Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
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Scandinavian journal of primary health care
Shoulder-to-shoulder: healthcare professionals' experiences of learning during electronic health record implementation in municipal primary care.
BACKGROUND: Formal training is commonly used in electronic health record (EHR) implementation, but often fails to address healthcare professionals' ongoing, context-specific learning needs. There is limited knowledge of how learning unfolds in practice when such training is experienced as insufficient, particularly in municipal healthcare services. METHODS: This qualitative study examined learning processes during the implementation of a new EHR system in a municipal healthcare institution in Central Norway. Data was generated through interviews and observation, and was analyzed thematically. RESULTS: Participants experienced formal training as poorly aligned with their digital competencies and everyday clinical work. Limited time and staffing further constrained participation in formal training and follow-up. Alongside formal training, employees engaged in peer-based learning practices embedded in everyday work, described as 'shoulder-to-shoulder' learning. These practices became particularly important due to limited time and staffing, enabling rapid problem-solving and mutual support, while also reinforcing shared responsibility for learning. Rather than merely compensating for inadequate training, shoulder-to-shoulder learning emerged as an important adaptive practice that supported problem-solving and collaboration during EHR implementation. CONCLUSION: Learning to use EHR systems in municipal primary care should be understood as a socially embedded and ongoing process. While formal training may provide initial orientation, implementation strategies should also recognize and support peer-based learning practices that support ongoing learning and collaboration during periods of organizational change.
18 May 2026
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From Concept to Practice: Lessons From the Balanced Nursing Teams Decision-Support System
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 system, a decision-support tool integrating approximately 250 data points-of which roughly 150 are extracted from existing organizational systems (human resources, scheduling, electronic health records, quality registries) through flexible import mechanisms, and the remainder collected through a built-in 360-degree staff survey with automated analysis-across 10 domains to evaluate nursing team balance between capacity, performance, and outcomes. Following crowdfunding by 18 Belgian health care organizations, balanced nursing teams were implemented across 8 diverse settings (home health care, general hospitals, academic centers) between 2019 and 2023. Using the Human-Organization-Technology fit framework, we analyze why evidence-informed, organization-endorsed digital innovations struggle to achieve adoption. Our analysis reveals 3 interdependent barrier categories: technological fragmentation (vendor lock-in, legacy systems, prohibitive integration costs), organizational siloing (Chief Nursing Officers [CNOs] lacking budgetary authority, nursing framed as peripheral to strategic priorities), and managerial hesitance (fear of punitive data use, cognitive overload from staffing crises). These barriers were worsened by the substantial data-integration burden that the system's breadth imposed on organizations with limited digital maturity. Critically, only one site (ie, a nurse-led home health care organization where leadership held both strategic authority and resource control) achieved sustained implementation. This contrast demonstrates that workforce optimization through data 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 health care organizations' highest 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.
14 May 2026
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