Diffusing an Innovation: Clinician Perceptions of Continuous Predictive Analytics Monitoring in Intensive Care

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)

Rebecca R.,Vaughan,Ashley,Skeeles-Worley,Angela,Keim-Malpa Kitzmiller (Creator)

Institution

East Carolina University (ECU )

Web Site: http://www.ecu.edu/lib/

Abstract: Background The purpose of this article is to describe neonatal intensive care unitclinician perceptions of a continuous predictive analytics technology and how thoseperceptions influenced clinician adoption. Adopting and integrating new technologyinto 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 monthsfollowing the conclusion of the predictive monitoring technology randomized controltrial. Following qualitative descriptive analysis, innovation attributes from Diffusion ofInnovation Theory-guided thematic development.Results Results suggest that the combination of physical location as well as lack ofintegration into work flow or methods of using data in care decisionmaking may havedelayed clinicians from routinely paying attention to the data. Once data were routinelycollected, documented, and reported during patient rounds and patient handoffs,clinicians came to view data as another vital sign. Through clinicians" observation ofsenior physicians and nurses, and ongoing dialogue about data trends and patientstatus, 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 ofillness may require implementation strategies that acknowledge the risk--benefit oftreatment cliniciansmust balance and take advantage of existing clinician trainingmethods.

Additional Information

Publication

Other

Language: English

Date: 2019

Keywords

predictive analytics; continuous predictive monitoring; neonatal intensive care; sepsis; Diffusion of Innovations; innovation attributes; implementation

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