Background: Analyses of large, complex data sets are common in health informatics and usability research. Researchers need feasible ways of streamlining data handling and analyses. We offer a useful approach across qualitative and digitalized data.

Methods: Illustrated by a usability evaluation study on a mHealth system, we present methods for managing a large set of usability data using qualitative data analysis software (QDAS). Three different data collection methods were used (usability testing, in-depth interviews, and open-ended questionnaire responses).

Results: The process began at initial transcription and all data were imported into the system. Content analysis was used throughout – from problem identification to assigning problem classifications and severity ratings to linkages with system views.

Conclusion: This approach was practical and useful as it allowed the capture and synthesis of a large number of multifaceted usability problems. We recommend this approach to other researchers performing usability evaluations on large data sets.