Data

The data used in this project is drawn from integrated care board (ICB) information. The dataset included appointments location, date, duration, type, mode, status, service setting, context type, national category, count of appointments and time between booking and date of the appointment. ICBs are statutory NHS organisations involved in providing health care and managing budgets for specific geographic regions in England. There are over 40 of them. They are further divided into sub-ICBs.

Please note that the scenario in this project is fictitious. Any resemblance to real persons, living or dead, is purely coincidental.

The dataset was manipulated and visualised using Python and a course of action was recommended based on the results.

Scenario

National Health Services (hereafter “NHS”) is a publicly funded healthcare system in England that is incurring significant avoidable costs due to the large number of patients that miss their medical appointments. In this project, we focus on potentially existing gaps on NHS’ resources and capacity that affect the ability of patients to attend their appointments. Also, we identify few leads for further exploration on the topic. Mainly, we address: Has there been adequate staff and capacity in the networks? What was the actual utilisation of resources?

To explore the above questions we look at:

How many locations, service settings, context types, national categories, and appointment statuses are there? What are the five locations with the highest number of records? Between which dates were appointments scheduled? Which month had the highest number of appointments and records per month? What trends are evident, based on the number of appointments for service settings, context types, and national categories? What are the top trending hashtags (#) on Twitter related to healthcare in the UK?

Insights

Below, the video leads you through the main conclusions of the analysis:

Additionally, the following report allows you to find further details on the analysis performed, insights extracted and conclusions reached:

Finally, the dashboard built for this project can be found on my Github repository here.