CareTeam

Problem: About 9 in 10 people with cardiac arrest outside hospitals don’t make it. Annually, this disease affects between 5000 - 6000 people. Just after a few minutes without oxygenation, the brain cells start to die. The average arrival time for an ambulance car is about 8 minutes in a city and in rural areas about 15 mins. There are skilled people willing to help and their potential is untapped.

Solution: We, the citizens, or the doctors who happen to be around, can also help. However, how does the person concerned know that they can save someone's life? We developed an app through which the dispatcher can send a help signal. The AI further evaluates who among the informed is closest to the affected person and can start helping and who can run to get the AED. We would like to use it as a recommendation system - recommend sending a doctor nearby to the patient and an amateur to bring the AED.

Impact: Our app may decrease the arrival time by 90 seconds on average. In special cases, volunteers can help immediately in a range of 120 to 180 seconds as they are nearby. There is a huge potential. 6000 people a year are affected, and we can increase the survival rate dramatically.

Feasibility & financials: Two possible approaches - the main one is to integrate it into the Zachranka App. The rough estimate for development is 30K EUR. Or we can launch it as a new app, it would cost around 160K EUR. Marketing is also required, from 5K - 20K EUR. Our business model consists of a non profit function. There are opportunities for cooperation with insurance companies. In theory, hospitals can pay a monthly fee for the possibility of using this function. Early adopters: 100K Czech doctors + med. students.

What is new about your solution?: We aim to integrate more than just running or walking into the app. We also want other types of transportation, such as Uber, Lime scooters or Liftago, to make the process even more efficient and decrease arrival times. Additionally, we want to include more factors than distance when choosing which volunteer will go for what - A doctor will go immediately to the patient, whereas a less-skilled person will bring AED. The whole system can work as an AI recommendation system for dispatchers.

What you have built at the hackathon - text explanation + code (e.g. GitHub link): We coded an MVP of the project. The app is developed in Flutter for iOS and Android with the same codebase (40% cheaper than native). Backend in Firebase services. We also had 2 iteration checks with doctors to ensure we understood the problem correctly and are on the same page. Furthermore, we recorded a pitch video and are ready to kick off the project. https://github.com/MatejKrcek/ikemHack https://docs.google.com/document/d/1WXNVbxX2V2LZ1k0JuR1sh6Go2jmR7VbRJnCFahKSlAQ/edit?usp=sharing

What you had before the hackathon, please mention open source as well: Experience. Tomas is a designer, has a company focused on website development and started a non-profit organisation Comenio which helps Ukrainian students with integration. Matej is a developer, works at Deloitte on innovations, and has previous experience with the HeatlhTech project, developed an AI app for people with Alzheimer's in high school. Max is responsible for operations. He launches a FinTech student project educating society on the importance un understating finance.

What comes next and what you wish to achieve: Our primary goal is to integrate our solution with the Zachranka application. We would like to continue working on this project, in the *cealestinus incubator. To be successful, we would mainly need support from the medical side - consultations with doctors, experts, or paramedics. Next steps: build a team and define roles, find doctors interested in the problem, and reach out to Zachranka as well as Vodafone, PPF and other foundations. Cesko.Digital can help with app development.

Video: https://www.youtube.com/embed/EWdMNigqcgg