Generative AI in Healthcare: Workflows and Review Rules
Use generative AI for carefully bounded drafting and summarization. Start with nonclinical material, keep patient information out of unapproved systems and make review explicit.
Updated 5 min read
Generative AI in healthcare can help draft and summarize information, but every workflow needs approved inputs, a defined purpose and a reviewer who can verify the result. A practical starting point is nonclinical work using public or fictional material, such as staff training outlines and administrative procedure drafts.
Treat clinical use and patient information as separate approval questions. A general writing assistant is not automatically suitable for either. fenbs can preserve approved nonclinical prompts and project rules without patient information, so the next assistant and reviewer can see the boundaries of the work.
Which workflows make a sensible starting point?
Choose a job whose input and acceptance criteria are easy to inspect. For example, an operations team might turn a public parking policy into a staff FAQ. The assistant drafts wording; the owner of the policy checks the draft against the actual policy before anyone distributes it.
| Workflow | Permitted example input | Required review |
|---|---|---|
| Staff training outline | Public visitor procedures and a fictional orientation scenario. | Confirm the procedure owner agrees with every instruction. |
| Administrative summary | An approved facilities policy without patient or employee personal information. | Check exceptions, responsibilities and deadlines in the source. |
| Project communication | A nonclinical project brief and accepted task updates. | Verify promises, status and the intended recipients. |
| Research preparation | Publicly available source material. | Open each original source and verify the summarized claim. |
These are example starting points, not a blanket permission to use an app. Your organization still needs to approve the tool and the specific data involved. Even an administrative document can contain information that should remain in an approved internal system.
What information must stay out of the trial?
Keep patient information out of the nonclinical trial described here. Do not paste clinical notes, transcripts, appointment lists, screenshots or patient-related examples into fenbs or an unapproved assistant. A prompt template should use clearly fictional placeholders rather than a lightly edited real encounter.
For organizations subject to HIPAA, HHS cloud computing guidance (opens in a new tab) explains obligations when a cloud provider handles electronic protected health information, including business associate arrangements. Whether a service and workflow meet the applicable requirements needs organizational review. A browser setting or a vendor’s general privacy statement is not that review.
Removing a name is not a reliable shortcut. HHS de-identification guidance (opens in a new tab) describes Expert Determination and Safe Harbor as the two methods for meeting the HIPAA de-identification standard. Do not ask an assistant to improvise a de-identification process and assume the result is safe to upload.
Write the permitted data boundary in plain language. In this trial it can be simple: public documents and fictional examples only, with no patient information in prompts, tasks, comments or saved progress. Store the approved instruction with the project so it survives a change of assistant.
How do you verify a generated summary?
Compare the result with the complete source. A summary may preserve the main point while dropping an exception, turning an optional action into a requirement or blending two different procedures. Ask for source locations, but inspect those locations yourself.
- Identify the authoritative document and confirm that it is the version intended for this task.
- Ask for a draft that distinguishes source statements from suggested wording and flags missing information.
- Check each instruction, qualification, responsibility and deadline against the source.
- Have the designated owner approve the result before it becomes training or operational material.
Do not use a generated confidence score as evidence. The NIST generative AI profile (opens in a new tab) identifies confidently presented false content as a risk. A useful review process checks whether the output is supported, not whether the assistant sounds certain.
Our guide to human review of generative AI explains how to give a reviewer a specific acceptance job. For a parking policy FAQ, that job includes checking exceptions for accessible parking and after-hours visits rather than approving a draft because it reads smoothly.
Where does drafting stop and clinical decision support begin?
A workflow changes materially when its output is intended to influence diagnosis, treatment or another patient-specific clinical decision. Do not extend a successful administrative writing trial into that use without a separate clinical, privacy, security and regulatory assessment. The intended function matters more than the fact that both activities produce text.
The FDA clinical decision support guidance (opens in a new tab) explains that some software functions fall outside the device definition and others remain subject to device policies. Do not assume that calling software an assistant, or putting a person after its output, determines its regulatory status.
Set a stopping rule for the administrative workflow. If the request needs patient-specific information, medical recommendations or an interpretation beyond the reviewer’s authority, pause the task and route it through the appropriate organizational process. A reusable prompt should state that boundary as clearly as it states the desired format.
What belongs in a reusable nonclinical prompt?
Include the purpose, audience, permitted inputs, output structure, prohibited additions and reviewer. For example: draft an orientation FAQ from the supplied public visitor policy; use only that policy; flag missing details; do not add medical advice; leave approval to the policy owner. Keep fictional examples visibly fictional.
Save the review checklist beside the prompt. A reusable instruction that only describes the desired prose leaves the important part to memory. An approval workflow also needs to distinguish a draft that exists from material that a person has accepted.
Preserve the prompt and its review boundary
Save approved nonclinical instructions in fenbs Skills and prompts, using no patient information. Record the organization’s agreed project boundaries in Decisions and rules. Connected assistants can read the instructions while people retain responsibility for decisions and sign-off.
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How to do this with fenbs
- Create a free account and add a project for a nonclinical trial that uses only approved public or fictional material.
- Save the prompt, its input restrictions and its review checklist in Skills and prompts. Keep patient records and patient-related details out of the project.
- Record a person’s approved boundaries in Decisions and rules, then add a task describing the draft and its acceptance criteria.
- Ask a connected assistant to read the context before working and save progress afterward. Record review status and the next step without copying sensitive source content.
fenbs is not the right fit for a patient record or a clinical decision system. Use it here only for nonclinical project coordination and approved instructions without patient information. Its work context features help preserve the rules around the trial.
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