What should be documented for an anterior shoulder dislocation? A Delphi study.

Emerg Med J

Department of Emergency Medicine, Diakonessenhuis, Utrecht, The Netherlands.

Published: February 2025

Background: Standardised consensus-based documentation following anterior shoulder dislocation in the ED might improve clinical quality, reduce heterogeneity in research and reduce workload. The aim of this study was to determine important elements and the extent of variability for the ED documentation following anterior shoulder dislocation.

Methods: An expert panel of physicians who perform the documentation (emergency physicians) of diagnosis and management of anterior shoulder dislocation and those who may read it (orthopaedic surgeons and general practitioners) was recruited in a three-round Delphi design between May and November 2022. Important elements were identified for history, physical examination, additional examinations, reduction technique and miscellaneous. These were rated on a 0-9 Likert scale. Consensus was reached when ≥80% scored 7-9. Another, independent, outcome was high variability in opinion, defined as at least one score between 1 and 3 and one score between 7 and 9 on an item after the third round.

Results: The expert panel consisted of 22 emergency physicians, 5 general practitioners and 3 orthopaedic surgeons. In the first round, 85 elements were identified, and consensus on importance was reached in 22 out of the 85 elements: (5 out of 30), (5 out of 18), (5 out of 9), (5 out of 17) and (2 out of 11). High variability in importance was seen in 79 (93%) out of the 85 elements after the third round.

Conclusion: A consensus on 22 out of the 85 elements was reached and could be included in the ED documentation on anterior shoulder dislocation. Regardless of this consensus, high variability was observed in almost all the elements, highlighting the difference in opinions. Nevertheless, these elements could facilitate more concise communication among healthcare professionals and could facilitate homogenous datasets.

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http://dx.doi.org/10.1136/emermed-2024-214347DOI Listing

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