Why referrals stall before the prescription

Ask a commercial leader at a medical device company where referrals are lost, and the first answer is usually the patient: they changed their mind, or nobody could reach them. Look at the records and a different picture appears. Most referrals that never become prescriptions were never refused. They waited at a handoff that nobody owned, until they expired.

This note follows a referral from the moment it arrives to the signed prescription. It shows where referrals typically wait, who could move them, and what follow-through looks like at each step.

About field notes. Field notes describe how a process typically runs and where it typically breaks. The figures are sample data, not any company's results.

Out of 1,000 referrals

1. ReferredReferring practice1,000
2. Patient contactedPatient access812−188 (19%)
3. Benefits verifiedBenefits team604−208 (26%)
4. EvaluatedClinic471−133 (22%)
5. PrescribedPrescriber380−91 (19%)

The path, and who owns each step

Five steps, four teams and at least five systems. The referring practice sends the referral by fax, e-referral or the EHR. Patient access has to reach the patient. A benefits team checks coverage and, often, prior authorization in payer portals. The clinic evaluates the patient. A prescriber signs the order.

Each team measures its own step, and usually measures it well. Nobody measures the path. So the question that matters, how many referrals became prescriptions this week and where the rest are, has no owner and no answer.

Four places a referral goes quiet

1. First contact

   The referral arrives by fax or e-referral and lands in a shared inbox. Patient access calls once, leaves a message, and the referral slides down a list sorted by date received.

   Owner

   Patient access

   Signal it has stalled

   No successful contact within two working days

   Follow-through

   Text first, then call at a time the patient chose. After three attempts, go back to the referring practice.

2. Benefits and prior authorization

   The biggest leak in most samples. Prior authorization needs clinical notes the benefits team does not have. The request waits on the referring practice, the practice assumes the device company is handling it, and the payer's clock runs out.

   Owner

   Benefits team

   Signal it has stalled

   Prior authorization not submitted within three working days of contact

   Follow-through

   Ask for the missing notes the same day, through the channel the practice actually uses, with a named owner and a due date.

3. Evaluation

   Coverage is confirmed but the evaluation is not booked, or booked and missed. Notes from the visit sit unsigned, so the next step cannot start.

   Owner

   Clinic

   Signal it has stalled

   No visit booked within five days of verification

   Follow-through

   Offer a slot while the patient is still on the phone, and confirm it the day before.

4. Signature

   The order is complete and waits in the prescriber's queue behind everything else. It is the cheapest loss to fix and the most frustrating one.

   Owner

   Prescriber

   Signal it has stalled

   Order unsigned after two working days

   Follow-through

   Send the order for signature with everything the prescriber needs on one screen.

One referral, 23 days

1. Day 0Received
2. Days 1–3Waiting: in the shared inbox
3. Day 4Contacted
4. Days 5–13Waiting: for clinical notes
5. Day 14Verified
6. Days 15–19Waiting: for a visit slot
7. Day 20Evaluated
8. Days 21–23Waiting: for a signature
9. Day 23Prescribed

23 daysfrom referral to prescription

20 dayswaiting for someone

Most of the time is waiting, not work

Put one referral's days on a line and the problem is plain. In the sample above, people worked on the referral for three days out of twenty-three. The other twenty it waited: in an inbox, for notes, for a slot, for a signature. Every wait had someone who could have moved it. None of them knew it was theirs.

This is why adding staff to one team rarely moves the conversion rate. The waits sit between teams, so they belong to none of them.

Most lost referrals were never declined. They waited at a handoff nobody owned.

What follow-through looks like

Follow-through is not more reminders. It is four rules, applied to every referral, every day.

The number to watch

Track one number each week, from source systems: the eligible referral-to-Rx rate. Alongside it, track how many referrals are past their clock at each step. The first tells you whether things are getting better. The second tells you where to look this week.

Outcome definitionEligible referral-to-Rx rate

Counts

Prescriptions signed for referred patients

Out of

Eligible referrals received in the same cohort week

Excludes

Duplicate referrals; patients outside coverage

Owner

VP Patient Access or Commercial Operations

Five questions to ask this week

• How many open referrals have had no successful patient contact in two working days?
• Which step loses the most referrals, and who owns it?
• How many prior authorizations are waiting on clinical notes, and who is chasing them?
• How many orders are waiting for a signature right now?
• Could you report last week's referral-to-Rx rate from source systems today?

If the answers take more than a day to find, that is the first finding. An Outcome Baseline measures this path with your team and finds your leak before anything is built. Read the Baseline guide.