Currently accepted at: JMIR Nursing
Date Submitted: Jan 29, 2026
Date Accepted: Apr 1, 2026
Date Submitted to PubMed: Apr 2, 2026
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/92417
The final accepted version (not copyedited yet) is in this tab.
An "ahead-of-print" version has been submitted to Pubmed, see PMID: 41924859
From Concept to Practice: Lessons from the BNuT Balanced Nursing Teams Decision-Support System–A Viewpoint Paper
ABSTRACT
The global nursing workforce crisis demands a shift from reactive staffing to strategic workforce optimization through data-driven decision-support systems. This viewpoint paper reflects on the development and attempted implementation of the Balanced Nursing Teams (BNuT) system–a decision-support tool integrating approximately 250 data points across ten domains to evaluate nursing team balance. Following crowdfunding by 18 Belgian healthcare organizations, BNuT was implemented across eight diverse settings (home healthcare, general hospitals, academic centers) between 2019 and 2023. Using the Human-Organization-Technology fit (HOT-fit) framework, we analyze why conceptually sound, organization-endorsed digital innovations struggle to achieve adoption. Our analysis reveals three interdependent barrier categories: technological fragmentation (vendor lock-in, legacy systems, prohibitive integration costs), organizational siloing (Chief Nursing Officers lacking budgetary authority, nursing framed as peripheral to strategic priorities), and managerial hesitance (fear of punitive data use, cognitive overload from staffing crises). Critically, only one site–a nurse-led home healthcare organization where leadership held both strategic authority and resource control–achieved sustained implementation. This contrast demonstrates that workforce optimization through technology depends not on software maturity alone but on achieving simultaneous fit across human, organizational, and technological domains. We argue that the persistent marginalization of nursing leadership within hospital governance structures represents the fundamental barrier to digital transformation in nursing workforce management. The urgency paradox is striking: while nursing represents healthcare organizations’ largest operational cost and most direct patient interface, workforce optimization tools are consistently deprioritized in favor of regulatory compliance systems and billing infrastructure. Bridging this gap requires systemic investment in nursing leadership authority, data interoperability standards, and recognition that data-driven workforce decisions are strategic imperatives rather than operational luxuries.
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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.