Inequalities in cancer treatment access: 10% of Spanish people would have to travel more than 2h every day for radiotherapy
Entry type: Single project
Publishing organisation: elDiario.es
Organisation size: Big
Publication date: 2022-05-28
Authors: Victòria Oliveres, Sofía Pérez Mendoza
Victòria Oliveres: Data journalist member of elDiario.es data team. She is specialized in data gathering, analysis and visualization and focused in education, health, environment and gender stories.
Sofía Pérez Mendoza: Spanish journalist specialized in health, local politics, education and social stories at elDiario.es
Sixty percent of the estimated 280,000 people who are diagnosed with cancer every year in Spain will require radiotherapy, which often requires daily sessions. elDiario.es developed an interactive map calculating for the first time the average travel time for patients from each municipality to receive this treatment. The resulting story found deep geographical disparities: while Barcelona and Madrid have several hospitals offering radiotherapy services, five Spanish provinces and two autonomous cities do not have any. Furthermore, according to the analysis, 10% of the population would have to travel for more than two hours to get treatment.
With this article (link 1) we published, for the first time in Spain, the inequalities in cancer treatment access in different regions. With an innovative approach, we calculated how far people really were from medical centers, going further than the usual analysis of radiotherapy centers per province.
It was shared by multiple stakeholders, including subscribers of elDiario.es, but also medical societies and activists for public health. It was also highlighted by other media and investigative journalists for its innovation in data compilation as well as its visualization. It was also selected by the Global Investigative Journalism Network (link 2).
For this report we created a database compiling the fastest route using a private vehicle between each municipality in Spain and the nearest hospital with a radiotherapy oncology service. We crossed the coordinates of the location of the hospitals with the coordinates of each municipality centroid using the Open Street Maps (OSM) API. With this methodology, approximate route times without traffic were obtained. In the case of trips between islands and between Ceuta and Melilla and the mainland, air travel times have been calculated, but probable waiting times have not been added.
Context about the project:
The first problem we faced when developing this investigation was to find which medical centers had a radiotherapy machine in Spain and classify them between public or private. There was a directory from the Spanish Oncological Society, but it was not up to date. As it did not include all the hospitals and also had some that closed the radiotherapy department, we needed to verify them one by one from their websites and reading newspapers.
After verifying the list, we had to localize every hospital (latitude and longitude) and get the centroids of every municipality for the crossing. The actual process of getting the route times was automatised with R, but lasted more than two days.
We also talked to multiple sources to know factors such as if it was possible for the patients to change to go to a hospital from another province if it was closer to their home than the one in their own province. Or if they could be referred to a private one if there was no service in their area. Knowing these factors helped us focus the analisis.
What can other journalists learn from this project?
With this project we proved that sometimes the inexistence of data is not an impediment to start a project, but an opportunity to create a database and exploit it exclusively.
Also, it shows an innovative way to talk about regional inequalities in health data, with a bigger breakdown than the usually used. Using municipalities made the audience closer to the data, as they could find themselves portrayed in the story.
The data analysis was complemented with stories of different patients that had to travel long distances to receive the treatment and with explanations of cancer experts. This helped humanize the data we were talking about.