RWE Synopsis · Human-reviewed
Evidence synopses, drafted in minutes and reviewed by researchers.
New synopsis
RWE Synopsis · Pharmatiya Health
What evidence question are you working on?
Describe it in a sentence — the condition, who it is for, the data you hold. I’ll structure it into a feasibility plan, a retrospective study and a pragmatic outreach design.
01Search prior work
Feasibility starts with a question most teams cannot answer quickly: has this been looked at before, in which data? Type a condition, a data type or a method.
The searchable index is being prepared. In the meantime, tell us the condition or data source you are asking about and we will confirm what prior work exists.
Note — the list is a published sample of prior work. Client identities are not included.
How it works
01 / Describe
The problem, in plain language
A business, clinical or evidence question — who it is for, which patients, what data you hold. A sentence or two is enough.
“A payer-facing synopsis for migraine patients cycling through acute therapies, using claims and EHR data.”
02 / Structure
Laid into the framework
Feasibility first: cohort logic and code families. Then the retrospective study: objectives, endpoints, cost, and the statistical plan. Then pragmatic outreach: workflow, funnel, and dashboards.
03 / Review
Checked by a researcher
The draft is copied or downloaded, then reviewed — code lists, windows, and sample sizes confirmed against the data — before anything reaches a client.
The framework
- 01
Feasibility
Can this question be answered with the data available?
- 02
Retrospective
What does existing data already show?
- 03
Pragmatic outreach
Who should be approached, and how?
Human reviewRequired at every stage, before any output leaves the system. Not optional, and not post-hoc.
02Where AI is used — and where it is not
The model does
- Structures a plain-language problem into a synopsis
- Drafts cohort logic and claims / EHR code families
- Proposes objectives, endpoints, cost, and statistical plans
- Outlines the outreach workflow and dashboards
A researcher does
- Approves the study question
- Validates every method choice
- Confirms code lists and sample sizes against the data
- Signs off all output before it leaves
- Retains professional responsibility
The right-hand column is longer than the left, and that is the point.
03Trust
01
No patient data
The builder needs the question, not the patient. A statement that contains an identifier is refused before anything is drafted.
02
Human review, every time
No synopsis reaches a client without expert sign-off. Review is a stage in the workflow, not a check at the end.
03
Where your question goes
Your problem statement is sent to Pharmatiya's own drafting service, which uses a language model to produce the synopsis. Nothing is published.
04
What it does not do
It does not decide whether a study is feasible, fix final code lists or sample sizes, or write the protocol. It drafts the structure; a researcher decides.
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Thirty minutes with the team that built it — including what it does not do.
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