Augmenting Patient Care with Predictive Analytics

Generally, surgeries expose patients to an array of possible surgical site infections (SSIs). SSIs are expensive for healthcare providers and patients because they can lead to more postoperative complications and chronic wounds. Any postoperative complications have a huge financial impact on healthcare providers, patients, and insurers. Surgeons do not have a tool to monitor post-op wounds remotely, catch SSIs early, and eliminate unnecessary office visits.

The MyHealthPal platform leverages the power of artificial intelligence and machine learning to facilitate the analysis of surgical site incisions (SSI)  to predict early signs of SSI infection.  The prediction is enhanced by vital signs data entered by the patient using a smart tablet or smartphone.  By doing so, it automatically generates alerts to healthcare providers, enabling them to monitor surgical site infections and focus on patients who require immediate attention.

Post-operative patients' journey is filled with challenges. Upon discharge, the patients are sent home with little support to track their health status and avoid complications. 

On the other hand, clinicians need new, reliable ways to monitor and optimize post-operative surgical incision follow-up. 

We are working with patients and surgeons to understand the disconnect after the patient is being discharge and how we keep the patient in contact with his clinical team to provide up to date medical advice

Predictive Healthcare is founded and led by Talal Ali Ahmad, a 3x startup entrepreneur with successful exits. Talal has been either part of a startup team or was the startup's founder. He has taken companies from an idea to commercialization and has successfully raised funding for startups. We created medical advisory board from different speciality to guide us with our mission nd product development

We need to put the product to work and show that the solution can cut unnecessary office visits and reduce Emergency Room visits.  The prize will enable us to deploy the product  and continue enhancing the solution to support a wider range of surgeries.,

Our founder is a volunteer with Global Smile Foundation and provides the product free of charge and is in touch with the patients and surgeons to get their feedback to improve the product stays helpful and improve the healthcare delivery standard.

MyHealthPal is an artificial intelligence-based algorithm that analyzes postoperative surgical incision photos and data that patients enter into the platform to monitor for surgical site infections and send alerts to clinicians.

The solution revolutionizes the assessment of patient surgical wounds by eliminating the need for physical visits to clinicians. Through the power of a mobile application, individuals from anywhere in the world can conveniently access healthcare providers to assess their wound status and receive medical advice. This innovative approach enhances accessibility to proper healthcare and eliminates geographical barriers that may limit patients' access to timely and expert medical guidance.

Our impact goal is to establish a means for patients to connect with clinicians throughout their surgical recovery, especially when they reside in remote areas with limited access to healthcare providers. By utilizing their mobile devices, patients can receive the necessary medical advice and guidance, enabling them to address their concerns effectively. This approach empowers individuals in underserved areas by bridging the geographical gap and ensuring they can access timely and appropriate healthcare support, enhancing their overall surgical recovery experience. The goal is to detect early signs of infections and address them before they create more complications dn sometimes death.

In September 2022, our solution was deployed by the Global Smile Foundation (GSF), a US-based NGO, to monitor postoperative patients in Ecuador and Lebanon. By providing daily wound images, vital signs data, and predictive outcomes, the solution offered valuable insights to surgeons and clinicians without requiring patients to undertake lengthy journeys for clinic visits. Currently, GSF's patients have shown an impressive 85% compliance rate in using the application, while our predictive outcomes boast an accuracy rate of 84%. Notably, the solution successfully detected all instances of postoperative surgical wound infections at an early stage, enabling prompt intervention by clinicians. This implementation has significantly improved patient care, minimizing the need for physical visits while ensuring timely and effective treatment for surgical complications.

Our approach of monitoring surgical site infections using AI and mobile devices can have a significant impact on the problem for several reasons.

Firstly, by using AI algorithms, we can analyze photos of surgical incisions and other data entered by patients into our mobile application. The AI algorithms are trained to identify signs of infection, such as redness, swelling, or discharge. This helps in early detection of infections that might otherwise go unnoticed.

Secondly, the use of mobile devices allows patients to easily capture and share images of their surgical wounds with healthcare providers. This eliminates the need for patients to physically visit the clinic for wound assessment, especially for those in remote or inaccessible areas.

The combination of AI analysis and mobile device accessibility enables timely monitoring and intervention. If an infection is detected, alerts can be sent to healthcare professionals, who can then provide guidance and appropriate medical treatment remotely. This proactive approach helps prevent infections from worsening and reduces the risk of complications.

By offering convenient and remote monitoring, our solution improves access to healthcare for patients who may face barriers to in-person care. It also optimizes healthcare resources by reducing the need for unnecessary clinic visits and allowing healthcare professionals to focus on more critical tasks.

Overall, our AI-based monitoring of surgical site infections using mobile devices enhances early detection, enables timely intervention, and improves patient outcomes by providing accessible and convenient healthcare support.

The platform is comprised of a patients' app, a clinicians' app, and a clinician's desktop dashboard. Patients take photos of their superficial surgical incisions using their smart devices such as smartphones and enter additional data to improve prediction accuracy. The algorithm then analyzes the data and renders a standard or elevated infection risk prediction. Clinicians receive elevated risk alerts and have full access to all the patient data to inform their decision-making

We have successfully deployed our solution in collaboration with the Global Smile Foundation (GSF), a US-based NGO specializing in Cleft Lip surgeries in Latin America and the Middle East. This implementation empowered GSF to remotely monitor their patients and gather crucial information about their wound healing progress, eliminating the need for patients to undertake long drives for follow-up visits. For statistical data and further details, please refer to the following link:  MyHealthPal - Predictive Healthcare

Developers 3 full time, 2 part time

Project manager partime

Sales Full time

2 years

We are developing our algorithm to detect different skin tones  to ensure that our application can work on all skin color people and does not exclude them from using the applciation

Our business model is to first focus on specific surgeries with high surgical site infection rates and high hospital readmission rates within the first 30 days post-surgery. 

We already have investment from Friends and Family, and we are in the process of rasing additional funding from angel investors and venture capitalist.