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From Concept to Practice: Lessons From the Balanced Nursing Teams Decision-Support System
Senne Vleminckx1, Peter Van Bogaert1, Wim De Keyser2
1Workforce management, Health systems, and Outcome Research in Care - Centre for Research and Innovation in Care, Faculty of Medicine and Health Sciences, University of Antwerp, Universiteitsplein 1, Wilrijk, Antwerp, 2610, Belgium, 32 474859762.
JMIR Nursing
|May 11, 2026
Summary
Strategic nursing workforce optimization requires data-driven systems. Successful implementation hinges on addressing technological, organizational, and managerial barriers, not just software capabilities.
Area of Science:
- Healthcare Management
- Nursing Informatics
- Health Services Research
Background:
- The global nursing workforce faces a crisis, necessitating a move from reactive staffing to strategic, data-driven workforce optimization.
- Decision-support systems are crucial for evaluating nursing team balance across capacity, performance, and outcomes.
- The Balanced Nursing Teams (BNT) system was developed to integrate diverse data points for comprehensive team assessment.
Purpose of the Study:
- To reflect on the development and implementation of the BNT system.
- To analyze barriers to the adoption of evidence-informed digital innovations in nursing workforce management.
- To identify critical factors for successful data-driven workforce optimization in healthcare.
Main Methods:
- A viewpoint paper analyzing the implementation of the BNT system across 8 diverse healthcare settings.
- Utilized the Human-Organization-Technology fit framework to examine adoption challenges.
- Collected data through system integration (HR, scheduling, EHR, quality registries) and a 360-degree staff survey.
Main Results:
- Identified three interdependent barrier categories: technological fragmentation, organizational siloing, and managerial hesitance.
- Implementation challenges were exacerbated by data integration burdens, particularly in organizations with low digital maturity.
- Sustained implementation was achieved only in a nurse-led home health care organization with strong leadership control.
Conclusions:
- Successful data-driven nursing workforce optimization depends on achieving fit across human, organizational, and technological domains, not solely on software sophistication.
- The marginalization of nursing leadership in governance structures is a fundamental barrier to digital transformation in nursing workforce management.
- Systemic investment in nursing leadership, data interoperability, and recognizing workforce optimization as a strategic imperative are essential.
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