Precision health: Advancing symptom and self-management science

Kathleen T Hickey; Suzanne Bakken; Mary W Byrne; Donald Chip E Bailey; George Demiris; Sharron L Docherty; Susan G Dorsey; Barbara J Guthrie; Margaret M Heitkemper; Cynthia S Jacelon; Teresa J Kelechi; Shirley M Moore; Nancy S Redeker; Cynthia L Renn; Barbara Resnick; Angela Starkweather; Hilaire Thompson; Teresa M Ward; Donna Jo McCloskey; Joan K Austin; Patricia A Grady

doi:10.1016/j.outlook.2019.01.003

Precision health: Advancing symptom and self-management science

Nurs Outlook. 2019 Jul-Aug;67(4):462-475. doi: 10.1016/j.outlook.2019.01.003. Epub 2019 Jan 18.

Authors

Kathleen T Hickey¹, Suzanne Bakken², Mary W Byrne³, Donald Chip E Bailey⁴, George Demiris⁵, Sharron L Docherty⁴, Susan G Dorsey⁶, Barbara J Guthrie⁷, Margaret M Heitkemper⁸, Cynthia S Jacelon⁹, Teresa J Kelechi¹⁰, Shirley M Moore¹¹, Nancy S Redeker¹², Cynthia L Renn¹³, Barbara Resnick¹⁴, Angela Starkweather¹⁵, Hilaire Thompson¹⁶, Teresa M Ward¹⁶, Donna Jo McCloskey¹⁷, Joan K Austin¹⁸, Patricia A Grady¹⁷

Affiliations

¹ Cardiac Electrophysiology, Columbia University School of Nursing, Columbia University Medical Center, New York, NY.
² School of Nursing and Department of Biomedical Informatics, Columbia University, New York, NY. Electronic address: [email protected].
³ Department of Anesthesiology, Columbia University School of Nursing, Columbia University College of Physicians and Surgeons, New York, NY; Center for Children and Families, Columbia University School of Nursing, Columbia University College of Physicians and Surgeons, New York, NY.
⁴ Duke University School of Nursing, Durham, NC.
⁵ University of Pennsylvania, School of Nursing, Philadelphia, PA.
⁶ Department of Pain and Translational Symptom Science, School of Medicine, University of Maryland Baltimore, Baltimore, MD; Department of Anesthesiology, School of Medicine, University of Maryland Baltimore, Baltimore, MD.
⁷ Bouve College of Health Sciences, Northeastern University School of Nursing, Boston, MA.
⁸ Department of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA.
⁹ University of Massachusetts Amherst College of Nursing, Amherst, MA.
¹⁰ Medical University of South Carolina, College of Nursing, Charleston, SC.
¹¹ Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH.
¹² Section of Pulmonary, Critical Care and Sleep Medicine, Yale University, New Haven, CT.
¹³ Department of Pain and Translational Symptom Science, University of Maryland Baltimore, Baltimore, MD.
¹⁴ Organizational Systems and Adult Health Nursing Department, University of Maryland Baltimore, Baltimore, MD.
¹⁵ University of Connecticut School of Nursing, Storrs, CT.
¹⁶ University of Washington School of Nursing, Seattle, WA.
¹⁷ National Institute of Nursing Research, Bethesda, MD.
¹⁸ National Institute of Nursing Research, Bethesda, MD; Indiana University School of Nursing, Bloomington, IN.

Abstract

Background: Precision health considers individual lifestyle, genetics, behaviors, and environment context and facilitates interventions aimed at helping individuals achieve well-being and optimal health.

Purpose: To present the Nursing Science Precision Health (NSPH) Model and describe the integration of precision health concepts within the domains of symptom and self-management science as reflected in the National Institute of Nursing Research P30 Centers of Excellence and P20 Exploratory Centers.

Methods: Center members developed the NSPH Model and the manuscript based on presentations and discussions at the annual NINR Center Directors Meeting and in follow-up telephone meetings.

Discussion: The NSPH Model comprises four precision components (measurement; characterization of phenotype including lifestyle and environment; characterization of genotype and other biomarkers; and intervention target discovery, design, and delivery) that are underpinned by an information and data science infrastructure.

Conclusion: Nurse scientist leadership is necessary to realize the vision of precision health as reflected in the NSPH Model.

Keywords: Air self-management; Major nursing; Precision health; data science; informatics; symptom science.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Diagnostic Techniques and Procedures / standards*
Humans
Models, Nursing
Nursing Care / standards*
Nursing Research
Practice Guidelines as Topic*
Precision Medicine / nursing*
Precision Medicine / standards*
Self-Management / methods*

Abstract

Publication types

MeSH terms

Grants and funding