Background Translating and scaling healthcare quality improvement (QI) and patient safety interventions remains a significant challenge. Context has been identified as a major factor in this. QI and patient safety research have begun to focus on context, with ethnography seen as a promising methodology for understanding the professional, organisational and cultural aspects of context. While ethnography is used to investigate the context of a variety of QI and safety interventions, the challenges inherent in effectively importing a qualitative methodology and its social science practitioners into this work have been largely unexamined.

Method and results We explain ethnography as a research practice grounded in theory and dependent on observations gathered and interpreted in particular ways. We then review the approach of health services literature to evaluating this sort of qualitative research. Although the study of context is an interest shared by both social scientists and healthcare QI and safety researchers, we identify three key points at which those ‘exporting’ ethnography as a methodology and those ‘importing’ it to deal with QI and safety challenges may diverge. We describe perspectival divergences on the methodology's mission, form and scale. At the level of mission we demonstrate how ethnography has been adapted to a ‘describe and feed back’ role in the service of QI. At the level of form, we show how the long-term embedded observation at the heart of ethnography can be adapted only so far to accommodate QI interests if both data quality and ethical standards are to be upheld. Finally, at the level of scale, we demonstrate one ethnographic study design that balances breadth of exposure with depth of experience in its observations and so generates a particular type of scalable findings.

Summary The effective export of ethnography into QI and safety research requires discussion and negotiation between social scientific and health services research perspectives, as well as creative approaches to producing self-reflexive data that will allow clinicians to understand their own context and so improve their own processes.