Quick Workflow: Qualitative Analysis of RCDP

Evidano is an AI-powered qualitative data analysis platform that automates transcription, AI-assisted coding, and cross-segment analysis while keeping clinical data secure.

This post gives a seven-step, reproducible Evidano workflow to turn RCDP CCU interviews into stakeholder-ready reports following the July 6, 2026 PLOS One phenomenological study methods.

• The source study: Xie et al., published July 6, 2026, studied 13 CCU nurses (data Apr–Jul 2025) with interviews averaging ~43 minutes.
• Evidano speeds the pipeline with automated transcription (custom dictionaries and optional PII redaction), AI-assisted coding mapped to Tanner’s noticing→interpreting→responding→reflecting, and cross-segment co-occurrence analysis.
• Use the included seven-step checklist to reproduce the paper’s inductive coding then Tanner-model mapping and produce exportable visuals and quotable excerpts in hours.

Fast take: Xie et al. (Published July 6, 2026) report a phenomenological study of rapid cycle deliberate practice for electrocardiographic monitoring in a Zhejiang Province CCU, with 13 nurses (ages 21–45; experience 3–20 years) describing shifts across Tanner’s noticing→interpreting→responding→reflecting sequence. Read the full paper: PLOS One article.

• Why it matters: RCDP’s pause, coach, resume sequence appears to change perception, reasoning, responses, and professional identity, outcomes best captured by qualitative methods.
• What you get here: an actionable qualitative analysis workflow tailored to RCDP transcripts and simulation field notes, optimized for Evidano (www.evidano.com).

The study ran a three-phase, station-based RCDP program focused on ECG rhythm recognition, morphology, arrhythmia classification, and emergency response. Participants practiced, were paused when errors occurred, received immediate coaching, and resumed until objectives were met.

• Design: phenomenological interviews plus field observation, with reflexive journaling used to reduce bias.
• Analysis: inductive NVivo coding, then mapping themes to Tanner’s noticing→interpreting→responding→reflecting.
• Limitations: single site, n=13, self-reported changes were not triangulated with objective performance metrics.

Follow these steps to turn RCDP interviews into a stakeholder-ready report.

• 1) Collect and label: gather audio, field notes, and simulation logs; label by participant metadata (years of experience, role).
• 2) Transcribe in Evidano: use a custom dictionary for ECG terms and enable PII redaction.
• 3) Import the paper codebook or run seed-topic extraction: start inductive coding with AI suggestions mapped to Tanner’s noticing→interpreting→responding→reflecting.
• 4) Validate codes: run a two-coder check on 20% of transcripts, reconcile disagreements, and lock code definitions.
• 5) Run cross-segment analyses: frequency counts, co-occurrence matrices, and quote distributions by experience level and station.
• 6) Produce visuals: export co-occurrence networks and code-to-subcode hierarchies for presentations.
• 7) Deliver and iterate: use the Evidano AI chat to generate an executive summary and pull 6–8 representative quotes for immediate use in training decks.

If your team runs simulation training or RCDP-style programs, Evidano accelerates the entire path from audio to stakeholder-ready reports while keeping data secure.

• Try Evidano for free to upload one interview and test transcription and auto-coding.
• For multi-site RCDP evaluations, export cross-site dashboards and co-occurrence visuals to measure whether pause, coach, resume consistently produces the perceptual and identity shifts reported in the PLOS One study.

Ethics note: this guidance is research-focused and non-diagnostic; always follow institutional review and consent procedures when handling clinical transcripts.