We’re all only human. And human behaviour is often a complex thing to predict. At DrDoctor we’re committed to understanding patient behaviour and using that understanding to influence how we design our services.
We believe that to run a good hospital we must strive to make it work for everybody involved. This means all the staff as well as the patients. There are many variables that affect human behaviour and have an impact on whether or not someone attends their hospital appointment. After looking at data from one of our partner hospitals, we found that weather, distance from hospital, clinic specialty, age and gender all affect the likelihood of a patient attending. When looking more closely, we noticed that these trends can be seen across all our partner hospitals, all over the UK.
We used a sample size of over 845,000 anonymised appointment details to dive into the stats – searching for insight into what makes someone turn up. The number of missed appointments is often called the Did Not Attend (DNA) rate and we calculated it as a standard rate of 6.45% at this hospital (Although it was ~10% before DrDoctor was implemented). We saw the following trends;
- DNA rates highest in young adults in their early 20s (>11%)
- DNA rates also high in babies under two (10%) (or perhaps more accurately, the carers responsible for them)
- Men are more likely to miss appointments than women
- This is especially true for males aged between 20 – 25
Young adults are maybe looking after their own lives for the first time. Perhaps they are less organised, which can lead to missing appointments. But why are young men in particular much more likely to miss an appointment? According to the data young children are also more likely to DNA. Is this purely down to parents’ poor organisation, or is something more subtle at play here?
- Audiological medicine & Oncology showed the lowest DNA rate (3 – 3.5%)
- Diabetic & Respiratory medicine had the highest DNA rate (~10%)
Attendance seems to be highest in clinical specialties where the complaint has a significant impact on a patient’s quality of life or is viewed as very serious. This has led us to consider the possibility that the greater the impact a condition has on your life, the more likely you are to seek, value and attend treatment.
Distance from hospital
- The closer you live the more likely you are to NOT attend!
- This is especially true for patients living 1-2 miles away as opposed to 9-10 miles
We thought it was interesting that the closer you live to a hospital, the less likely you are to attend. This is especially true for hospitals set in urban rather than rural areas.
- Patients less likely to attend in terrible weather
- Patients MORE likely to attend in unpleasant weather
- Patients less likely to attend in hot weather
Some of these findings are not surprising. We’re all likely to stay indoors with a cup of tea when it’s grim outside. However, it looks like unpleasant weather is less likely to deter people of Britain from leaving the house. This may be due to our national thick skin when it comes to a bit of rain / wind. But truly horrible weather is horrible, even for our nation. And when it’s sunny outside, we expectedly want to be there too and perhaps are more likely to make a conscious decision to skip an appointment.
- Patients are most likely to cancel one day before an appointment
- People are then most likely to cancel in seven-day intervals; 7 days, 14 days, 21 days before the date etc
Perhaps it is unsurprising that patients that choose to cancel their appointment are most likely to do so only one day before. Life can just get in the way sometimes. Perhaps a week before is also unsurprising when making plans for the week ahead. But we have not been able to get our heads around to why cancellation rates tend to follow seven-day intervals. This goes beyond running your finger down the calendar. This is complex human behaviour.
So what are we doing about this newfound understanding? We are committed to helping hospitals counteract unusual behavioural variables. We’re doing this by choosing who we offer appointments to and at what times. We are being conscious of what factors affect attendance and are using this insight to change processes for the better. Our promise is to help make healthcare work for everyone, and every additional insight takes us one step closer to building a system that works for you.
Have you noticed any other similar trends?
Do you have any clues for why these trends exist?
Do you have any ideas on how we can all use this knowledge to improve the health system?
If so, or if you have any comments, we’d love to hear from you!
Drop me a line on firstname.lastname@example.org