Scale Findings: Qualitative analysis of PIP review

The Timms Review interim report (9 July 2026) found PIP is widely valued but not fit for purpose, drawing on over 38, 000 submissions and reporting an assessment process described as dehumanising by about 90% of respondents.

A rapid, reproducible qualitative workflow should combine a clear codebook, AI-assisted auto-coding with human validation, and cross-segment quantification to convert lived-experience evidence into decision-ready recommendations.

Use Evidano to ingest, auto-code, quantify, and export quotable excerpts with provenance while protecting sensitive data.

• The Timms corpus includes 38, 000+ Call for Evidence responses collected during 19 March–28 May 2026.
• The interim report was published on 9 July 2026 and highlights that roughly 90% of respondents described assessments as dehumanising.
• A seven-step checklist in this post shows how to move from import to insight and produce stakeholder-ready outputs in days.
• Evidano ingests submissions, supports PII redaction and custom dictionaries, auto-codes with human validation, and exports reproducible tables and quotable excerpts.

The Timms Review interim report (9 July 2026) concluded PIP is widely valued but not fit for purpose, citing an assessment process described as dehumanising by about 90% of respondents and drawing on over 38, 000 submissions. Read the government announcement on GOV.UK and the interim report on GOV.UK.

• Why analysts care: the corpus is a large, co-produced dataset with rich lived-experience evidence (n>38, 000) that must be thematically coded, compared by condition (for example, fluctuating vs visible), and translated into operational fixes.
• Payoff: extract reproducible themes, quantify prevalence, compare segments, and produce stakeholder-ready visualizations in days not months, then iterate as the Review moves to design and testing in autumn 2026.

The Timms Review ran a national co-produced review combining a public Call for Evidence (19 March–28 May 2026), workshops, and sector submissions, and the compiled evidence pack feeds the steering group's deliberations for design and testing ahead of final recommendations in autumn 2026.

Corpus types include free-text survey responses, organisational submissions, workshop notes, and expert evidence.

• Key analytic challenges include variable length and structure, multiple conditions per respondent, fluctuating versus fixed symptoms, and emotive language (words like “dehumanising” and “stressful”).
• Analysis goals are reliable theme extraction, codebook consistency, cross-segment frequency counts (by condition, age, region), and quoting representative lived-experience examples for outputs.

This checklist gives seven concrete steps you can execute in days to reproduce a rigorous qualitative analysis of the Timms corpus.

• 1) Gather inputs: import Call for Evidence exports, submissions, and workshop notes into one Evidano project.
• 2) Normalize terms: apply a custom dictionary for clinical terms and common synonyms (for example ‘fluctuating’ versus ‘episodic’).
• 3) Draft codebook: create 20–40 top-level codes from an initial 500-document sample.
• 4) Auto-code + validate: run AI-assisted coding, then validate a 5–10% stratified sample for inter-coder reliability.
• 5) Quantify & segment: produce frequency tables and cross-segment comparisons (condition, age, region).
• 6) Visualize & export: generate co-occurrence networks, hierarchical code trees, and clickable quote lists for briefings.
• 7) Turn findings into decisions: map top 5 policy levers and attach representative evidence to each recommendation.

The Timms Review interim report (9 July 2026) offers a unique, large-scale repository of lived experience that should drive PIP reform, and credible recommendations require robust qualitative coding, transparent quantification, and repeatable reporting.

Explore how Evidano accelerates thematic and cross-segment analysis, protects sensitive data, and produces reproducible outputs for policy teams at Evidano, or Try Evidano for free.