This publication is a conceptual synthesis and position paper that brings together insights from the CGS Paper Series (Papers 1–5), which examine human-centered digitalization in health care from clinical, organizational, and system-level perspectives. Rather than presenting new empirical data, the paper integrates longitudinal experience from Swedish health care—spanning quality registries, patient-engaged data systems, workflow design, and system failure modes—to articulate a unifying principle for AI adoption in clinical practice: digital technologies are only sustained when they save time, reduce cognitive burden, or improve clinical decision-making at the point of care. The paper is intended to support health care leaders, clinicians, system designers, and policymakers in critically evaluating AI and digital health initiatives beyond technical performance, with a focus on clinical usefulness, workflow integration, and long-term system resilience.
Anita Domargård (Thu,) studied this question.