Part 10: AI in your industry, and on the floor

Where does AI help a dental or medical office?

Written lesson · about 3 minutes to read

The short answer

AI helps a dental or medical office on the office side: booking and reminders at the front desk, claims checked before they go, and letters and forms drafted for a person to sign. Settle patient privacy first, because it decides which tools may be used, and leave every clinical decision with the clinician.

Three things to remember

01Settle privacy first: a vendor handling patient information must sign a business associate agreement.
02The front desk can hand off booking, reminders and forms, but not upset or urgent patients.
03Diagnosis and treatment stay with the clinician, and a coder still signs the code.

Privacy comes first

Patient information is governed by rules that decide which tools may touch it, where it may be stored and who may see it. In the US the main one is HIPAA, and it is the first conversation, before any feature. A vendor whose tool handles patient information has to sign a business associate agreement and say where the data is stored, who can see it and how long it is kept. A vendor who cannot is not a vendor for a practice.

Then look inward. Many practices have a consumer app on a staff member's phone that has been summarising referral letters, or a free transcription tool, used with good intentions and no agreement. Close them and give people an approved tool that does the same job, or they will go back. Rules differ by state, so check your own position with a lawyer.

The front desk

The receptionist has the same few conversations all day. Under the right agreement and settings, a tool can read appointment requests from the phone and portal, find the slot against the schedule and appointment type, and send the confirmation. The patient who calls at six in the evening gets an appointment instead of a voicemail.

Reminders go out two days ahead with a yes or a reschedule, and intake forms are sent before the visit and returned filled, so the clipboard disappears. Eligibility can be checked before the visit rather than after. The no-show rate is the number to write down before you start.

Billing and documents

Claims can be read against the reasons that usually get them rejected: a missing field, a mismatched code, an authorisation that was not attached. They are flagged before submission, and a rejection that comes back is summarised with the fix. Referral letters, prior authorisations (the insurer's approval sought before treatment) and plain-word summaries for patients are drafted for a person to review.

A person reviews every claim before it goes, and the coder signs the code. The tool can suggest and check, but the coder decides, because the coder is accountable and the tool is not.

Never the clinical decision

Diagnosis, treatment and anything a clinician is licensed to decide stay with the clinician. On the office side, a wrong draft is caught by a person and costs a minute. On the clinical side, the same mistake costs far more, and a tool sounds certain either way.

Watch for the front desk tool that also offers, in the demo, to answer a patient's question about their symptoms. Write down what the tool may touch: scheduling, reminders, intake, billing and documents. Write down what it may not: the chart, the clinical note and any question about a patient's condition. Build those into its hand-off rules.

Where to start this week

Decide who in the practice owns the privacy question, and list every tool that already sees patient information, including the ones nobody approved. Ask each vendor for the agreement and its storage and retention answers in writing, and read them.

Then pick one small, reversible workflow. Reminders come first, since the no-show rate moves most and the risk is low. Let booking follow after a month of watching, and check a sample of conversations each month.

Next lessonWhere does AI help a finance or insurance business?

More in part 10

Next step

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