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Appl Clin Inform 2024; 15(02): 295-305
DOI: 10.1055/s-0044-1785688
Research Article

Identifying Barriers to The Implementation of Communicating Narrative Concerns Entered by Registered Nurses, An Early Warning System SmartApp

Mollie Hobensack
1   Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York City, New York, United States
,
Jennifer Withall
2   Department of Biomedical Informatics, Columbia University, New York City, New York, United States
,
Brian Douthit
3   Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, United States
,
Kenrick Cato
4   Department of Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, United States
,
Patricia Dykes
5   Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Sandy Cho
6   Department of Clinical Informatics, Newton-Wellesley Hospital, Newton, Massachusetts, United States
,
Graham Lowenthal
7   Brigham and Women's Hospital, Boston, Massachusetts, United States
,
Catherine Ivory
8   Vanderbilt University Medical Center, Nashville, Tennessee, United States
,
Po-Yin Yen
9   Washington University School of Medicine in St. Louis, St. Louis, MO, United States
,
Sarah Rossetti
2   Department of Biomedical Informatics, Columbia University, New York City, New York, United States
› Author Affiliations Funding This project is supported by the National Institute of Nursing Research (1R01NR016941-01, T32NR007969), American Nurses Foundation (ANF): Reimagining Nursing Initiative, and Jonas Scholarship.
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Abstract

Background Nurses are at the frontline of detecting patient deterioration. We developed Communicating Narrative Concerns Entered by Registered Nurses (CONCERN), an early warning system for clinical deterioration that generates a risk prediction score utilizing nursing data. CONCERN was implemented as a randomized clinical trial at two health systems in the Northeastern United States. Following the implementation of CONCERN, our team sought to develop the CONCERN Implementation Toolkit to enable other hospital systems to adopt CONCERN.

Objective The aim of this study was to identify the optimal resources needed to implement CONCERN and package these resources into the CONCERN Implementation Toolkit to enable the spread of CONCERN to other hospital sites.

Methods To accomplish this aim, we conducted qualitative interviews with nurses, prescribing providers, and information technology experts in two health systems. We recruited participants from July 2022 to January 2023. We conducted thematic analysis guided by the Donabedian model. Based on the results of the thematic analysis, we updated the α version of the CONCERN Implementation Toolkit.

Results There was a total of 32 participants included in our study. In total, 12 themes were identified, with four themes mapping to each domain in Donabedian's model (i.e., structure, process, and outcome). Eight new resources were added to the CONCERN Implementation Toolkit.

Conclusions This study validated the α version of the CONCERN Implementation Toolkit. Future studies will focus on returning the results of the Toolkit to the hospital sites to validate the β version of the CONCERN Implementation Toolkit. As the development of early warning systems continues to increase and clinician workflows evolve, the results of this study will provide considerations for research teams interested in implementing early warning systems in the acute care setting.

Keywords

qualitative - nursing informatics - toolkit - implementation - early warning system

Human Subject Protections

Consent was provided by all participants included in the study. Participant names and videos were not recorded during the interviews; only audio was recorded. The interviewer (M.H.) cleaned the qualitative transcripts prior to further analysis. All data were stored on a protective drive that was password protected. All recordings and transcripts will be destroyed following publication. Approval from the Institutional Review Boards at both study sites was provided.




Publication History

Received: 02 October 2023

Accepted: 06 February 2024

Article published online:
17 April 2024

© 2024. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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