Collaborative Analysis of Observational Data in Healthcare




Interdisciplinary research, Health services research, Research design, Observer variation, Qualitative research, Data analysis


Solving complex problems can be challenging as they often involve multiple layers of related issues and factors. Observational research is a helpful tool for understanding healthcare's complex and contextually dependent problems; however, observations can be time-consuming and resource-intensive, particularly when including the analysis process. As a result, researchers may utilize other qualitative methods, such as interviews or focus groups. However choosing a strategy different than observations could miss subtleties of care that happen in practice. It is easy to underestimate the value of data gathered through firsthand observations of patient-provider and team interactions. One solution to making observations a more convenient method in healthcare research is collaborating in the analysis process. Research collaboration involves establishing an interprofessional research team with diverse backgrounds and professional perspectives. In this way, the group comprises individuals from various roles and different professional backgrounds to ensure exhaustive findings and improve the reliability and accuracy of the results. The diversity in the team represents the intricate dynamics in the complex system of care. Although there are guidelines for collaborative analysis in a traditional ethnographic study, there must be more focus on healthcare research. This paper explains the concepts and features of collaborative analysis in interprofessional research. This approach offers a systematic way to construct a code book, which can produce comprehensive and valuable insights into the complex dynamic of care.


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How to Cite

McCartan, C., King, S., & Roduta Roberts, M. (2023). Collaborative Analysis of Observational Data in Healthcare. New Trends in Qualitative Research, 16, e786.