Application of COM-B model as a support to Lean Healthcare diagnostic: the case of Pharmaceutical Care Process

Abstract

Goal: The objective in this paper is to test the Capability, Opportunity, Motivation to perform Behavior model (COM-B model) from the Behavior Change Wheel (BCW) tool (Michie et al., 2014) as part of the diagnosis of Lean Healthcare. Design / Methodology / Approach: Interviews were performed with health professionals from the Pharmaceutical Care Process (PCPr) in the city of Porto Alegre-RS, responsible for the stages of selection, programming, acquisition, storage, distribution and dispensation (SPASDD) of the PCPr cycle in the municipality. The content analysis of data allowed to develop a model for diagnosing and monitoring the logistical performance of PCPr. Results: Results indicated that about 94.0% of problems related to physical and social opportunities in the processes, including improvements in the workspace, furniture, HR hiring and training, security of assets and relationships with users of the PCPr system, which if minimized can reduce the resistance of employees to the change process. Dimensions such as motivation, psychological and physical capacity have revealed lower percentages, but they are important opportunities to improve the PCPr process. Limitations of the investigation: The reduced number of respondents, however interviews were sufficient to capture the perceptions and build a scenario that may be validated in the future with other stakeholders involved in the process. Practical implications: The practical contribution resides in the identification of the behaviors to be changed in a Lean Healthcare project at the Pharmaceutical Care context. COM-B helped to identify behaviors that may hamper the efficiency of the PCPr in a large city. Originality / Value: COM-B has proved to be a useful method to support Lean Healthcare projects, the contribution of this investigation lies in expanding the applicability of COM-B model along with Lean Healthcare projects, mainly at the diagnosis stage.