Lulan Emergency Routing App was conceptualized to “light the path” for people towards efficient and appropriate healthcare. This is especially since infection risks are of utmost concern during the pandemic, a fact that has consequently altered how people react to non-COVID related health emergencies. With this, the application also addresses one of the United Nations Sustainable Development Goals– Good Health and Well-being.
The pilot location of the application is set in Cebu Province. The population density of the province was observed with NASA’s Worldview, together with Google Maps’ hospital locator and Philippine GeoPortal’s COVID-19 testing center locator. With the gathered information, we will eventually be able to create a seamless working algorithm which will direct COVID-suspected patients to the nearest testing centers, and non-COVID related patients to hospitals with low COVID patient densities. This is to ensure that patients are brought to the safest and most efficient hospitals possible. The efficiency is determined based on distance, estimated travel time, hospital bed capacity, and equipment available (for COVID & Non-Covid cases).
With a generation experiencing a global pandemic, each country’s response is of great importance– especially with regards to their respective healthcare systems. The Philippines’ response to the situation undoubtedly still calls for improvement as evidenced by lacking equipment and faulty approaches, with the ratio of government hospitals to population being approximately 1 : 229,306 (PCIJ Data Team, 2019). A number of hospitals and medical facilities were advised to accommodate only COVID-19 patients as it is of greatest priority in current times. Due to this, there have been reported events of non-COVID related patients who were in need of urgent medical attention, but were rejected by certain hospitals. One case was of an elderly who was refused by 6 hospitals, and died hours later (Philstar, 2020). Another case was of a woman who just gave birth needing surgery, but was rejected by 6 hospitals (Philstar, 2020). Both cases point out that the hospitals either did not have vacant rooms and beds, or were being used as COVID facilities. Our application, the Lulan: Emergency Routing App, aims to address this problem. Both patients with COVID or non-COVID cases have the right to receive the medical attention they need, and Lulan paves way for its users to be properly informed as to which facilities could accommodate their medical needs in case of emergencies.
Malintala focused on how the efficiency of seeking medical attention in this time of crisis can be improved. The application’s user interface and general flow were optimized to ensure a user-friendly design which is fast and easy to use. The team also considered many factors that affect choosing the best facility to go to including the following:
We used the population density data from NASA’s Worldview as a factor which was connected to the aforementioned factors. These were also used to help avoid the heavily dense areas for non COVID-19 patients, especially with situations that are not urgent. The application uses an algorithm that looks for the nearest hospital or facility that can accommodate the patient based on condition and urgency. The programming language used for the sample codes was Java, using Netbeans, Android Studio and Xcode as the programming platform.
One of the issues faced at the beginning was that the team could not find space agency data that can be used for the project. The group eventually realized that population density is an essential factor to hospital capacity, as well as infection risk. Through the gathered visuals of Cebu province in the Philippines regarding population density, hospital locations, and test center locations from NASA’s Worldview, Google Maps, and Philippine GeoPortal respectively, it was observed that there were more hospitals located in more populated areas, but the testing centers were not as much nor as spread out. The team consequently came to the conclusion that the densely populated areas, especially around COVID-19 testing centers, should be avoided to minimize infection risk. The data regarding hospital and testing center locations were incorporated to propose an application that can direct patients to appropriate hospitals that can accommodate them, but could also be reached in the time appropriate to the urgency of their situations. A flowchart was also made to easily understand the ideal process undergone in the application. It also goes to show how simple and easy-to-use the application would be, while ensuring that it could run as quickly and efficiently as possible– considering that user inputs are expected to be emergencies.