# Patient History & Recovery-Factor Software (Beta) > Patient history and recovery-factor extraction software, in beta: social, family, occupational, allergy, and prior-accident history in 1 cited profile. Canonical page: https://medrecords.ai/product/patient-history-recovery-factors/ --- NewWe now read the actual MRI and CT imaging — not just the radiologist's 1-page report. [See how →](https://medrecords.ai/product/imaging/) [Home](https://medrecords.ai/) ›[Product](https://medrecords.ai/product/) › — Structured Patient History & Recovery-Factor Extraction STRUCTURED PATIENT HISTORY & RECOVERY-FACTOR EXTRACTION ## The history that affects recovery, structured and cited. BETA Structured patient history and recovery-factor extraction software from Medrecords AI extracts social, family, occupational, allergy, prior-accident, prior-surgery, and pre-existing-condition history into one evidence-linked profile, keeping patient-reported statements clearly separate from clinician-confirmed findings, extraction only. Live in beta and testable today. [Join the beta ](https://medrecords.ai/demo/?src=beta-patient-history-recovery-factors) [Book a demo](https://medrecords.ai/demo/) Adams, Timothy — right knee · Case #IME-4812 BETA History profile — 7 categories Prior surgery — right knee, 2020 clinician-confirmed Occupational — warehouse lifting patient-reported Allergy — NKDA clinician-confirmed 7 history categories · **extraction only** , every line cited. IN ACTIVE BETA Refined hands-on with early customers, extracting **the history that shapes recovery** , cited throughout. ### One profile, 7 history categories, all cited. Social, family, occupational, allergy, prior-accident, prior-surgery, and pre-existing-condition history are pulled from across the file and assembled into a single structured profile — the kind of background that shapes a recovery timeline, gathered once instead of hunted for chart by chart. 7 categories, each traced to its exact source Assembled once from the whole file, not per document Categories tracked · Social & family history · Occupational history · Allergies · Prior accidents & prior surgeries · Pre-existing conditions Source tagging SELF-REPORT "I used to smoke, quit 5 years ago" CONFIRMED Prior right-knee surgery, per operative report ### Patient-reported stays separate from clinician-confirmed. What a patient says about their own history and what a clinician has independently confirmed are 2 different kinds of evidence, and the profile never blurs them. Each entry is tagged to its source type, so a reviewer can see at a glance which parts of the history are self-report and which are backed by a clinical finding. Every entry tagged patient-reported or clinician-confirmed No history is inferred beyond what's actually written Profile state EXTRACTION ONLY What the profile provides · What's written, tagged by category and source · Patient-reported vs. clinician-confirmed, always split What it never does · Render a medical or psychological judgment · Infer sensitive history beyond what's written The boundary ### Extraction, not judgment — and no history invented. The profile only ever pulls forward what the record actually states. It never makes a medical or psychological judgment about what a patient's history means, and it never infers sensitive history — mental health, substance use, or similar categories — that isn't directly supported by the text. If the record is silent, the profile stays silent too. Patient-reported statements and clinician-confirmed findings are kept in clearly separate lanes throughout, so a reviewer always knows whether a fact in the profile came from what the patient said or from what a clinician independently established. Audit-grade, source-linked, and no more than what's on the page. ### From scattered history to one cited profile. 3 steps, with nothing inferred beyond the page. 01 Each category scanned across the file Social, family, occupational, allergy, prior-accident, prior-surgery, and pre-existing-condition mentions are located. 02 Statements tagged by source type Every entry is marked patient-reported or clinician-confirmed, with its citation attached. 03 Profile assembled, extraction only The 7 categories come together into one structured profile — no added judgment. ### Who reads the history profile. The same structured background, useful wherever recovery-factor context matters. [ Law firms Get the recovery-factor context needed for causation and apportionment, cited. For law firms ](https://medrecords.ai/solutions/law-firms/) [ Medical evaluators Walk in with prior-accident and prior-surgery history already structured, not buried. For evaluators ](https://medrecords.ai/solutions/medical-evaluators/) [ Insurance carriers See pre-existing conditions and prior history clearly separated from the current claim. For carriers ](https://medrecords.ai/solutions/insurance-carriers/) FAQ ### Patient history & recovery factors, answered. Social, family, occupational, allergy, prior-accident, prior-surgery, and pre-existing-condition history — the categories that typically shape a recovery timeline — pulled from across the file into one profile. No. This is extraction only: it never infers unsupported sensitive history, and it never renders a medical or psychological judgment about what a patient's history means. If the record doesn't say it, the profile doesn't say it either. Every entry in the profile is tagged to its source type. A patient's own statement about their history is tagged patient-reported; a finding a clinician independently established is tagged clinician-confirmed. The 2 are never merged into a single undifferentiated fact. Yes, in beta. Structured patient history & recovery-factor extraction is live and testable now; we're refining it hands-on with early customers, and if your use case is a good fit we'll work with you directly. Yes — every entry in the profile is cited back to its exact source page, the same citation model used across the rest of the platform. ### Related capabilities. What sits alongside the history profile, live today or in this same beta batch. [ Causation & Apportionment Graph Maps how prior and current conditions relate to the covered incident, cited throughout. Explore ](https://medrecords.ai/product/causation-apportionment-graph/) [ Injury Causation Analysis Tags every visit and charge related, unrelated, or disputed to the covered incident. Explore ](https://medrecords.ai/product/treatment-relatedness-compensability/) [ Negative Findings & Documentation-Gap Flagging Surfaces what the record doesn't document — kept distinct from what it denies. Explore ](https://medrecords.ai/product/negative-findings-detection/) [ Work Capacity & Functional Restriction Tracking A dated trajectory of work status and functional limitations, cited throughout. Explore ](https://medrecords.ai/product/work-capacity-functional-restriction-tracking/) ### See the history behind the recovery. Extract social, family, occupational, allergy, prior-accident, prior-surgery, and pre-existing-condition history into one evidence-linked profile — extraction only, never judgment. Join the beta on one of your own files, or book a demo first. [Join the beta ](https://medrecords.ai/demo/?src=beta-patient-history-recovery-factors) [Book a demo](https://medrecords.ai/demo/) [All capabilities →](https://medrecords.ai/product/)