Part of The AI Communications Hub · companion to ChatGPT for Public Relations
Edited on Sep 15, 2026.
Healthcare communications teams use AI tools the same way any comms team does, drafting, research, and reporting, but with one added constraint that changes every workflow: nothing that could identify a patient or make an unverified clinical claim can go into a consumer AI tool. This guide covers where AI tools genuinely help a healthcare PR or comms team, and the specific rules that make healthcare use different from a general agency workflow.
Two constraints apply to healthcare work that do not apply to most other PR verticals. The first is HIPAA and patient privacy: any material that could identify a patient, even indirectly through a combination of details, cannot go into a consumer-tier AI tool. The second is clinical accuracy: a claim about a treatment, a drug, or a health outcome carries regulatory and liability weight that a marketing claim does not, and an AI tool's fluent, confident writing style makes an unverified clinical claim look just as credible as a verified one. Both constraints mean healthcare comms teams need a stricter review step than a general consumer or B2B account.
Four tasks come up repeatedly for healthcare communications work.
Drafting Patient-Facing Education Content, From an Approved Outline
An AI tool can turn a clinician-approved outline into readable patient education copy quickly. The clinical facts still need to come from and be verified by a qualified source; the tool's job is readability and structure, not the medical content itself.
Summarizing Clinical Trial Results for a Lay Audience
A dense trial results document can be turned into a plain-language summary a reporter or patient could understand, provided every specific number and claim is checked against the source document afterward.
Monitoring Coverage of a Health System, Drug, or Medical Device
Perplexity's sourced citations make it well suited to tracking what outlets are saying about a health system or product, since every claim in the monitoring output traces back to a specific source that can be checked.
Drafting Crisis Statements for Adverse Events or Recalls
The same crisis-statement discipline that applies to any industry applies here, with an added layer: legal and clinical review before anything ships, not after.
Patient-identifiable information is the hardest line. This includes not just a patient's name, but any combination of details, a specific diagnosis plus a specific location plus a specific date, that could identify a real person even without a name attached. Unannounced clinical trial results, adverse event details before a formal report is filed, and any material covered by a business associate agreement with a covered entity carry the same restriction. When in doubt, the safer assumption is that the material does not go into a consumer-tier tool at all.
| Tool | Recommended tier for healthcare work | Why |
|---|
| ChatGPT | Enterprise | Stronger data-handling terms and admin controls suited to a compliance-heavy environment |
| Claude | Enterprise | Long-context review of dense clinical or regulatory documents, with the confidentiality terms an Enterprise account carries |
| Perplexity | Enterprise | SOC 2 controls for monitoring work that may touch non-public product or trial information |
| Gemini | Enterprise, bundled with Workspace | Matches the data-handling terms already in place for a health system's existing Google Workspace contract |
A general consumer Pro tier is not a safe default for a healthcare communications team working with any patient-adjacent or clinical material, even occasionally. The cost difference between Pro and Enterprise is small relative to the risk of a compliance incident.
What Should a Healthcare AI Policy Add to the General Template?
Beyond the standard confidentiality rules any PR team should follow, a healthcare-specific policy needs two additions: a named clinical reviewer who signs off on any AI-drafted content containing a health claim before it goes external, and an explicit statement that patient-identifiable information, defined broadly to include any combination of details that could identify a real person, never goes into any AI tool regardless of tier. See the AI Data Handling Policy Template for the general structure to build this on top of.
What Are the Best AI Prompts for Healthcare Communications?
Two examples show the pattern: give the tool the verified facts and ask for structure and readability, not the facts themselves.
Patient education draft from an approved outline.
"Turn this clinician-approved outline into a patient-facing explainer at an eighth-grade reading level. Outline: [paste]. Constraints: no claims beyond what is in the outline, flag any place you had to simplify a nuance that a clinician should review."
Plain-language summary of a trial result.
"Summarize this clinical trial result for a general news audience in 150 words. Source document: [paste, already cleared for external use]. Constraints: state the specific numbers exactly as written in the source, flag any claim that needs a citation."
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