Re-Imagining the Data Collection and Analysis Research Process by Proposing a Rapid Qualitative Data Collection and Analytic Roadmap Applied to the Dynamic Context of Precision Medicine

Our implementation science study focuses on implementing a new way of practice and offers methodological specificity about how to rapidly investigate an individually tailored precision medicine intervention. A qualitative study advancing a new methodology for speedily identifying barriers and enablers to implementation in the context of childhood cancer. Data were collected through rapid ethnography, coded using the Consolidated Framework for Implementation Research, and analysed by Sentiment Analysis. Thirty-eight data collection events occurred during 14 multidisciplinary tumour board meetings, 14 curation meetings, and 10 informal conversations. Sentiment Analysis distilled Consolidated Framework for Implementation Research codes to reveal key barriers and enablers to implementation. A traffic light labelling system has been used to present levels of positivity and negativity (green for strong enablers and red for strong barriers), highlighting levels of concern regarding implementation. Within the intervention design characteristics, "Adaptability" was the strongest enabler and "Design quality and safety" the strongest barrier. Among the contextual factors: "Networks and communication" were the strongest enabler, and "Available resources" were the strongest barrier. Overall, there was a higher percentage of negative sentiment towards intervention design characteristics and contextual factors than positive sentiment, while more concerns were raised about intervention design factors than contextual factors. This study offers a rapid qualitative data collection and analytic methodological roadmap for establishing barriers and enablers to a paediatric precision medicine intervention.