How a Device Maker Quantified Why 73% of Calls Never Led to a Scheduled Appointment

An enterprise device manufacturer knew its appointment scheduling rate was low, but it couldn't say why. Its device is an implantable therapy that requires a provider assessment before a patient is confirmed eligible — a necessary gatekeeping step, and evidently a point where a lot of patients were falling out of the process.

Of course the dashboards reported on the scheduling rate, but they didn't show what was happening on the calls behind it. Without that, the team was making decisions about patient services, staffing, and outreach off a symptom, with no real read on the cause.

The A-Ha Moment

A low scheduling rate can come from a lot of places: a broken process, a patient population that isn't motivated, a mismatch between what marketing promises and who actually qualifies. The team couldn't do much with the number itself. Fixing it meant explaining it first, and the reality was that there was no explanation — just a guess dressed up as a plan.

Getting more patients scheduled was still the goal, but that top-line number wasn't something anyone could act on directly. What the team needed was narrower: what's happening on the calls that don't end in an appointment, and which of those reasons they could actually change.

The Intervention

Authenticx built custom classifiers to isolate the calls that ended without a scheduled appointment, then used targeted listening to quantify what was driving that outcome. Of the calls that didn't end in an appointment, four reasons carried most of the weight:

• No clinic reached or scheduled — 32%

• Insurance coverage concerns — 20%

• Referral requirements — 18%

• Did not meet FDA indications — 9%

Together, those four reasons account for 79% of the calls that fell out; the remaining share was spread across smaller, less concentrated reasons. Still, one large, undifferentiated number became four specific, sized problems — some operational, some clinical, and one worth acting on immediately.

The Impact

• 73% of all calls ended with no scheduled appointment

• Of those calls, 32% never reached or scheduled with a clinic, 20% had an insurance coverage concern, 18% ran into referral requirements, and 9% didn't meet FDA indications

• The other 21% of those calls were spread across smaller reasons

• Clinic access and insurance concern, 52% of the drop-off, were identified as directly fixable

The insurance concern finding gave the organization a clear, data-backed business case: verify coverage on the call itself, rather than lose the patient to uncertainty after they hang up.

The New Normal

The appointment scheduling rate isn't a single, opaque number anymore. The organization has a ranked, quantified breakdown of what's driving patients away before they're ever assessed, with the fixable operational gaps separated from the clinical eligibility limits that were never going to convert.

That changes what gets built next. Rather than a broad campaign aimed at "improving scheduling," the team is prioritizing in-call insurance verification and clinic-access support: the two drivers they can actually control. Referral requirements and FDA indication mismatches are a separate conversation, for later.

Why It Matters for Medical Device Leaders

Most device companies with a patient program run some version of this funnel. A patient calls about starting a therapy, or about a device they already have, and somewhere between that call and the outcome the company is tracking, people drop out. That might be a consult for an implant, the first week on a pump or a CPAP, a resupply order for ostomy or CGM supplies, or a coverage question that ends in a cancellation.

The dashboard has the rate. The only place the reasons get said out loud is on the calls.

What this team did works for any of those outcomes. Isolate the conversations that ended the wrong way, then quantify what patients said got in the way. Part of that gap is clinical or regulatory, and it stays where it is. The rest is operational — and a good share of it can be fixed next quarter. Knowing which is which turns a number into a plan, and it gives the people who run these programs a business case built from their own patients' words.

Authenticx does this at scale for device patient services and support teams, on the calls they already have. Learn how you can use the actual voices of your patients to find out what's behind the numbers you're seeing on your dashboards.