“What do Salvadorans die from?” is a project that started from the question what are the type of diseases that affect the Salvadorans the most? Currently there’s no way of accurately knowing this regarding the cases of cancer, chronic kidney disease or other type of diseases, since unfortunately the way the Health System gathers the data of all the people they receive in hospitals is still imprecise. For example, if one person goes to one hospital and then is referred to another hospital, each time this one patient will be registered as a different new case in each hospital. That’s why we decided to ask the Minister of Health for their hospital deaths database, from the years 2010 to 2017. We got a database of 121,395 deaths. Each of these registers contained the age of the patient, gender, place of origin, the date of the death and the diagnosis. When faced with the database we encountered the challenge of analyzing more than two thousand different diagnoses, or causes of death. We had to dig through the International Classification of Diseases ICD-10 to match the codes of the different diagnoses and we added them into two more fields of information, using the general chapters and subchapters of the ICD-10. With this we were able to identify the chronic kidney disease as the major cause of death. For a number of years now, this disease has been recognized as an epidemic in El Salvador, but its impact is often overlooked. This work highlighted the danger of this disease and its mortal trace. But the project was divided in several publications, the first was dedicated to the chronic kidney disease, the second one to the deaths caused by circulatory diseases, and the last one indicated the differences between women and men, for example, in El Salvador, after kidney failure, men die more because of external causes, related to road traffic accidents or injuries caused because of violence. Instead women die more because of diagnoses related to circulatory diseases. This project presented an innovative tool that let the reader know what are the major causes of death of people that share their same characteristics. Using all the causes of deaths, we created a tool that let the user choose their gender and their location to find out what are they more likely to die from as they age. This tools allows to see the huge difference of major causes of death from someone who live in the central city to someone who lives near the coastal areas.
What makes this project innovative?
Using the database of all the deaths registered at 30 public hospitals, from 2010 and 2017, we created a tool that allowed its users to pick their gender and location to find out what are the major causes of death of people that share their same characteristics. This tool visualizes what is the trajectory of the main causes of deaths from the age 0 to 100. For example, a youngster from a central town, is unfortunately most likely to die because of an external cause, related to road traffic accidents or violence. Meanwhile, a man in his forties who lives in a coastal area is most likely to die from chronic kidney disease. This tool is the first one to be made in our country and its an exercise that intents to shade light into the areas that need more attention and work in prevention of certain diseases.
What was the impact of your project? How did you measure it?
We measured our success by the records of page visits and engagement with the users. For example, the "how will you die" tool attracted a lot of attention and the stories reported gained more retention time than other articles. The article was shared among different associations, like the Renal Association.
Source and methodology
The source is the Health Minister of El Salvador. Through a public information access request, we asked for the database of all the deaths registered at the 30 public hospitals of the country. The information requested was the date of the death, the age and the gender of the patient, where were they from, and the diagnosis. This information was recorded by the Public Health System using the International Classification of Diseases, ICD-10. Among the 121,395 deaths recorded, there were more than a thousand different diagnoses. By counting these diagnoses, the main cause of death was “pneumonia” followed by “sepsis” which were general and imprecise. We then decided to use the ICD-10 to match the codes of each diagnosis with the 20 general big chapters and its subchapters. Each diagnosis was put into these two fields. By using the subchapters for the analysis, we were able to detect the burden of the chronic kidney disease among the patients of the public system. Using this information we were also able to detect recognize the areas of the country more affected by certain diseases, which helped to find the human stories. To visibilize this issue we decided to create the interactive tool as a “how will you die” predictor, to attract more readers and let them play with all the data we had gathered and organized.