Kathryn Lytle

Chief Nursing Information Officer

Duke University Health System

United States

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About

Kathryn Lytle serves as the Chief Nursing Information Officer at Duke University Health System in the United States. Her research interests include the integration of artificial intelligence in nursing, health equity, and the development of clinical knowledge models to prevent healthcare-associated risks. Recent publications focus on empowerment in nursing informatics, the ethical implementation of AI technologies, and optimizing nursing workflows through electronic health record systems.

Articles (10)

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2025

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2024

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2024

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2024

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2024

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2022

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2022

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2021

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2020

Year:

2020

Collaborators (6)

Stephen Blackwelder

Visiting Professor

UNITED STATES

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Charlene Ronquillo

Assistant Professor

University of British Columbia Okanagan

CANADA

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Siobahn Grady

Assistant Professor

North Carolina Central University

UNITED STATES

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michael cary

Assistant Professor

Duke University School of Nursing

UNITED STATES

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Steven Johnson

University of Minnesota

UNITED STATES

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Armando Bedoya

Duke University

UNITED STATES

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Kathryn Lytle

Research Interests

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Articles (10)

Education, empowerment, and elevating nursing voices: Nursing informatics leaders’ perspectives on the path forward with artificial intelligence in nursing

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare

Empowering nurses to champion Health equity & BE FAIR: Bias elimination for fair and responsible AI in healthcare

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism.

A framework for the oversight and local deployment of safe and high-quality prediction models

Implementing Best Practices to Redesign Workflow and Optimize Nursing Documentation in the Electronic Health Record

Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar

Evaluation of ML-Based Clinical Decision Support Tool to Replace an Existing Tool in an Academic Health System: Lessons Learned

A Closer Look at the “Right” Format for Clinical Decision Support: Methods for Evaluating a Storyboard BestPractice Advisory

Collaborators (6)

Stephen Blackwelder

Charlene Ronquillo

Siobahn Grady

michael cary

Steven Johnson

Armando Bedoya

Make your next move.

Kathryn Lytle

Research Interests

Explore related searches

Contact this professor

About

Articles (10)

Education, empowerment, and elevating nursing voices: Nursing informatics leaders’ perspectives on the path forward with artificial intelligence in nursing

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare

Empowering nurses to champion Health equity &amp; BE FAIR: Bias elimination for fair and responsible AI in healthcare

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism

Clinical Knowledge Model for the Prevention of Healthcare-Associated Venous Thromboembolism.

A framework for the oversight and local deployment of safe and high-quality prediction models

Implementing Best Practices to Redesign Workflow and Optimize Nursing Documentation in the Electronic Health Record

Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar

Evaluation of ML-Based Clinical Decision Support Tool to Replace an Existing Tool in an Academic Health System: Lessons Learned

A Closer Look at the “Right” Format for Clinical Decision Support: Methods for Evaluating a Storyboard BestPractice Advisory

Collaborators (6)

Stephen Blackwelder

Charlene Ronquillo

Siobahn Grady

michael cary

Steven Johnson

Armando Bedoya

Make your next move.

Empowering nurses to champion Health equity & BE FAIR: Bias elimination for fair and responsible AI in healthcare