Evidano is an AI-powered qualitative data analysis platform that accelerates PSAT-style mixed-methods sustainability assessments from multilingual audio to actionable briefs. Fast take: A mixed-methods PSAT study published 25 June 2026 evaluated Rwanda’s mass drug administration (MDA) program and found a moderate sustainability capacity (overall score 3.75/5; n=21 interviews, 17 PSAT respondents). Read the original paper at PLOS Neglected Tropical Diseases. For qualitative researchers and health program analysts, this is a practical case of qualitative sustainability assessment: strong partnerships (4.1) and political support (3.9) versus weak funding stability (3.3) and strategic planning (3.5). In this post we show how to operationalize those PSAT insights faster and more reproducibly using AI-enabled qualitative research workflows (from Kinyarwanda transcripts to cross-segment theme comparison) with secure pipelines on Evidano. You’ll get a short workflow, concrete examples tied to the Rwanda findings, and a pilot checklist you can run in two weeks.
Key Takeaways
Evidano is an AI-powered qualitative data analysis platform that speeds PSAT-style mixed-methods sustainability assessments from multilingual audio through coding to decision-ready briefs.
The Rwanda MDA PSAT (25 June 2026) produced a moderate overall sustainability score (3.75/5), with partnerships highest (4.1) and funding stability lowest (3.3); teams can convert those findings into prioritized action in 10–14 days using AI-assisted workflows.
- The Rwanda study: overall 3.75/5 (n=21 qualitative informants, 17 PSAT respondents), partnerships 4.1, funding stability 3.3, strategic planning 3.5.
- Automated transcription, translation, and AI-assisted coding reduce manual review hours and inter-coder drift when mapping open responses to the PSAT’s eight domains.
- Cross-segment frequency and co-occurrence analyses reveal where problems cluster (e.g., funding with data quality), enabling targeted interventions.
- Evidano supports PII redaction, end-to-end encryption, and a no-third-party-model-training policy to meet donor and ethical requirements.
Findings snapshot
The findings snapshot summarizes the key metrics and sources cited in the Rwanda MDA PSAT study.
See the table below for quick reference to sample sizes, domain means, and the original publication source.
Findings snapshot
| Metric | Value | Notes / Source |
|---|---|---|
| Publication date | 25 June 2026 | PLOS Neglected Tropical Diseases |
| Key informants (qualitative) | 21 | Interviews recorded in Kinyarwanda; transcripts translated to English |
| PSAT respondents | 17 | Domain means & SDs calculated per PSAT |
| Overall sustainability score | 3.75 / 5 | Mixed-methods PSAT result |
| Top domain | Partnerships (4.1) | Strong government + donor + community ties |
| Lowest domain | Funding stability (3.3) | 97% of financing 2019–2023 external per RBC data |
What happened: the PSAT mixed-methods application
The PSAT mixed-methods application combined an adapted Program Sustainability Assessment Tool and open-ended interviews to assess eight sustainability domains in Rwanda’s MDA program.
The team used an adapted Program Sustainability Assessment Tool (PSAT) and open-ended interviews to assess eight sustainability domains (political support, funding stability, partnerships, organizational capacity, program evaluation, program adaptation, communications, strategic planning). Surveys were completed electronically (Qualtrics) and interviews were audio-recorded in Kinyarwanda, transcribed verbatim, and translated into English.
- Design: Mixed-methods PSAT plus deductive thematic coding aligned to PSAT domains.
- Sample: 21 stakeholders (government, donors, implementers); 17 completed PSAT.
- Key numeric takeaways: overall 3.75/5; partnerships 4.1; funding stability 3.3; strategic planning 3.5.
- Operational notes relevant to qualitative workflows: multilingual audio, decentralized data sources, variable denominator estimation across districts.
Implications for researchers and program teams: qualitative sustainability assessment
Mixed-method PSAT outputs provide comparable domain scores and explanatory quotes that guide where to prioritize sustainability investments and interventions.
These results matter for qualitative teams because they highlight how mixed-method PSAT outputs produce both domain scores (comparable metrics) and rich explanatory quotes that reveal causes (e.g., donor dependence, understaffing, data fragmentation). Turning these into action requires fast, trustworthy qualitative synthesis and cross-segment comparison.
- Translate domain scores into decision levers: treat funding stability (3.3) as a priority risk register item; use partnerships (4.1) as leverage for domestic advocacy.
- Use interview excerpts to validate who experiences the problem (central vs district staff) and where interventions should focus (data systems, workforce, budgeting).
- Standardize denominator/target definitions across districts by extracting and comparing coded phrases that describe local methods (e.g., 'ubudehe lists', 'CHW assessments').
Do more, faster with Evidano (mapped to the Rwanda use case)
Problem: multilingual audio and translation needs
Multilingual audio and translation were bottlenecks in the Rwanda study, with interviews recorded in Kinyarwanda and translated to English.
Evidano solution: automated transcription plus translation with custom dictionaries to preserve local terms like 'imihigo' and 'ubudehe', plus PII redaction for ethical storage.
Problem: inconsistent coding and domain alignment
Inconsistent manual coding slows mapping open-ended responses to the PSAT’s eight domains and causes inter-coder drift.
Evidano solution: import the PSAT codebook and run AI-assisted coding to auto-tag excerpts to PSAT domains, then review and lock codes to save reviewer hours and increase consistency.
Problem: comparing segments (central vs district, donors vs implementers)
Different denominator estimation approaches across districts make cross-segment comparison difficult without standardized extraction and analysis.
Evidano solution: run cross-segment frequency and co-occurrence analyses that show which themes concentrate in which groups, and generate co-occurrence networks to test whether 'data quality' clusters with 'funding' or 'political targets'.
Problem: presenting evidence to funders and stakeholders
Stakeholders require persuasive PSAT scores plus quotes, visuals, and an actionable plan to fund follow-on work.
Evidano solution: generate exportable visuals (word clouds, hierarchical code→subcode maps, co-occurrence networks) and clickable quote libraries tied to PSAT domains for rapid stakeholder briefs.
Security & governance
Health program data are sensitive and often subject to donor restrictions and ethical requirements.
Evidano solution: end-to-end encryption, no third-party model training on your data, role-based access, and audit logs, aligning with the consent and de-identification expectations noted in the Rwanda study.
Two-week pilot: checklist to reproduce a PSAT mixed-methods synthesis in Evidano
This two-week pilot checklist shows how to reproduce a PSAT mixed-methods synthesis in Evidano in 10–14 days.
Run-book to go from raw audio plus PSAT scores to a decision brief in 10–14 days:
- Day 0–2: Ingest files, upload audio, PSAT spreadsheets, and any district reports to Evidano; set project language (Kinyarwanda) and add custom dictionary terms (imihigo, ubudehe).
- Day 3–5: Auto-transcribe plus translate; run PII redaction; review and correct transcripts (accuracy boost where local terms appear).
- Day 5–7: Import PSAT domain codebook; run AI-assisted coding to tag excerpts to the eight PSAT domains; review and finalize codes.
- Day 8–10: Run cross-segment frequency and co-occurrence analyses (e.g., funding mentions by district vs central); generate top themes and illustrative quotes per domain.
- Day 11–12: Create visuals (domain score table, quote packs, co-occurrence network) and assemble a 1-page decision brief with recommended actions tied to domain scores.
- Day 13–14: Share interactive report link with stakeholders, collect comments, and produce a brief FAQ and next-step backlog for budget/HR interventions.
FAQ: qualitative sustainability assessment
What is a qualitative sustainability assessment and when should I use it?
A qualitative sustainability assessment combines structured tools like the PSAT with interviews or focus groups to measure capacity across domains and explain the reasons behind scores.
Use a qualitative sustainability assessment when you need both comparable domain metrics and grounded explanations to plan sustainability investments and prioritize interventions.
How do I compare segments (districts, donor vs govt) reliably?
Standardize the codebook and run cross-segment frequency and co-occurrence analyses to surface reliable differences between groups.
Evidano automates segment comparisons and surfaces statistically meaningful differences in theme prevalence, and the study recommends validating differences with targeted follow-ups.
Is this approach secure for health program data?
This approach can be secure if you follow consent, de-identification, and storage best practices.
Evidano supports PII redaction, encrypted storage, and a no-third-party-model-training policy to meet typical donor and ethical requirements noted in the Rwanda study.
Ethics note
Maintain informed consent and local IRB approvals when handling interview audio and transcripts.
This is non-diagnostic research focused on program sustainability; always follow local ethical review and data-handling protocols.
Wrapping up & next step (try this in Evidano)
AI-assisted workflows can cut manual synthesis time and improve comparability for PSAT-style mixed-methods sustainability assessments.
If your team runs PSAT-style mixed-methods or any qualitative sustainability assessment, you can cut manual synthesis time and improve comparability with AI-assisted transcription, translation, codebook import, and cross-segment analysis. For the Rwanda MDA study specifically, prioritize funding-stability scenarios, workforce planning, and data-standardization workstreams, all of which you can accelerate as described above.
- Ready to pilot? Upload one campaign’s audio plus PSAT spreadsheet to Evidano and follow the two-week checklist.
- For security-sensitive projects, note Evidano’s encryption and data governance options before onboarding stakeholders.
To start a pilot or request a demo, Try Evidano for free.