Inspiration

While doing her masters research in data science focusing on health issues, Tsitsi found out that doctors are usually able to tell whether or not a fetus might have an abnormality only after the second scan which happens after 22 weeks. It is at this point that an expecting mother gets options including termination in certain cases. This can be very emotionally exhausting and also leaves less room to mitigate risk. This realisation coupled with Tino's dream to go back to medical school and his passion for medicine gave birth to Guardian Health. With the both us well versed in technology and passionate about health, we started on our journey to transform the health system for the better with solutions that benefit every citizen regardless of social status.

The first thing that we did is we built a system that can help health professionals with the early detection of fetal abnormalities and gives the risk of an expecting mother to get a caesarean. Our solution looked great, however we realized that having such a solution without solving some of the problems the health sector is facing might make the adoption a little difficult.

We then proceeded to build a platform that allows patients to book appointments with health care providers. The appointments can be in-clinic, after hours or virtual. Virtual appointments can be conducted via the Guardian Health platform with access to digital notes and digital prescriptions that can be ordered for delivery via the platform. Digital filing and digital prescriptions are also available for in-clinic appointments. These are very important as they allow patient history to be easily transferred and easily accessible thus improving provided health care. The maternal health detections can be used to also refer patients to hospital when their risk is high.

What it does

Our solution is a system that connects patients and health professionals. It also allows for early detection of maternal health issues.

  1. Patients are able to book appointments.
  2. Appointments can be in-clinic, after hours or virtual appointments.
  3. Virtual appointments are performed on the Guardian Health platform.
  4. The platform also provides digital notes making it easy to transfer patient history when patients are referred to a different health care provider improving quality of health care.
  5. The digital prescriptions offering allows patients to order and receive prescriptions from the comfort of their homes.
  6. The platform also allows patients to pay for appointments using credit cards on the platform.
  7. Patient risk factors such as high risk of getting a caesarean section are used to refer them to a hospital.
  8. Early detection of fetal abnormalities is performed also allowing for the referral of high risk patients to hospital.
  9. The management allows facility admins or receptionists to manage multiple doctors by onboarding patients, health professionals, handle billing, appointments and all other management tasks.

How we built it

  1. We built a web app for the patient side.
  2. We also built a web app for the health professional side.
  3. We used machine learning algorithms for the predictions of caesarean risks and fetal abnormalities.

Challenges we ran into

Unfortunately we were not able to finish our billing functionality as it relied on things outside our control.

Accomplishments that we're proud of

  • Ability to bring together optimisation methods, natural language processing, analytics and AI into our solution.
  • Coming up with a solution that is relevant to society and can make a much needed difference.

What we learned

  • Through research, we learnt how vulnerable the health sector is and how much of a difference solutions that can make it more efficient would make.

What's next for Guardian Health

  • Actively developing Guardian Health to launch into the private sector and onboarding health professionals and users onto the platform.
  • Partnering with relevant stakeholders such as pharmacies and medical aids/health insurance to ensure success for our platform.
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