Abstract
IntroductionLean, especially Value Stream Mapping is increasingly used in hospitals to optimize processes. This method, which originated in the automotive industry, enables all staff involved in the process to make it more customer-friendly. Despite the widely reported success of Lean projects, they have failed in some cases. This study investigated the contextual factors and mechanisms that contribute to a successful implementation of Value Stream Mapping. MethodsValue Stream Mapping was applied to the discharge process in four breast cancer centers. A mixed-method approach was used in two steps. First, to verify the successful implementation, defined as time optimization, time measurement was conducted at three points in time and analyzed using an ANOVA. Second, an analysis of contextual factors was combined with a qualitative content analysis of mechanisms based on normalization process theory, using routine data, meeting protocols, field notes, and interview transcripts as data source. ResultsAt one of the four breast cancer centers, lead- and waiting time were significantly reduced; at the others, these reductions did not occur. Failure/success cannot be explained by the size of the hospital, the number of cases or staffing levels. The variable project team composition is evident, especially leadership involvement. DiscussionA comparative analysis was conducted to identify the factors that led to success. These factors were: participation of all leaders relevant to the process, in the case of the discharge process including medical and nursing leaders; dissemination of the changes from the project team to colleagues including its sense and possibility to discuss it; joint reflection of the implementation process in regular work team meetings. ConclusionsThese results confirm the important role of leadership in implementation projects. Leadership support enabled the mechanisms found. The used combination of theoretical approaches from management research and implementation science determined the interpretation and should be applied more often in implementation science.
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