# AI for Medical Malpractice

> How a hospital risk manager, patient safety officer or claims lead can use AI on medical malpractice exposure, from the incident report to the reserve: incident review, early case assessment, claim file review, reserving support and privilege, with a workflow diagram, an interactive early-case-assessment checklist, a dated tool table and synthetic worked examples. Published by Medrecords AI (https://medrecords.ai/), which makes 1 of the products covered.

- [AI for medical malpractice: a guide for hospital risk and claims teams](https://aiformedicalmalpractice.com/): AI for medical malpractice on the hospital side: incident review, early case assessment, claim file review and reserving, with a workflow and checklist.
- [AI for incident review: from the event report to the chart timeline](https://aiformedicalmalpractice.com/incident-review/): How hospital risk and patient safety teams use AI in incident review: triage, the chart timeline, late entries and gaps, with a synthetic worked example.
- [Early case assessment for malpractice claims: an interactive checklist](https://aiformedicalmalpractice.com/early-case-assessment/): A 28-item early case assessment checklist for hospital malpractice claims, marking which items AI can speed up and which stay human. Runs in your browser.
- [AI for malpractice claim file review on the hospital side](https://aiformedicalmalpractice.com/claim-file-review/): How hospital claims teams use AI on a malpractice claim file: merged chronology, duplicates, testimony vs chart, counsel reports, with a synthetic file costed.
- [AI and malpractice case reserves: support, not the number](https://aiformedicalmalpractice.com/reserving/): How AI can support case reserving on hospital malpractice claims: the inputs it can gather, the triggers it can watch, and why the number stays human.
- [Privilege and governance: using AI without losing protection](https://aiformedicalmalpractice.com/privilege-and-governance/): Where AI output sits under patient safety work product, peer review privilege and work product, the questions for counsel, and an AI policy template.
- [AI tools for hospital malpractice risk and claims, compared](https://aiformedicalmalpractice.com/tools/): 16 tools hospital risk and claims teams can use on malpractice work, by job: incident systems, adverse event detection, benchmarks, claim file AI, legal AI.
- [Medrecords AI for hospital risk and claims teams: our product, described plainly](https://aiformedicalmalpractice.com/medrecords-ai/): Our own product, described plainly for hospital risk and claims teams: what Medrecords AI does on a malpractice file, what it costs, and what it doesn't do.
- [Glossary of hospital risk, claims and AI terms](https://aiformedicalmalpractice.com/glossary/): Plain definitions of the risk management, claims and AI terms used on this site, from early case assessment and case reserves to PSWP, late entries and BAAs.
- [Frequently asked questions about AI in hospital malpractice work](https://aiformedicalmalpractice.com/faq/): Short answers on AI in hospital malpractice work: what it can read, what it can't decide, privilege, BAAs, reserves, costs and how to test a tool first.
- [Methodology and conflict of interest](https://aiformedicalmalpractice.com/methodology/): Where the facts on this site come from, how we read search results, vendor pages and studies, and the rules we follow because Medrecords AI publishes it.
- [About this site](https://aiformedicalmalpractice.com/about/): AI for Medical Malpractice is a guide for hospital risk and claims teams, published by Medrecords AI. Who owns it, who writes it, and how to send a correction.
- [Privacy](https://aiformedicalmalpractice.com/privacy/): This site has no forms that send data, no accounts, no ads and no tracking cookies. The checklist runs only in your browser. Hosting logs and contact details.
- [Site map](https://aiformedicalmalpractice.com/site-map/): Every page of aiformedicalmalpractice.com on 1 screen, grouped by what you came to do, with word counts and the date each page was last updated.