Case study: Big Data and APIs help to improve an hospital

2 min reading
Case study: Big Data and APIs help to improve an hospital
Case study: Big Data and APIs help to improve an hospital


The benefits of using APIs are increasingly being felt across all sectors, including healthcare. One example is the University Hospital of Liège, Belgium, which has managed to be more efficient thanks to a simple visualization generated by IBM’s Watson Analytics, an API that offers a predictive data analysis service.

Hospital funding in Belgium is based on the activities they carry out throughout the year, as reflected in a federal portal that compiles the reports sent to the public health service. Based on this data, a national average is established that sets the guidelines for allocating funds to each hospital in relation to the points obtained.

“We knew that these reports are a gold mine that could help improve our nursing practices and the hospital’s overall performance, and we wanted to be able to understand them more easily”, explains Olivier Thonon, head of nursing and a researcher at the Belgian hospital.

Each hospital receives every year several complex Excel files that contain the annual feedback and all the details about their score. To help improve both nursing resource planning and performance in general, the University Hospital of Liège wanted to structure its activities based on this information.

And here is where IBM Watson Analytics comes into play. This smart data service available in the cloud serves as a guide for exploring data, automates predictive analysis and allows to create easily computer graphics and visualization panels.

The tool allowed the University Hospital of Liège to visualize all the data from the federal reports and benefit from the feedback in an agile way, thus improving the quality of its services, both medical and related to nursing, and adding supplementary information when needed.

Ultimately, the strengths of Watson Analytics are:

It speeds up the processes, facilitating the understanding of complex data without having to build a previous model.

It saves analysis time and resources, enabling a single user to make advanced queries.

It extends the visibility of the metrics, which are key to performance throughout the organization.

Olivier Thonon sums it up as follows: “Our first goal was to be able to extend the feedback reports and we’ve clearly managed to do this. In fact, we’ve gone further: we felt that these files contained a large amount of information, but not to what extent. Now we understand the key points and this will enable us to make practical changes.”

The head of the nursing area knows that they will need time to change their working practices, but they have already come a long way: “The ability to visualize the data is a great help and facilitates communication of the analysis, so everyone in the organization can understand what needs to be done.”


Are you interested in financial APIs? Discover all the APIs we can offer you at BBVA


It may interest you