Mapping and assessing clinical handover training interventions.
BMJ Qual Saf. 2012 Dec;21 Suppl 1:i50-7
Authors: Stoyanov S, Boshuizen H, Groene O, van der Klink M, Kicken W, Drachsler H, Barach P
BACKGROUND: The literature reveals a patchwork of knowledge about the effectiveness of handover and transfer of care-training interventions, their influence on handover practices and on patient outcomes. We identified a range of training interventions, defined their content, and then proposed practical measures for improving the training effectiveness of handover practices.
METHODS: We applied the Group Concept Mapping approach to identify objectively the shared understanding of a group of experts about patient handover training interventions. We collected 105 declarative statements about handover training interventions from an exhaustive literature review, and from structured expert interviews. The statements were then given to 21 healthcare and training design specialists to sort the statements on similarity in meaning, and rate them on their importance and feasibility.
RESULTS: We used multidimensional scaling and hierarchical cluster analysis to depict the following seven clusters related to various handover training issues: standardisation, communication, coordination of activities, clinical microsystem care, transfer and impact, training methods and workplace learning.
CONCLUSIONS: Ideas on handover training interventions, grouped in thematic clusters, and prioritised on importance and feasibility creates a repository of approaches. This allows healthcare institutions to design and test concrete solutions for improving formal training and workplace learning related to handovers, and addressing informal social learning at the organisational level, with the aim of increasing impact on handover practice and patient outcomes. Measures need to be taken to assure a continuum of handover training interventions from formal training through workplace learning through less formal social learning, and to embed this training in the design of the clinical microsystem.
PMID: 23077279 [PubMed - indexed for MEDLINE]