Reduce no-shows in ophthalmology and recover lost revenue | Noshowsvoorspellen.nl

Recover revenue lost to no-shows in ophthalmology

Demonstrable results within 90 days, without extra administrative work.

Book an introductory call See if this makes financial sense
You only pay for success
Proven in hospitals and mental health care
Less administrative hassle
No-show prediction dashboard

Trusted by healthcare organisations including:

Erasmus MC logo Arkin logo

In previous projects, an average of 14% of the revenue lost to no-shows was recovered.

Sound familiar?

No-shows in ophthalmology are rarely “one-offs”

A missed appointment seems small. But in ophthalmology it adds up fast: full waiting lists, empty slots in the schedule and extra rescheduling.

Empty slots while the waiting list is full

No-shows leave “gaps” you often can't fill in time. The result: less productive clinics and patients waiting longer than necessary.

Revenue loss that adds up per clinic session

One missed appointment is lost revenue and lost capacity. Over a year this becomes a structural cost that is often not explicitly visible in the schedule.

Fixing it afterwards mostly costs time

Invoicing or calling patients after a no-show often leads to disputes and extra admin. The goal is to identify no-show risk early, helping your team plan follow-up and manage capacity more predictably.

Financial impact

What do no-shows cost you in capacity and revenue?

It's not just lost revenue per appointment, but lost capacity, extra rescheduling and less predictability.

Worked example (indicative)

1 no-show per day × €185 per appointment × 48 weeks = €44,400 per year in lost revenue (example figure).

Hidden costs

  • More rescheduling and extra phone calls
  • More admin and disputes afterwards
  • Unused capacity while the waiting list grows

As long as this stays invisible, it remains a hidden cost.

See how much revenue you lose each year

How much revenue do you lose to no-shows each year?

Enter your numbers and instantly see how much revenue you lose each year. Based on real-world data.

What do you already know?

Annual loss due to no-shows

€0

Indicative calculation based on the numbers entered and 80% fixed costs

This money does not come back through rescheduling or no-show fees.

In the next step you'll see how much of this can actually be prevented

You can recover €0 – €0 per year

You only pay for no-shows that were actually prevented.

Estimate based on experience with comparable organisations. Not a guarantee.

Find out if this works for you Impact analysis: 15 min • No preparation • No obligation

Without a targeted approach, this loss comes back every year.

Reality check

How much of this can realistically be prevented?

Not every no-show can be prevented. But a share follows predictable patterns (for example timing, lead time to the appointment and no-show history). That lets you follow up in a targeted way without extra pressure on the organisation.

A share can be structurally influenced

A measurable share of no-show losses can be reduced with targeted follow-up — without turning your whole process upside down.

Estimate based on practical experience. Not a guarantee.

How I prevent no-shows

Step 01

We predict which patients will not show up

Every day we analyse scheduled appointments and flag the ones with an elevated risk.

Step 02

We only call patients with a high no-show risk

Targeted phone reminders make sure appointments still go ahead. This works alongside SMS and email reminders.

Step 03

You see exactly how much revenue was recovered

Insight into prevented no-shows and recovered revenue, fully measurable and transparent in a dashboard. The approach and results are scientifically proven. Read the paper

You only pay for proven results

A results-based approach informed by work with Erasmus MC and Arkin.

You only pay for no-shows that were actually prevented.

No results = no costs.

First results within 90 days. You see how many no-shows were prevented and what that is worth.

You only pay once results are visible. Example: no-shows prevented in January are not invoiced until the end of February.

See how the results guarantee works

Frequently asked questions

Practical information about implementation, data security, costs and results.

Will this work for our organisation? ⌄
If your organisation manages scheduled appointments, the approach may be relevant. No-show risk varies between appointments and can often be predicted from existing data.

In a short initial analysis, we assess whether your data can support useful predictions and estimate the potential financial impact of acting on them.
What does it cost? ⌄
Fees are based on no-shows demonstrably prevented through the solution.

There are no fixed licence fees, no implementation fees and no upfront costs.

There are no licence, implementation or upfront fees. Before proceeding, we prepare a business case to estimate the likely value for your organisation.
When do we pay? ⌄
Payment is always made afterwards, based on no-shows that were demonstrably prevented.

If no no-shows are prevented, nothing is invoiced.

Example: no-shows demonstrably prevented in January are not invoiced until the end of February.

This means there is no financial risk upfront. You only pay for proven results.

Read more about my results guarantee .
What do we need to do ourselves? ⌄
The effort on your side is limited and mostly about explaining how things work.

You explain:
  • How no-shows are recorded
  • Where appointment data is stored
  • Which definitions are used internally
Using this information, I prepare the appointment data needed to build and run the prediction model. This may include factors such as appointment details and no-show history.

The work can be coordinated with your IT team or carried out independently. On-site support is available when needed.

Data never leaves your organisation.
What if it doesn't work? ⌄
No approach can guarantee that every no-show will be prevented. The aim is to identify appointments at higher risk and make timely, targeted contact.

If you decide to work with me, you only pay for no-shows that were actually prevented. If no no-shows are prevented, you pay nothing.

Initial results are expected within 90 days. We then review the measured impact together. If the business case does not stack up, you can stop without being charged for results that were not achieved.
Is this secure and GDPR-compliant? ⌄
Yes. The solution runs within your organisation's existing IT infrastructure. Data does not leave your organisation.

The prediction model works with pseudonymised appointment and patient data. Identifiable data is only used where operationally necessary.

An example DPIA is available on request. The approach has been applied in hospital and mental health care settings and was reviewed with Data Protection Officers.
Why don't SMS/email reminders already solve this? ⌄
SMS and email reminders are a good first step, but they don't prevent all no-shows.

Combining risk predictions with targeted phone reminders can help teams focus their calls on appointments where follow-up is most likely to make a difference.

If you don't use reminders yet, you can expect an even higher return.