Locating the Right Place for Blood Donation in Hong Kong by Data Analytics

Big data is the use of data mining techniques to analyse large amount of data that were collected from different sources in order to derive useful insights. Essentially, data mining extracts patterns and details from digital records and turns it into useable information about human preferences and behavior patterns. It allows entities like governments and corporations to make strategic decisions or to plan when and where to build facilities like hospitals, schools and supermarkets.

When the Hong Kong Red Cross Blood Transfusion Service (BTS) was looking for a site for a new donor centre, they sought academic help to find the best location.

Dr Michael Chau, Associate Professor in the Faculty of Business and Economics at The University of Hong Kong, took on the project with the aim of finding a suitable site that would ultimately increase blood donations.

"They provided us with a lot of data of the past usage of blood donation records of where the donors live and where they made their donations," Dr Chau said. "After we have analysed the data it pointed to Yuen Long but Yuen Long is still a very big district."

So the next step for Dr Chau and his team was to analyse the data they had for the district at a "finer level", which meant looking at the flow of people in Yuen Long, transportation to the town and where individual MTR and bus stops were.

The result of the research and data analysis led to a site that was approved by the BTS. It has since opened and has been as successful as they hoped, and as the data analysis suggested.

For Dr Chau, the success of the project shows how academic findings and data mining techniques can be applied to "real world" issues, and this is something he hopes to do more of in the future.