Publication Date
9-1-2023
Journal
CIN: Computers, Informatics, Nursing
DOI
10.1097/CIN.0000000000001003
PMID
36648170
PMCID
PMC10350463
PubMedCentral® Posted Date
9-1-2024
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
Keywords
Humans, United States, Veterans Health, Delivery of Health Care, Workforce, learning health system, nursing, qualitative research, workforce
Abstract
Healthcare systems and nursing leaders aim to make evidence-based nurse staffing decisions. Understanding how nurses use and perceive available data to support safe staffing can strengthen learning healthcare systems and support evidence-based practice, particularly given emerging data availability and specific nursing challenges in data usability. However, current literature offers sparse insight into the nature of data use and challenges in the inpatient nurse staffing management context. We aimed to investigate how nurse leaders experience using data to guide their inpatient staffing management decisions in the Veterans Health Administration, the largest integrated healthcare system in the United States. We conducted semistructured interviews with 27 Veterans Health Administration nurse leaders across five management levels, using a constant comparative approach for analysis. Participants primarily reported using data for quality improvement, organizational learning, and organizational monitoring and support. Challenges included data fragmentation, unavailability and unsuitability to user need, lack of knowledge about available data, and untimely reporting. Our findings suggest that prioritizing end-user experience and needs is necessary to better govern evidence-based data tools for improving nursing care. Continuous nurse leader involvement in data governance is integral to ensuring high-quality data for end-user nurses to guide their decisions impacting patient care.
Included in
Biochemistry, Biophysics, and Structural Biology Commons, Medical Sciences Commons, Medical Specialties Commons, Nursing Commons, Quality Improvement Commons
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