Predicting Cancellations in the NHS with Machine Learning and Data Science

As the NHS continues to strive to become more efficient, the ability to accurately predict cancellations is becoming increasingly important. Cancellations can have a significant impact on patient experience and the overall efficiency of the service. Understanding which patients are likely to cancel their appointments can help the NHS to plan, staff and manage resources better.

Many NHS organisations are currently using predictive analytics to identify cancellations in advance. This involves analysing historical data to identify patterns that indicate an increased risk of cancellation. For example, the NHS may look at factors such as previous cancellations, distance from the hospital and appointment times and paydays, including benefit payment dates.

How machine learning and data science can be used to predict and prevent cancellations and no-shows?

Predictive modelling: Machine learning algorithms can analyse historical appointment data to identify patterns and relationships that are associated with cancellations and no-shows.
Clustering: Data science techniques, such as clustering, can be used to group patients based on similar behaviour patterns. This can help identify high-risk groups of patients who are more likely to cancel or not attend appointments.
Root cause analysis: Data science techniques can also be used to perform root cause analysis to understand why cancellations and no-shows occur.

With this information, healthcare providers can then take steps to prevent cancellations and no-shows, such as sending reminders to patients or rescheduling appointments.

Various healthcare organisations around the world have implemented machine learning and data science solutions to reduce the rates of cancellations and no-shows.

In 2021-22, 6.4% of outpatient appointments were ‘Did Not Attend’. This is an increase of 15.6% from the previous year.¹

Machine learning and data science have the potential to improve appointment attendance and reduce the impact of cancellations and no-shows on the NHS.

By using machine learning and data science, healthcare providers can be more efficient and effective in reducing the impact of cancellations and no-shows.

The goal is to make sure that patients get the care they need, when they need it, and to reduce wasted time and resources.

Data science for NHS and UK Healthcare, such as machine learning can empower your organisation to make faster and better decisions; enabling you to predict probability with confidence.

Questions

If you have any queries regarding Data Science for UK Healthcare, like machine learning or the tools mentioned in this article, please don’t hesitate to reach out to us via our live chat. One of our specialists will be more than happy to answer your questions.

[1] Hospital Outpatient Activity 2021-22

Blog Author

Paul Deluce, Lead Consultant, Simpson Associates