Faster Diagnosis: Qualitative Analysis of Training Interventions

Multilevel onsite training combined with a 6-month mentorship reduced facility diagnostic interval by 54.3% and raised provider knowledge to about 91/100 in the Ethiopia pilot.

• The program trained 1, 020 health extension workers (HEWs) and delivered immersive hospital and primary-care courses between Jan–Sep 2024.
• Median knowledge scores rose from 54.6 to 90.9 (primary) and from 36.4 to 90.9 (secondary); diagnostic interval fell from 56.5 to 25.8 days (−54.3%).
• Budget was USD 52, 762, and program adaptations (mentorship cadence, pictorial HEW modules) mattered amid conflict and supply shortages.

A University of Gondar-led program (Jan–Sep 2024) delivered immersive onsite courses for clinicians, pictorial modules for 1, 020 health extension workers, and a 6-month mentorship program, producing large knowledge and practice gains and a 54.3% reduction in diagnostic interval.

• Design: quasi-experimental pre–post mixed-methods with KAP surveys, chart reviews (n=100 patient charts), in-depth interviews (IDIs) and focus group discussions (FGDs).
• Operational constraints: active regional conflict (April 2023 onward), seasonal rains, and reagent shortages were tracked in implementation logs.

The intervention combined immersive 10-day training for hospital clinicians, seven-day workshops for primary providers, and a five-day pictorial curriculum for HEWs, followed by monthly (then biweekly) mentorship and tele-support through April–September 2024.

• Process fidelity: 90% of planned training days were delivered and 87% attended all sessions.
• Quantitative impact: large KAP increases and tripled HEW referrals (0.4 → 1.2 referrals/HEW/month).
• Context: supply shortages and strained tertiary capacity limited speed-to-treatment despite faster diagnosis.

This seven-step checklist reproduces the study analysis using transcripts, charts, and logs. Step 1: Gather inputs, including KAP surveys, 100 patient charts, IDI/FGD audio, mentorship logs, and training agendas (Jan–Sep 2024). Step 2: Upload and preprocess, use Evidano transcription with custom dictionary entries and enable PII redaction. Step 3: Define a codebook, import CFIR-based codes or start with auto-suggested themes and refine. Step 4: Run thematic and frequency analysis, generate theme counts, co-occurrence matrices, and timeline-coded events (for example, June 2024 adaptations). Step 5: Run cross-segment analysis, comparing themes by facility tier, district, and mentorship cadence. Step 6: Validate, pulling representative de-identified quotes, checking intercoder consistency, and reconciling qualitative findings with KAP and chart outcomes. Step 7: Deliver, export visualizations and an executive brief for MOH with clear operational recommendations (for example, increase tele-support cadence and procure reagents).

The PLOS Medicine study (published June 29, 2026) demonstrates that multilevel onsite training plus mentorship can cut diagnostic delays substantially, and rapid explanatory qualitative analysis is required to translate training into system fixes such as supply chain improvements, motivation interventions, and referral coordination.

• If you are evaluating trainings or scaling mentorship, use AI-enabled qualitative analysis to connect participant experiences to measurable outcomes quickly.
• Ready to reproduce these analyses on your corpus? Try Evidano for free to upload your transcripts, logs, and charts and get a thematic and cross-segment report in hours, not weeks.