The Use of Technology to Support Precision Health in Nursing Science

Angela Starkweather; Cynthia S Jacelon; Suzanne Bakken; Debra L Barton; Annette DeVito Dabbs; Susan G Dorsey; Barbara J Guthrie; Margaret M Heitkemper; Kathleen T Hickey; Teresa J Kelechi; Miyong T Kim; Jenna Marquard; Shirley M Moore; Nancy S Redeker; Rachel F Schiffman; Teresa M Ward; Lynn S Adams; Karen A Kehl; Jeri L Miller

doi:10.1111/jnu.12518

The Use of Technology to Support Precision Health in Nursing Science

J Nurs Scholarsh. 2019 Nov;51(6):614-623. doi: 10.1111/jnu.12518. Epub 2019 Sep 30.

Authors

Angela Starkweather¹, Cynthia S Jacelon², Suzanne Bakken³, Debra L Barton⁴, Annette DeVito Dabbs⁵, Susan G Dorsey⁶, Barbara J Guthrie⁷, Margaret M Heitkemper⁸, Kathleen T Hickey⁹, Teresa J Kelechi¹⁰, Miyong T Kim¹¹, Jenna Marquard¹², Shirley M Moore¹³, Nancy S Redeker¹⁴, Rachel F Schiffman¹⁵, Teresa M Ward¹⁶, Lynn S Adams¹⁷, Karen A Kehl¹⁸, Jeri L Miller¹⁹

Affiliations

¹ Mu, Associate Dean, Professor, University of Connecticut, School of Nursing, Storrs, CT, USA.
² Beta Zeta, Interim Associate Dean for Academic Affairs, Professor, PhD Program Director, University of Massachusetts Amherst, College of Nursing, Amherst, MA, USA.
³ Alpha Zeta, Professor of Biomedical Informatics, Alumni Professor of the School of Nursing, Columbia University, New York, NY, USA.
⁴ Professor, Associate Dean for Research and Rackham Graduate Studies, Department of Systems, Populations and Leadership, University of Michigan, School of Nursing, Ann Arbor, MI, USA.
⁵ Eta, Professor, Department Chair Acute & Tertiary Care, University of Pittsburgh, School of Nursing, Pittsburgh, PA, USA.
⁶ Pi, Professor and Chair, Department of Pain and Translational Symptom Science, School of Nursing, and Professor, Department of Anesthesiology, School of Medicine, and Professor, Department of Neural and Pain Sciences, School of Dentistry, University of Maryland, Baltimore, MD, USA.
⁷ Professor & Associate Dean for Faculty, Bouve College of Health Sciences, School of Nursing, Northeastern University, Boston, MA, USA.
⁸ The Elizabeth Sterling Soule Endowed Chair in Nursing, Affiliate Professor, Division of Gastroenterology, School of Medicine, University of Washington, School of Nursing, Seattle, WA, USA.
⁹ Alpha Eta, Professor of Nursing at Columbia University Medical Center, Columbia University, School of Nursing, New York, NY, USA.
¹⁰ Gamma Omicron, David and Margaret Clare Endowed Chair and Professor, Medical University of South Carolina, College of Nursing, Charleston, SC, USA.
¹¹ Epsilon Theta, Professor, Associate Vice President for Community Health Engagement, LaQuinta Centennial Endowed Professor, University of Texas-Austin, School of Nursing, Austin, TX.
¹² Associate Professor, Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, USA.
¹³ Delta Xi, The Edward J. and Louise Mellen Professor of Nursing, Distinguished University Professor, Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA.
¹⁴ Delta Mu, Beatrice Renfield Term Professor of Nursing, Yale School of Nursing, Orange, CT, USA.
¹⁵ Alpha Chi and Eta Nu, Associate Dean and Professor, University of Wisconsin-Milwaukee, College of Nursing, Milwaukee, WI, USA.
¹⁶ Alpha Eta and Psi at Large, Professor, University of Washington, School of Nursing, Seattle, WA, USA.
¹⁷ Health Scientist Administrator, National Institute of Nursing Research, Bethesda, MD, USA.
¹⁸ Beta Eta at Large, Health Scientist Administrator, National Institute of Nursing Research, Bethesda, MD, USA.
¹⁹ Chief, OEPCR and NINR Research Centers Program, National Institute of Nursing Research, Bethesda, MD, USA.

Abstract

Purpose: This article outlines how current nursing research can utilize technology to advance symptom and self-management science for precision health and provides a roadmap for the development and use of technologies designed for this purpose.

Approach: At the 2018 annual conference of the National Institute of Nursing Research (NINR) Research Centers, nursing and interdisciplinary scientists discussed the use of technology to support precision health in nursing research projects and programs of study. Key themes derived from the presentations and discussion were summarized to create a proposed roadmap for advancement of technologies to support health and well-being.

Conclusions: Technology to support precision health must be centered on the user and designed to be desirable, feasible, and viable. The proposed roadmap is composed of five iterative steps for the development, testing, and implementation of technology-based/enhanced self-management interventions. These steps are (a) contextual inquiry, focused on the relationships among humans, and the tools and equipment used in day-to-day life; (b) value specification, translating end-user values into end-user requirements; (c) design, verifying that the technology/device can be created and developing the prototype(s); (d) operationalization, testing the intervention in a real-world setting; and (e) summative evaluation, collecting and analyzing viability metrics, including process data, to evaluate whether the technology and the intervention have the desired effect.

Clinical relevance: Interventions using technology are increasingly popular in precision health. Use of a standard multistep process for the development and testing of technology is essential.

Keywords: National Institute of Nursing Research; nursing research; self-management; symptoms; technology.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Humans
Nursing Research*
Precision Medicine*
Technology*
United States

Abstract

Publication types

MeSH terms

Grants and funding