Osteoporosis often goes undetected until the first fracture, significantly increasing the risk of subsequent fractures. The Fracture Liaison Service (FLS) model aims to prevent secondary fractures and improve osteoporosis management. This study aims to provide a comprehensive overview of the current status of FLS implementation in Iran, applying the essential elements outlined in the FLS framework. This qualitative study used framework analysis to explore key components of the FLS framework from the perspectives of Iranian experts. Semi-structured, in-depth interviews were conducted over a 3-month period. Collaborative scenario synthesis was employed to accurately reflect the complexities of FLS operations. A total of 13 participants with an average practical experience of 3.2years contributed to the study. The results covered the people involved, needed information, locations, timeframes, and operational details of FLS stages, as well as quality improvement. The study confirmed the FLS framework's applicability in describing an implemented FLS and highlighted areas for improvement, such as coordinator training, role clarification, and data management issues. Given the scarcity of comprehensive studies on FLS within Iran's context and the recent growth and expansion of FLS initiatives in the country, this study offers insights into FLS implementation from the perspective of experts, serving as a guiding resource for future initiatives in this domain. Future research may benefit from developing tailored questionnaires based on the FLS framework to gather insights from a larger population for a better assessment. Key points • Iran lacks specialized training programs for FLS coordinators. Developing these programs is crucial, particularly for healthcare professionals from non-nursing specialties. • There is a lack of clarity regarding the timeline for each stage of the FLS process. A context-specific timeline is needed to optimize service implementation and workflow. • There are inaccuracies in coding patient information that pose significant challenges, potentially undermining hospital statistics and the quality of FLS data.
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