Researchers, public health teams, and healthcare policymakers need qualitative evidence that preserves patient experience while revealing patterns across interviews. The obstetric fistula qualitative study conducted in Ghana's Kpandai District shows why that work matters: women described physical suffering, stigma, economic loss, and barriers to timely care. The study also provides a useful model for AI-enabled qualitative research because the researchers transcribed interviews verbatim, analyzed thematically, and developed themes collaboratively. Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze sensitive interviews, documents, and survey responses while supporting transcription, thematic analysis, and cross-segment comparison. This article summarizes the findings reported in PLoS ONE, “Harrowing experiences of vagina fistula victims in the Kpandai District of Ghana” and explains how AI can accelerate synthesis without replacing ethical review or researcher judgment.
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- obstetric fistula qualitative study
- qualitative analysis of obstetric fistula
- AI qualitative research healthcare
- thematic analysis health interviews
- Ghana maternal health research
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