04
Step 04 Tool
Evidence Module
Strategize evidence collection & packaging: identify the right evidence, match it to your stakeholders, and package it for impact.
0% checklist complete
How to collect the right evidence — in 3 steps
Follow these steps in order. Each builds on the previous one. Use the checkboxes to track your progress.
1
Define your Change Ask
Your ask determines everything. Start here before choosing any evidence.
▾
- I have articulated a specific, concrete Change Ask (e.g. inclusion of CUP patients in national precision medicine policy).
- I know the type of change I'm asking for: regulatory reform / funding allocation / clinical integration / other.
- I have reviewed (or created) a Change Ask Narrative to sharpen my ask.
2
Identify the relevant Readiness Dimension
Match your ask to the area of the health system you are targeting.
▾
- Regulatory environment around personalized healthcare
- Healthcare budget allocation & reimbursement
- Clinical practice guidelines & integrated care models
- Digital infrastructure
- Educated workforce
Tip: Your Change Ask may touch more than one dimension — that's fine. Prioritise the one with the greatest gap based on your readiness assessment (Step 2 of the Roadmap).
📊 PM Implementation Readiness Assessment Tool (Step 2 resource)
3
Select evidence types & find examples
Use the repositories to find evidence matched to your dimension and stakeholder.
▾
- I have identified the stakeholder(s) I am advocating to (see Stakeholder Mapping, Step 3).
- I have reviewed the Evidence Types Repository tab (above) for my readiness dimension.
- I have checked the Evidence Examples Repository tab for concrete sources to use or adapt.
- I have a shortlist of 3–5 pieces of evidence that directly support my Change Ask.
Evidence Types Repository
Select a readiness dimension to see the most relevant evidence types and the decision-makers they are best suited for.
| Evidence Type | Stakeholders / Decision-Makers |
|---|---|
Clinical, research & implementation evidence |
Director of Health Policy & Innovation
Director of National Research Institutes
Minister / Secretary of Health
Head of HEOR
HTA Program Director
|
Quantitative data on digital usage; case studies on impact; financial analyses (cost-saving potential) | |
Utilisation of biobanks and health registers as resources for personalised medicine | |
Evidence on improved quality of life and clinical outcomes from precision medicine | |
Data on incidence of specific cancer mutations and available targeted treatments |
| Evidence Type | Stakeholders / Decision-Makers |
|---|---|
Patient case studies showing improved quality of life & productivity |
Policymakers & Public Health Officials
HTA Program Directors
Chief Reimbursement Officers (Health Insurers)
Head of Coverage & Reimbursement (National Insurance Agencies)
|
Data on rising healthcare expenditure and oncology drug development costs | |
Evidence on increased use and clinical impact of biomarker-driven cancer therapies | |
Documentation of affordability and access gaps in precision oncology | |
Policy and economic analyses linking precision oncology to improved outcomes and system efficiency |
| Evidence Type | Stakeholders / Decision-Makers |
|---|---|
Evidence on clinical integration practices supporting provider education & alignment with PM standards |
Director of Healthcare Delivery / Integrated Care
Health Policy Director
Director of Clinical & Economic Evidence
Head of Clinical Innovation
|
Data demonstrating successful incorporation of precision medicine into routine treatment pathways | |
Position statements from ESMO & ASCO supporting advanced treatment standards | |
Peer-reviewed publications showing improvements in care efficiency and outcomes | |
Analyses linking innovative care models to enhanced quality of care and system performance |
| Evidence Type | Stakeholders / Decision-Makers |
|---|---|
Case studies on impact of bias mitigation on equity and clinical decision-making |
Director of Digital Health / Chief Data Officer
Head of Health Informatics & Technology
Directors of Interoperability
Chief Medical Informatics Officers (CMIOs)
|
Quantitative data on patient access, satisfaction, and EHR preferences | |
Qualitative evidence from patient feedback on digital user experience | |
Utilisation of biobanks and health registers as critical PM resources |
| Evidence Type | Stakeholders / Decision-Makers |
|---|---|
Clinical outcomes data |
Senior Regulators for Medical Training
Directors of Curriculum Development
Heads of CME Programs
Chief Medical & Nursing Officers
Chief Licensing Officers
Education Chairs, PM Committee Leaders
|
Educational frameworks | |
Competency frameworks | |
Workforce data |
Evidence Examples Repository
Concrete examples mapped to evidence type and readiness dimension. Use these as starting points to locate or adapt real sources for your advocacy.
| Evidence Type | Example |
|---|---|
Clinical, research & implementation evidence |
Widespread use of gene sequencing across hospitals indicating clinical acceptance. Long-standing use of genetic information in hereditary disease counselling, now expanding to targeted treatments. |
Quantitative & financial evidence |
Ethical and legal frameworks emphasising confidentiality, individual rights, data protection, and research ethics approval. National infrastructure standards, secure data sharing protocols, and economic sustainability analyses for PM integration. |
Biobank & health register utilisation |
NordForsk (2014) policy paper on joint Nordic registers and biobanks: harmonisation of national registers provides a basis for high-value international research benefiting society. |
Quality of life & policy inclusion evidence |
UK Care Act 2014 — legal framework for technology use in health and care services. UK Government Digital Strategy (2013) and Department of Health's Digital Strategy (2012) on cultural change for digital adoption in healthcare. |
Cancer mutation incidence & targeted treatments |
Regional datasets show a meaningful proportion of metastatic colorectal cancer patients harbour actionable alterations (e.g. RAS wild-type, BRAF V600E), making them eligible for targeted biologics and clinical trials — yet many remain untested. Patients with RAS wild-type tumours treated with anti-EGFR antibodies show improved outcomes vs. non-targeted regimens, illustrating how routine mutation testing translates into better survival. |
| Evidence Type | Example |
|---|---|
Biomarker-driven therapy clinical impact |
Factors considered by Australia's PBAC in recommendations for new drug coverage: clinical impact, cost-effectiveness, and budgetary impact. See: nature.com/articles/s41698-022-00343-y |
Affordability & access gaps |
Statistical data on rising healthcare costs as a fraction of GDP in higher-income countries (US and Australia, 2019). Specific examples include increasing use of biomarker-dependent oncology drugs and adoption of managed entry agreements in the US, UK, and Australia to address affordability crises. |
Patient case studies |
Patient case stories and survey narratives from oncology patients using a treatment under HTA review showed improvements in quality of life and day-to-day functioning, giving decision-makers real-world context on the social and productivity value of therapy (Oncoguia). |
Rising healthcare expenditure data |
IQVIA Institute analyses show global spending on oncology medicines has risen sharply, reaching close to $200B in the early 2020s and projected to exceed $300–370B in coming years, driven by novel cancer therapies and more patients treated for longer durations. |
Policy & economic analyses |
Factors considered by Australia's PBAC in recommendations for new drug coverage and reimbursement — clinical impact, cost-effectiveness, and budgetary impact. See: nature.com/articles/s41698-022-00343-y |
| Evidence Type | Example |
|---|---|
Clinical integration practices |
Joanna Briggs Institute scoping review methodology. AGREE collaboration instrument for assessing rigour of guideline development processes. |
Literature review sources |
Databases: CINAHL, Scopus, PubMed; manual searches of health-related websites and national/international organisational health policies and documents. |
Peer-reviewed publications |
Evidence from critiques of Australian clinical practice guidelines (CPGs): conflicts of interest among panelists, recommendation validity, end-user involvement, and the GRADE system for assessing strength of recommendations. |
PM in routine pathways |
Joanna Briggs Institute scoping review methodology, and approaches such as the AGREE collaboration's instrument for assessing the rigour of guideline development processes. |
Innovative care model analyses |
Evidence from critiques of Australian clinical practice guidelines (CPGs): conflicts of interest among panelists, recommendation validity, end-user involvement, and the GRADE system for assessing strength of recommendations. |
| Evidence Type | Example |
|---|---|
Bias mitigation case studies |
Outcomes from seminars and roundtables by the Belgian Association of Hospital Managers (BVZD/ABDH). Expert opinions from multi-stakeholder discussions. International best practices in real-world data usage in healthcare and research. |
EHR access & patient satisfaction data |
Joanna Briggs Institute methodology for scoping reviews. AGREE collaboration instrument for guideline development rigour. |
Patient feedback & qualitative evidence |
Large quantitative survey with rare disease patients and family members exploring attitudes to data sharing and data protection in research and healthcare settings. |
Biobank & register utilisation |
Examples from Finland show that combining biobanks, electronic medical records, and national health registers can create a foundation for personalised medicine and faster innovation — highlighting the need to invest in better data linkage and broader use of these assets. |
| Evidence Type | Example |
|---|---|
Educational frameworks |
NHS Genomic Medicine Service, National Genomics Education Programme, government policies and strategies related to genomics and healthcare. |
Competency frameworks |
Case studies from the Netherlands (ZIN) and England (NICE) on implementing HTA and PM competency standards. |
Workforce data |
Literature review and iterative discussions with CEE HTA and patient experts. Inputs from a workshop (June 2, 2022) with stakeholders from CEE and Western European countries. |
Clinical outcomes data |
Example to be added by the FT3 team. |
How to package your evidence
Packaging is about presentation, not volume. The same evidence can succeed or fail depending on how it's delivered to who receives it.
1
Anchor everything to your Change Ask
Review your Change Ask before building any output. Every piece of evidence, every data point, every story must circle back to the specific shift you are requesting. Drop anything that doesn't.
📄 Change Ask Narrative Guideline2
Shape the message to your stakeholder
Tailor format, tone, and key messages to the person you're speaking to. Experts need technical depth. Politicians and the public need stories and summaries. Use your Stakeholder Map to guide this.
🗺 Stakeholder Mapping Tool3
Apply the packaging principles below
Use the checklist below to review your advocacy output before presenting it.
Packaging checklist
- Clear, concise format — I am presenting evidence in an accessible form (executive summary, infographic, or visual data). No dense text walls.
- 3 key messages max — I have distilled my evidence into no more than 3 memorable, actionable points.
- Personal story included — I have paired quantitative data with at least one patient story or case study to create emotional resonance.
- Counterarguments addressed — I have anticipated likely objections and briefly addressed them or presented alternative approaches.
- Data visualisation used — Complex statistics are shown as charts or infographics, not listed in paragraphs.
- Evidence is current and local — I am citing recent data and, where possible, local or regional examples relevant to my context.
- Sources are transparent — I have clearly stated sources, methodologies, and any limitations to build credibility.
Visualise data
Charts and infographics cut through for high-level audiences. Use them especially in digital materials.
Stay focused
Overloading stakeholders with data weakens your case. Fewer, stronger points win.
Humanise the data
A real patient story makes abstract statistics tangible and memorable.
Link to context
Reference current local policy developments to show your evidence is timely and relevant.
Quick feedback
How was this tool?
How likely are you to recommend this step of the Advocacy Roadmap to a colleague or fellow advocate?
Not at all likely
Extremely likely
Thanks for your feedback, it helps us improve.