
():
.
http://hdl.handle.net/10342/8063. Accessed
October 03, 2023.
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