Listen, look, link and learn: a stepwise approach to use narrative quality data within resident-family-nursing staff triads in nursing homes for quality improvements

Abstract

PurposeThe use of qualitative data to assess quality of care in nursing homes from the resident’s perspective has shown to be valuable, yet more research is needed to determine how this data can be used to gain insight into the quality of care within nursing homes. Whereas it is crucial to stay close to the stories that are the strength of qualitative data, an intermittent step to classify this data can support the interpretation and use. Therefore, this study introduces an approach that enables the use of narrative quality of care data to learn from and improve with.DesignA cross-sectional mixed-methods study in which qualitative data were collected with the narrative quality assessment method Connecting Conversations and interpreted for analysis.MethodsConnecting Conversations was used to collect narrative data about experienced quality of care in nursing homes according to residents, their families and nursing staff (triads). Data analysis consisted of coding positive/negative valences in each transcript.FindingsA stepwise approach can support the use of narrative quality data consisting of four steps: (1) perform and transcribe the conversations (listen); (2) calculate a valence sore, defined as the mean %-positive within a triad (look); (3) calculate an agreement score, defined as the level of agreement between resident-family-nursing staff (link); and (4) plot scores into a graph for interpretation and learning purposes with agreement score (x-axis) and valence score (y-axis) (learn).ConclusionsNarrative quality data can be interpreted as a valence and agreement score. These scores need to be related to the raw qualitative data to gain a rich understanding of what is going well and what needs to be improved.