Yes, for status — not for clinical interpretation. An AI voice or chat agent can verify a patient's identity, look up whether a test, scan, or order is complete, pending, or delayed, and relay that status immediately. Anything requiring interpretation of the actual clinical result still goes to a clinician; the agent reports status, never findings.

What "where's my result" calls actually consist of

In imaging, diagnostics, and other order-driven health services, status calls are one of the highest-volume, most repetitive call types, because patients have no visibility into where their order sits until someone tells them. The volume breaks down into a small set of intents:

• Whether a test, scan, or order has been completed
• Whether results have been reviewed by a provider yet
• Expected turnaround time or next steps
• Pickup, delivery, or portal-access instructions
• Whether an order needs more information before it can proceed

Which of these calls should you automate first?

Start with status lookups tied to a specific order — "has my order been completed" is a system lookup with an unambiguous answer. Then turnaround-time and next-step questions, which are close to scripted once the order status is known. Then portal and access instructions, which are static information paired to an order state. Interpretation requests — "what does this mean" — should never move into the automation queue; they should be detected and routed on contact.

What should not be automated in results and order status calls?

An AI agent should never read out or interpret clinical findings, offer a diagnosis, or speculate about what a result means. That boundary has to be enforced by design, not left to judgment in the moment. Route to a clinician or nurse line: any request for interpretation, any caller who sounds distressed about a result, and any case where the order status itself is unclear or contradictory in the source system.

How does an AI agent report status without crossing into clinical territory?

The same architecture principle applies here as anywhere else patient information is involved: the agent retrieves and reads back, it doesn't generate.

• Status comes from the source system — LIS, RIS, EHR, or order management platform — never inferred by the model.
• Identity is verified before any status is disclosed.
• The agent answers only the status question asked.
• A request for interpretation is detected and routed to a clinical line immediately, not answered.
• Every call is logged, so staff can see exactly what was and wasn't communicated.

What integrations does this require?

• The lab information system (LIS), radiology information system (RIS), or EHR that owns order and result status
• Patient portal or delivery system, for pickup and access instructions
• Telephony and contact center infrastructure, for routing interpretation requests to a clinical line
• The CRM or case management system, for logging

What results should you expect?

Southwest Medical Imaging (SMIL), a Replicant customer running 17 outpatient imaging centers, automated its highest-volume calls — appointment cancellations and confirmations — and saw its agent answer rate climb from about 73% to over 90%, abandonment drop by 20%, and 700 calls a day handled by AI, according to Replicant's published case study. SMIL's automation was scheduling rather than results delivery specifically, but a center running that call volume carries the same repetitive, non-clinical load on the status side of the phone — the workflow this use case is built for.

For your own program, track:

• Percentage of status calls resolved without a live agent
• Average hold time on the results and status line
• Rate of interpretation requests correctly routed to a clinical line
• Repeat contact rate — patients calling back because status wasn't clear the first time

What to ask a vendor before automating results and order status calls

• How does the agent distinguish a status question from a request for interpretation?
• What happens if the source system shows an unclear or contradictory status?
• Can escalation to a clinical line happen mid-call, without the patient having to call back?
• How is identity verified before any status information is shared?
• What does the audit log capture for a results-status call?

Frequently asked questions

Can AI actually access a patient's real test results? An AI agent can be connected to the systems that track order and result status, but it's typically scoped to report status — ready, pending, delayed — rather than the clinical content of a result, which stays with the care team.

What if a patient wants to know what their result means? That request should route straight to a clinician or nurse line. A well-built workflow recognizes the difference between "is it ready" and "what does it mean" and escalates the second one every time.

Is this only useful for imaging and diagnostics? No — any health services organization fielding a high volume of status calls, including labs, DME, and referral-based specialty practices, sees the same benefit, since the workflow doesn't change much between settings.

How does this reduce hold times for other callers? Because status checks are one of the most repetitive call types, automating even a portion of them frees staff to handle calls that actually require a person, which shortens hold times across the board.