Evidence before persuasion
Make the basis for a judgment visible. Do not manufacture belief.
About
Strong evidence still fails to change decisions.
People’s Evidence Lab is a small research and consulting group focused on how evidence becomes understandable, traceable and usable by the people who need to act on it.
Founder & Principal
Steve Watt
Physician. Evidence leader. Founder of People’s Evidence Lab.
Steve spent more than 25 years in pharmaceutical evidence generation and regulatory science at Pfizer, most recently leading Patient-Centered Research and Partnerships within Medical Evidence Generation.
His work spanned benefit–risk assessment, patient preference research, real-world evidence and patient-centered drug development.
He founded People’s Evidence Lab to address a recurring problem: rigorous evidence that does not reach the people who need to use it.
View Steve’s professional profilePfizer is a former employer. No client relationship or endorsement is implied.
Selected publications
Evidence design: patient preferences in medical product decisions
Multimethod quantitative benefit–risk assessment of treatments for moderate-to-severe osteoarthritis. British Journal of Clinical Pharmacology, 2022.
https://doi.org/10.1111/bcp.15309An overview of critical decision-points in the medical product lifecycle: where to include patient preference information in the decision-making process? Health Policy, 2020.
https://doi.org/10.1016/j.healthpol.2020.07.007What next for the science of patient preference? Interoperability, standardization, and transferability. The Patient, 2025.
https://doi.org/10.1007/s40271-025-00727-9Do we understand unmet need? A proposal to use length-of-life equivalent (LOLE) as a patient-centric measure of unmet need. PharmacoEconomics – Open, 2025.
https://doi.org/10.1007/s41669-025-00560-8Beyond the binary: integrating “real-world evidence” with randomized trials in contemporary health care. Journal of Clinical Epidemiology, 2025.
https://doi.org/10.1016/j.jclinepi.2025.111821Priority outcomes in sickle cell disease treatment: co-creation and implementation of a preference exercise with patients and caregivers to inform drug development. Journal of Patient Experience, 2023.
https://doi.org/10.1177/23743735231213767
Evidence communication: patients and healthcare providers
Empowering patients through pharmacovigilance, transparency, and health literacy: a narrative review. Current Medical Research and Opinion, 2025.
https://doi.org/10.1080/03007995.2025.2534468Developing, optimizing, and evaluating patient infographics for diagnosing cardiac amyloidosis. PEC Innovation, 2023.
https://doi.org/10.1016/j.pecinn.2023.100212Healthcare practitioner preferences for infographics: comparing workflows with and without generative AI assistance. Journal of the American Medical Informatics Association. Accepted, 2026.
AI and evidence methods
Using sentiment analysis to quantify the relative desirability and acceptability of drug-product attributes. JAMIA Open, 2026.
https://doi.org/10.1093/jamiaopen/ooag075AI for oncology drug data harmonization — Amazon versus OpenAI. NEJM AI, 2024.
https://doi.org/10.1056/AIcs2400661Practical aspects of using large language models to screen abstracts for cardiovascular drug development: cross-sectional study. JMIR Medical Informatics, 2024.
https://doi.org/10.2196/64143
Our mission
Help evidence earn trust where action is required.
Our vision
A world where evidence is useful in the context it is used.
What we stand for
Trust proportionate to the evidence.
We call this warranted trust: confidence based on what the evidence can actually show, with a basis that readers can inspect.
Context matters
Examine the setting in which the evidence needs to work.
Clarity is a safety feature
People need to understand what an output does and does not show.
Equity in use
Ask who benefits, who does not and whose experience is missing.
Traceability by default
Keep sources, methods and limitations connected to the output.
Work people can use
Produce outputs that help a team act and can be examined without us in the room.
How we collaborate
Alongside your team.
We define the decision and the work up front, handle sensitive material carefully and aim for reusable learning without exposing client specifics.
We work alongside medical, clinical, data, regulatory and product leads, using EvLander™, our approach to assessing how evidence is received, described in In the Open. Decisions remain with your team. An NDA is available when appropriate.
PEL does not run clinical trials, write or file regulatory submissions, provide legal, medical or regulatory advice, or promise a higher probability of approval or reimbursement.
Interested in working together?
We welcome enquiries about evidence and content, research collaboration, speaking and co-authorship.