Since my last visit
Symptoms, changes, concerns, treatment burden, workarounds, interruptions, questions, and what the care team should understand.
For patients and caregivers
Your health story, ready for the next doctor visit.
Start with what happened in your own words. PatientStories.ai helps organize the story into a Health Biography you control, including a concise Doctor Visit Report for care conversations.
Open story first.
Useful output back.
Research only with consent.
PatientStories.ai captures health in the wild — the lived reality of illness and treatment before healthcare has a field for it. Structured data tells us what healthcare already knows to measure. The wild reveals what people are actually living through.
Doctor visit lens
The first value back is practical.
The Doctor Visit Report turns recent lived experience into a concise summary a person can review, edit, print, download, or share before an appointment.
My words, organized
The story starts as text or voice. The structured version remains available for review, editing, deletion, or sharing by the person who created it.
Questions not forgotten
The report preserves the questions, concerns, and lived context that are easiest to lose during a short clinical visit.
Health Biography
One story can become many personal outputs.
Health Biography is the participant-facing offer. Research insight is an opt-in use case, not the reason someone has to start.
Doctor Visit Report
A concise, appointment-ready version of recent lived experience.
Longitudinal Health Biography
A living account of diagnosis, treatment decisions, turning points, setbacks, adaptations, and care gaps.
Caregiver or Family Version
A plain-language version for family, caregivers, school, work, or support partners.
Personal Archive
A record for posterity: what the person endured, learned, managed, lost, gained, and wants remembered.
Community Reflection
An anonymized mirror showing common patterns and “people like me” signals without exposing individual stories.
Research Submission Version
A participant-reviewed version that may be contributed to listening projects or research insight only with consent.
How it works
Speak first. Structure second. Approve before it goes anywhere.
PatientStories.ai is built for least-friction narrative intake. A person can start with a recent moment, a memory, a question, a treatment burden, a symptom pattern, or a story they want preserved.
The platform distinguishes raw story, user-reviewed structure, personal outputs, community learning, and governed research outputs.
Open narrative intake
Text or voice, without forcing the story into a survey first.
AI-assisted organization
Important facts, context, timeline, concerns, and questions are extracted into a reviewable structure.
User control
The person can review, edit, shorten, expand, delete, download, print, or share the output.
Optional contribution
Only approved, de-identified signals can contribute to community learning or research insight.
Health in the wild
The story often knows where the signal is before the form does.
Symptoms, burdens, workarounds, tradeoffs, social friction, and treatment realities often appear in lived narrative before they appear as formal fields.
Before the survey
Patients describe signals before anyone has turned those signals into a checkbox, endpoint, or database field.
Before the visit
The most useful context may emerge between visits, close to the moment people are managing burden, uncertainty, and adaptation.
Before the report
Open stories can reveal patterns that later become better prompts, questions, support, and structured fields.
30-day listening projects
Tell us what happened. We’ll tell you what the community taught us.
A listening project is a time-bounded community learning cycle. Participants share recent lived experience, get personal outputs back, and later receive an anonymized community report.
Day 1
Share one recent moment
Start with one real health moment from the last 7 days, not a full life history.
During the project
Create a useful output
Generate a Doctor Visit Report, Health Biography section, or research submission version under the participant’s control.
After 30 days
Report back
Return the patterns, failure points, workarounds, questions, and community signals in aggregate form.
Trust model
Personal value first. Research use by permission.
PatientStories.ai is built around a simple boundary: people create useful Health Biography outputs for themselves and may choose to help their community reveal patterns, gaps, burdens, unmet needs, and better questions.
Participant value firstHealth Biography outputs give people something useful back from their own stories.
No raw patient data salesThe commercial product is governed, anonymized, aggregated insight — not individual stories or participant-level datasets.
Review before contributionResearch submission versions are participant-reviewed and consent-driven.
Contact
For patient communities and early listening projects.
Use this path for Health Biography, Doctor Visit Reports, patient community partnerships, or 30-day listening projects. Research-client and sponsor conversations have a separate page.