Background There are benefits to healthcare from reporting and learning from near misses in patient care. However, there have been longstanding issues with identifying near misses, with variation in definitions. Learning is being lost, unlike in other industries that have harnessed their learning potential. The features of a healthcare near miss have never been described nor modelled. This study aimed to identify those features to support near-miss identification, reporting and learning. Methods This study took a mixed-methods approach with participants from healthcare and four high-reliability industries – aviation, maritime, nuclear and rail. Qualitative exploration helped identify the features of a near miss, while quantitative supported assessment of agreement on features between participants through the use of a scenario. Results Participants from 17 healthcare and 35 industry organisations took part. Quantitative findings demonstrated variation in agreement of the features of a near miss using Fleiss Kappa. Qualitative findings identified the following themes in relation to the features of a near miss – context dependent, involve control, are complex and represent vulnerabilities. In particular, several industries have lists of specific situations that constitute near misses that support reporting and focus. Conclusion Without clear agreement of the features of a healthcare near miss, definitions will continue to vary. This study has, for the first time, provided exploration and clarification of the features of a near miss with the offer of a healthcare model for future validation. Without addressing the fundamentals, such as agreeing what a near miss is, healthcare cannot hope to learn from them.