Hidden, informal advice is a large but unmeasured part of haematology work. An August 2025 modified-Delphi in the UK (n=20 experts, two focus groups) produced the first consensus definition of “liaison haematology” and showed most liaison work arrives via informal channels and is poorly captured. In this post you’ll learn a reproducible, AI-enabled approach to turn transcripts, emails and audit logs into thematic, frequency and cross-segment evidence you can use for workforce planning. Follow a practical workflow you can run in minutes on your corpus using Evidano (www.evidano.com) while keeping data private and research-grade.
Fast take: what the study found
A UK modified-Delphi (published Aug 2025) with 20 haematology professionals reached consensus (87% agreement) on a working definition for “liaison haematology”. Full article: www.bmjopen.bmj.com/content/15/8/e096271.
- Core: liaison work = haematological advice (clinical + laboratory) given formally or informally to other healthcare professionals.
- The study found large volumes of unrecorded work arriving via email, phone, bleeps and messaging; only some activities are captured in standard metrics.
- Why it matters: hidden labour affects job planning, staffing and service delivery; quantifying it requires systematic qualitative analysis.
Findings snapshot (quick numbers)
| Metric | Value | Source | Note |
|---|---|---|---|
| Study type | Modified Delphi (focus groups + 2 questionnaire rounds) | BMJ Open (Aug 2025) | Methods: Teams-recorded focus groups, transcribed |
| Participants | 20 | BMJ Open | 10 consultants, 3 registrars, 3 nurses, 2 clinical scientists, 2 biomedical scientists |
| Focus groups | 2 (n=13 and n=7) | BMJ Open | Conducted online via Microsoft Teams |
| Round 1 response | 85% | BMJ Open | Agreement on tasks/routes |
| Round 2 response | 75% (met threshold) | BMJ Open | Final definition agreement |
| Consensus on final definition | 87% agreement (>75% threshold) | BMJ Open | Definition adopted |
What happened and why it matters
The authors ran two online focus groups, transcribed the sessions, extracted tasks/routes/users via content analysis, then ran two anonymous questionnaire rounds applying a 75% consensus threshold. Outputs: a list of tasks/routes and a merged definition that explicitly includes both formal and informal advice to other healthcare professionals and laboratory-result context interpretation.
- Key methodological detail: transcripts were the primary qualitative input (Teams recordings → verbatim transcripts → content coding).
- A major finding: much liaison work is un-documented and therefore excluded from standard service metrics and job plans.
- Limitation: small, UK-only panel (20 experts), useful as a reproducible proof-of-concept, not a national census.
Implications for qualitative researchers and workforce planners
For qualitative researchers
Primary takeaway: tight definitions matter. The study shows a first operational definition you can use to label and filter transcripts and messages before coding.
Design implication: include both formal and informal channels (email, phone logs, messaging apps) in sampling frames to avoid undercounting liaison work.
For workforce & service planners
Use quantified themes and frequency counts to argue for FTEs and job-plan changes: e.g., hours spent drafting advice letters vs. clinic outputs.
Cross-segment analyses (by requestor type, route, time-of-day) reveal demand patterns for staffing, on-call rotas and documentation improvements.
For clinical operations and QI teams
Map informal routes (WhatsApp, bleeps) to risk and record-keeping gaps. The Delphi flagged that insecure channels existed and were hard to port into patient records.
A measurable baseline lets you track the impact of interventions (secure messaging rollout, dedicated advice clinics).
How Evidano helps: operationalizing qualitative analysis of liaison haematology
Ingest and centralize transcripts & messages
Bring Teams transcripts, email threads, secure messaging exports and survey spreadsheets into one workspace so you can search and code across channels without manual copy/paste.
Automate coding and thematic synthesis
Use Evidano’s AI-assisted thematic analysis to extract tasks (e.g., advice, guideline drafting, lab-interpretation) identified in the Delphi and surface emergent sub-themes.
Import the Delphi code list as a seed codebook to speed initial coding and ensure comparability.
Quantify volume and cross-segment demand
Run frequency and cross-segment analyses (by requester role, route, urgency) to produce numbers that speak to managers and workforce planners.
Export tables and visualizations (co-occurrence networks, hierarchical code trees) for job-plan proposals.
Validate, quote and export for evidence
Link themes back to representative quotes and timestamps for audit-ready outputs. Use AI chat over your imported corpus to surface exemplar quotes for reports.
Security and compliance
All data is encrypted and Evidano's models are proprietary, your data is not used to train third-party models, aligning with NHS and research privacy expectations.
This week’s 6-step runbook to reproduce the study with AI
Follow these steps to convert scattered liaison work into quantified insight:
- 1) Collect: export Teams transcripts, email threads, messaging logs and any referral records for the target period (e.g., 3 months).
- 2) Import: upload files and survey spreadsheets into Evidano; apply PII redaction and custom dictionary for clinical terms.
- 3) Seed codebook: use the Delphi-derived tasks/routes as initial codes (advice to professionals, lab interpretation, guideline drafting, etc.).
- 4) Auto-code & review: run AI-assisted coding, then sample-check and refine codes to ensure clinical nuance is preserved.
- 5) Analyze: run thematic frequency and cross-segment analyses (requestor role × route × time) and generate co-occurrence networks.
- 6) Report & act: export visuals, example quotes and a short deck for workforce leads to support job-plan/resource changes.
Quick ethics note
This content is research-focused and non-diagnostic. When working with clinical transcripts, always ensure local approvals and consent processes are followed and redact patient identifiers as required.
Wrapping up & next steps
The Aug 2025 Delphi (www.bmjopen.bmj.com/content/15/8/e096271) provides a practical definition and highlights a large volume of uncaptured liaison haematology work. If you need to quantify hidden labour, test staffing scenarios or build evidence for job-plan changes, use an AI-enabled qualitative workflow to move from transcripts to numbers and narratives.
- Ready to try it? Start a pilot: ingest one month of transcripts and 100 messages into Evidano and run a cross-segment report in under a day, see www.evidano.com for a demo and secure trial.
- If you want the Delphi codebook as a starter, Evidano teams can help you import the study’s task list and reproduce the authors’ approach for your site.
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