Did Not Attend (DNA) rate is the standard metric that hospitals use to understand how effectively their clinics are running. For the NHS, the DNA rate of a clinic is normally associated with its’ financial performance i.e. higher DNA rates are seen to indicate worse financial performance for a hospital. Understandably the fixed cost of running a clinic will remain similar regardless of whether patients turn up for their appointments or not. Staff will still be paid, and utilities and equipment will still be maintained.
For the past 20 years there’s been talk in the media of how much it costs the NHS when appointments are missed . But the problem of people not turning up for their hospital appointments remains.
Here at DrDoctor we are committed to creating common-sense technology that helps the NHS run better. A lot of our work focuses on improving DNA rates for hospitals by empowering patients to gain autonomy over their care and the ability to choose their own appointment logistics. But we strongly feel that DNA rates alone are not a reliable indicator of clinic financial performance.
DNA rate is normally calculated as:
Let’s look at a worked-out example of this; if you have 10 appointments booked and two people miss them, you have a DNA rate of 20%. If you have 10 appointments booked, one of them cancels the day before, and one person does not turn up, you have a DNA rate of 11%.
In both cases eight appointments took place out of 10 possible slots. The second example shows a better DNA rate, without any financial improvement for the clinic. The change in DNA rate has no impact on improving the financial performance of the hospital, waiting times for patients or the care they receive. In fact, a clinic’s DNA rate can be improved while worsening all of these.
In addition to this, many solutions that aim to improve DNA rates fail to consider cancellations. If patients call in and cancel their appointments at a late notice this results in an improved DNA rate for the clinic. The core issue remains here which is that a free appointment is still not being used, and the potential to see other waiting patients and the cost is going to waste.
We’ve done estimates on this by tracking the knock-on effects of DNA rate reductions. We found that between 30-50% of a simple (i.e. without addressing other issues) DNA rate improvement ends up resulting in no actual value.
We find it a shame that so many hospitals can only work with this metric as their primary measure of good outpatient services. It’s understandable as often this is the only metric they can measure. Associating this metric with financial value is ultimately missing a large part of the picture. There are much more useful metrics, like clinic utilisation or booking efficiency, which could offer more insight into financial performance, but they are often much harder to measure.
Although its hard to do, we support a lot of our partners to better understand these metrics so that they can better control their outpatient services and have a much more sophisticated and wholistic understanding into what’s actually going on. Decisions (and the financial management of the NHS) could then be based on something more meaningful and direct. We find that the few organisations that use these metrics and are setup to act on them can achieve much higher productivity. Without the need to resort to overbooking clinics or other superficial solutions.
The airline analogy
Let’s look at a commercially incentivised business as an example of financial management. The airline industry experiences analogous problems with people not turning up for their flights. It’s crazy to think an airline wouldn’t know how many seats there are on each flight they operate. Yet many hospitals don’t really know how many appointment slots were available in each clinic each month. They use information about the no-show rate to varying degrees of complexity to overbook flights and they are very good at making sure they extract all the value they can from their capacity. We realise the NHS has to sometimes resort to a blanket overbooking strategy, which results in misery for patients and staff. We’ve all seen or heard of the misery caused when people turn up for flights and don’t get on due to overbooking. The same misery happens in healthcare. We’ve found overbooking simply isn’t necessary in the NHS and it shouldn’t be used.
The underlying booking processes need to be as controlled as they can be first. There’s no point optimising a bad process. Apparent improvements to incomplete metrics just compounds the underlying problems. What really needs to be done is to build a better process (and then optimise it).
A better booking process
Although DNA rates are not an optimal indicator for what they’ve been used for traditionally, they are a good indicator of some aspects of the booking process. Across all the partners we work with we often see massively varying DNA rates even with the same levels of feature adoption. The best booking processes have DNA rates of 3-5% whereas the worst tend to be in the 12 – 15% range.
This is one of the reasons DrDoctor don’t focus on technology alone – we always work to get processes right first and then use the technology to support, scale and sustain better processes.
What’s the point of reminders?
Apparently, people forget to attend their hospital appointments, which is interesting because people don’t tend to forget to turn up for a flight, or that their leg hurts. They miss flights, yes, but they rarely forget to turn up. ‘Reminder’ is perhaps not the right term as often the real reason reminders improve DNA rates (and they do) is because people haven’t actually engaged with the fact they have or need an appointment. This can mostly be addressed through better processes (such as not booking appointments 6 months out) and ensuring the [n process points] about booking processes are addressed in the first place.
Of course, great booking processes don’t help unless they are well communicated (which is a whole other issue which we’ll try and write about soon).
In order for the NHS to use operational metrics to drive financial performance or at least to understand the metrics for financial performance, they should stop using DNA rates and to start working towards a collection of metrics that help managers and staff address the underlying issues in administrative and clinical practices and the effectiveness of their communications.
The NHS should use DNA metrics within their limits – as an indicator of certain aspects of scheduling. DNA rates are a reliable indicator of a broken scheduling process, or low clinical engagement and patient activation i.e. if a patient doesn’t think it’s clinically valuable to attend. ‘Reminders’ are useful, but the point isn’t because people are forgetting that they need care.
Getting the right patient in the right slot at the right time, the first time, and ideally with the right preparation, information and understanding- that is the key to success.