Spotlight: qualitative analysis of nursing home citations

Collect inspection PDFs, family interviews, staff statements, and Medicare snapshots. Include dates and facility identifiers in filenames or a metadata spreadsheet.

Use Evidano's ingestion to OCR PDFs and import spreadsheets so every document is tagged with source, date, and facility (www.evidano.com).

Transcribe audio interviews with custom dictionary entries for clinical terms and facility names; redact PII during ingestion.

Translate non-English interviews using the platform's translation pipeline, preserving dictionary mappings for consistency.

Import an initial codebook (e.g., staffing, medication errors, infection control, communication, dignity) and let AI propose subcodes from the corpus.

Review AI-proposed codes, accept/merge, then apply automated coding across the dataset to speed coverage and create hierarchical theme→subcode structures.

Run frequency analysis by facility, time window, and reporter (family vs staff). Use co-occurrence networks to identify which themes cluster with high-severity citations.

Export visualizations (word cloud, co-occurrence network, hierarchical code tree) for stakeholder briefs.

Combine citations (quantitative) and coded narratives to produce an evidence map: which facilities have recurring themes linked to outcomes, and which themes predict higher citation rates.

Produce a reproducible report and an evidence-backed set of recommendations for inspectors, operators, or advocacy groups.

This is a classic mixed-methods opportunity: pair inspection metrics with coded narratives to move from correlation to plausible causal mechanisms.

Prioritize inter-coder reliability checks after AI-assisted coding and document any code merges for auditability.

Use theme frequency and verbatim quotes to build user journeys for residents and family members; map pain-points to concrete product or service fixes.

Segment quotes by role (family, CNA, nurse, ombudsman) to reduce confirmation bias in design decisions.

Identify which operational themes (staffing, documentation, infection control) consistently precede high-severity citations to target inspections and training.

Use reproducible dashboards to track improvement over time after interventions are implemented.

This guidance is research-focused and non-diagnostic. Preserve consent and privacy; redact PII and follow IRB or local review rules when required.

Evidano ingests PDFs, audio, and spreadsheets and tags documents with metadata so you can combine inspection reports, family interviews, and Medicare snapshots into one analyzable corpus (www.evidano.com).

Import your codebook or start from a template. Evidano proposes subcodes, applies them at scale, and calculates code frequencies and inter-coder agreement to keep analysis auditable.

Run cross-segment frequency comparisons (by facility, date range, reporter type) and visualize co-occurrence networks to spot recurring failure modes quickly.

Create shareable evidence maps, clickable quote banks, and dashboards that make it simple to brief inspectors, operators, or advocacy groups.

Data is encrypted in Evidano and never used to train third-party models, important for sensitive health and resident data.