CC BY-NC-ND 4.0 · Appl Clin Inform 2019; 10(02): 295-306
DOI: 10.1055/s-0039-1688478
Research Article
Georg Thieme Verlag KG Stuttgart · New York

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

Rebecca R. Kitzmiller
1   School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
,
Ashley Vaughan
1   School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
,
Angela Skeeles-Worley
2   Curry School of Education and Human Development, University of Virginia, Charlottesville, Virginia, United States
,
Jessica Keim-Malpass
3   School of Nursing, University of Virginia, Charlottesville, Virginia, United States
,
Tracey L. Yap
4   School of Nursing, Duke University, Durham, North Carolina, United States
,
Curt Lindberg
5   Billings Clinic, Billings, Montana, United States
,
Susan Kennerly
6   College of Nursing, East Carolina University, Greenville, North Carolina¸ United States
,
Claire Mitchell
2   Curry School of Education and Human Development, University of Virginia, Charlottesville, Virginia, United States
,
Robert Tai
2   Curry School of Education and Human Development, University of Virginia, Charlottesville, Virginia, United States
,
Brynne A. Sullivan
7   Division of Neonatology, University of Virginia, Charlottesville, Virginia, United States
,
Ruth Anderson
1   School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
,
Joseph R. Moorman
8   Departments of Cardiology and Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States
9   Center for Advanced Medical Analytics, University of Virginia, Charlottesville, Virginia, United States
› Author Affiliations
Funding This study was funded by the National Center for Advancing Translational Sciences (Grant/Award Number: ‘KL2TR001109’), Mitre Corporation (Grant/Award Number: ‘Contract No 109140-Phase 1 & 2’), and University of Virginia (Grant/Award Number: ‘THRIV’).
Further Information

Publication History

29 October 2018

18 March 2019

Publication Date:
01 May 2019 (online)

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 = 14) and nurses (n = 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 clinicians must balance and take advantage of existing clinician training methods.

Authors' Contributions

C.L., J.R.M., R.A., R.K., and R.T. developed the study design. R.T. conducted participant interviews. A.V., C.L., R.A., R.K., S.K., and T.Y. lead the application of the theoretical framework. Data analysis was conducted by A.S.-W., A.V., C.K., C.M., J.K.-M., R.A., R.K., S.K., and T.Y. Drafts of the manuscript were prepared by A.S.-W., A.V., B.S., C.L., J.K.-M., J.R.M., R.A., R.K., S.K., and T.Y. All authors read and approved the final manuscript.


Protection of Human and Animal Subjects

Ethics approval was obtained from the University of Virginia IRB-SBS #2015–0352. Procedures included participant consent to participate.


 
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