EIR Perceptions: Qualitative Analysis Workflow

This post gives a reproducible, two-week workflow to run qualitative analysis of EIR perceptions using the Rajshahi pilot as an example. The Rajshahi pilot (published Jul 2, 2026) reported high acceptability but highlighted intermittent internet and device constraints that limited operations.

• Sample and timing: 321 participants (305 caregivers, 16 healthcare providers), data collected July–Sept 2024, paper published Jul 2, 2026.
• Top findings: 87% electronic registration at EPI centers; caregiver satisfaction mostly 59–78% satisfied and 16–22% highly satisfied.
• Reproducible workflow: secure ingestion → AI-assisted code suggestions → human validation → thematic frequency and cross-segment analysis, exportable as reproducible reports.

The Rajshahi EIR pilot reports mostly satisfied or highly satisfied perceptions but operational friction from intermittent internet and device limitations. Caregivers and healthcare providers reported primarily positive acceptability, while implementation issues centered on connectivity and device constraints.

• Study published: July 2, 2026; data collection: July–Sept 2024.
• Sample: 321 respondents (305 caregivers, 16 HCPs).
• Key figures: 87% electronic registration at EPI centers; caregiver satisfaction mostly 59–78% satisfied, 16–22% highly satisfied.
• Original source: PLOS One

The study is a descriptive cross-sectional survey (July–Sept 2024) designed to capture perceptions of EIR-supported services. Data included Likert-scale items and open-ended responses, quantitative items were summarized with frequencies, and open-text answers were summarized descriptively. The authors note the study is not an effectiveness trial and open-ended data are not publicly shared due to identifiability concerns.

• EIR features in pilot: unique child IDs, tablet data entry, SMS reminders; system introduced in 2019, paper published July 2, 2026.
• Survey instruments: pretested semi-structured questionnaire; 5-point Likert scale for acceptability.
• Analytic approach: SPSS for descriptive stats; open responses summarized manually.

This checklist lists seven reproducible steps to reproduce the Rajshahi synthesis in Evidano in two weeks.

• 1) Gather instruments, consent forms, and de-identified transcripts; confirm IRB access for open-text data.
• 2) Ingest documents into Evidano; run secure transcription if needed (custom dictionary for local terms).
• 3) Auto-extract themes; review top 15 candidate codes with subject-matter experts.
• 4) Run AI-assisted coding across the corpus; validate on a stratified 15% sample.
• 5) Run frequency tables and cross-segment comparisons (caregiver vs. HCP; facility vs. outreach).
• 6) Create visuals: co-occurrence network, hierarchical code tree, and quote packs for each theme.
• 7) Export reproducible reports and a policy brief; link recommendations to measurable KPIs (for example, percent of sessions with offline-capable devices).

The Rajshahi pilot (published Jul 2, 2026) provides a concise example showing positive acceptability tempered by infrastructure limitations. To move from descriptive impressions to prioritized action, combine thematic coding with cross-segment frequency analysis and visualize co-occurrence patterns to reveal root causes.

• Ready to reproduce this workflow on your dataset? Start a secure pilot and Try Evidano for free to ingest transcripts, run AI-assisted coding, and produce reproducible reports.
• Ethics reminder: handle open-text responses under IRB agreements and treat this synthesis as research-only, not diagnostic.