Advancing Continuous Predictive Analytics Monitoring Moving from Implementation to Clinical Action in a Learning Health System Jessica Keim-Malpass, PhD, RN a,b, *, Rebecca R. Kitzmiller, PhD, MHR, RN, BC c , Angela Skeeles-Worley, MEd d , Curt Lindberg, DMan e , Matthew T. Clark, PhD f,1 , Robert Tai, EdD d , James Forrest Calland, MD b , Kevin Sullivan, PhD g , J. Randall Moorman, MD b,f , Ruth A. Anderson, PhD, RN c Disclosure Statement: J. Keim-Malpass was supported through a grant from the University of Virginia Translational Health Research Institute of Virginia (THRIV) Scholars award. R. Kitzmiller was supported by the National Center for Translational Sciences and National Institutes of Health (NIH) through grant KL2TR001109. The content is solely the responsibility of the authors and does not necessarily represent official views of the NIH. C. Lindberg, R. Anderson, and R. Kitzmiller are supported by MITRE funding agreements 19140 and 11348 (accelerating staff engagement in predictive monitoring development, implementation, and use). The MITRE Cor- poration operates the Centers for Medicare & Medicaid Services (CMS) Alliance to Modernize Healthcare (CAMH), a federally funded research and development center dedicated to strengthening the nation’s health care system. The MITRE Corporation operates CAMH in part- nership with the CMS and the Department of Health and Human Services. Conflicts of Interest: Drs J.R. Moorman and M.T. Clark have equity in, and are officers of, the Advanced Medical Predictive Devices, Diagnostics, and Displays in Charlottesville, VA, USA (AMP3D). Dr M.T Clark is employed by AMP3D. a Department of Acute and Specialty Care, School of Nursing, University of Virginia, PO Box 800782, Charlottesville, VA 22908, USA; b Department of Medicine, School of Medicine, Uni- versity of Virginia, 1215 Lee Street, Charlottesville, VA 22908, USA; c School of Nursing, University of North Carolina, Carrington Hall, South Columbia Street, Chapel Hill, NC 27599, USA; d School of Education, University of Virginia, 405 Emmet Street South, Charlottesville, VA 22903, USA; e Billings Clinic, 801 North 29th Street, Billings, MT 59101, USA; f Advanced Medical Predictive Devices, Di- agnostics, Displays, Charlottesville, VA 22903, USA; g Department of Computer Science, School of Engineering, University of Virginia, Engineer’s Way, Charlottesville, VA 22903, USA 1 1215 Lee Street, Charlottesville, VA 22908. * Corresponding author. University of Virginia School of Nursing, PO Box 800782, Charlottes- ville, VA 22908. E-mail address: Jlk2t@virginia.edu KEYWORDS  Predictive analytics monitoring  Implementation science  Stakeholder driven design  Learning health system  Streaming design Crit Care Nurs Clin N Am 30 (2018) 273–287 https://doi.org/10.1016/j.cnc.2018.02.009 ccnursing.theclinics.com 0899-5885/18/ª 2018 Elsevier Inc. All rights reserved.