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Cited by 18Patient Satisfaction in HealthcareNursing education and managementSentiment Analysis and Opinion Mining

Leveraging Technology to Sustain Extraordinary Care: A Qualitative Analysis of Meaningful Nurse Recognition

Clavelle, Joanne T., Sweeney, Cynthia D., Swartwout, Ellen, Lefton, Cindy, Guney, Senem·2019·JONA The Journal of Nursing Administration
DOI 10.1097/nna.0000000000000757
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Abstract

OBJECTIVE: Meaningful recognition of nurses submitted by patients and families using interactive patient care (IPC) technology was analyzed using artificial intelligence (AI) to identify the themes and behaviors associated with extraordinary nursing. BACKGROUND: Meaningful recognition positively impacts nursing and organizational outcomes. The use of AI techniques such as natural language processing and machine learning to identify and describe behaviors impacting patient experiences is an emerging science. METHODS: Nurse recognition comments were collected from a convenience sample of 3 organizations via an IPC inpatient platform and analyzed using the AI techniques of natural language processing, machine learning, sentiment analytics, and corollary dictionaries based on rules of linguistics. RESULTS: The top theme of nursing recognition comments was courtesy and respect with the behaviors of empathy/compassion, helpfulness, kindness, attentiveness, and emotional comfort. The theme of skills/knowledge was the 2nd most common, with the behaviors of being professional, knowledgeable, keeping track, competence, dedication, and being thorough. CONCLUSIONS: AI techniques for qualitative analysis of comments collected through IPC reveal nurse themes and behaviors most meaningful to patients and their family members. Nurses can advance the science of AI and guide its evolution so that nurse caring behaviors associated with establishing human connections that positively influence patient and family experience are accurately represented.

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19 of 19 references verified0 citation errors · 0 not checkable

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  • Participants' enthusiasm about AI's capacity to facilitate early detection and intervention and relieve nurses from routine tasks mirrors earlier studies showing AI enhances clinical decision-making and optimizes workflow efficiency.

    “The fervor surrounding AI's capacity to facilitate early detection and intervention, coupled with its potential to relieve nurses from routine tasks, mirrors findings from earlier studies that accentuate AI's role in enhancing clinical decision-making and optimizing workflow efficiency [56,57].”

    From Artificial intelligence in future nursing care: exploring perspectives of nursing professionals - a descriptive qualitative study (2024) · cites this paper as [56]

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Authors
Clavelle, J. T., Sweeney, C. D., Swartwout, E., Lefton, C., & Guney, S.
Affiliations
DAISY Foundation (US)
Corresponding author
Clavelle, Joanne T.
ORCID
Venue
JONA The Journal of Nursing Administration
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2019-06
Volume
49
Issue
6
Pages
303-309
ISSN
  • 0002-0443 (ISSN-L)
  • 1539-0721
DOI
10.1097/nna.0000000000000757
OpenAlex
W2945350763
Cited by
18
References
19
Citations by year
2026: 2 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 2 · 2021: 3 · 2020: 3 · 2019: 1
FWCI
3.04
Type
journal article
Language
en
Open access
closed
Locations
  • JONA The Journal of Nursing Administration (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › General Health Professions › Patient Satisfaction in Healthcare
  • Health Sciences › Nursing › Research and Theory › Nursing education and management
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
Keywords
nurse recognition, empathy and compassion, sentiment analysis, natural language processing, patient experience, inpatient care
MeSH terms
Artificial Intelligence, Clinical Competence, Empathy, Humans, Nurse-Patient Relations, Nurses, Nursing Care, Professional-Family Relations, Technology, Qualitative Research

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