Sceptech

Data analytics can help reduce the impact of antimicrobial resistance and bacterial infections in low- and middle-income communities.

Jane Odey 

Radiographer. Front-End developer and a Techpreneur.

Our solution is focused on solving the problem of health disparities caused by a lack of access to high-quality health information. Specifically, I am working to improve health outcomes for people in underserved communities by providing them with access to accurate and relevant health information. 

This problem affects millions of people in Nigeria and around the world. According to the CDC, health disparities result in a higher incidence of disease, disability, and death for those who are affected. 

According to the CDC, there are significant disparities in health outcomes for racial and ethnic minorities in the United States.  African Americans have a life expectancy that is 3.5 years shorter than white Americans, and they are more likely to suffer from chronic diseases like diabetes and heart disease.

 Hispanic Americans have a life expectancy that is 1.9 years shorter than white Americans, and they are also more likely to suffer from chronic diseases. These disparities are driven by a variety of factors, including socioeconomic status, and environmental conditions.

 This problem leads to suboptimal diagnosis and treatment of infections, which can result in unnecessary suffering and death for patients,

This problem affects millions of people in low-resource settings around the world.

My solution primarily serves healthcare professionals, patients, and institutions in low- and middle-income countries. It helps healthcare professionals by providing them with real-time alerts and recommendations for infection prevention and control. It helps patients by reducing their risk of developing infections and reducing their exposure to resistant strains. It helps institutions by enabling them to track and manage infections more effectively.
We seek to support these groups by understanding their needs through regular surveys, interviews, and feedback mechanisms. We also work closely with them to ensure that my solution is user-friendly and addresses their specific needs.

Our solution is focused on addressing the needs of those who are most at risk for infection and resistance, including:
- Healthcare workers in resource-limited settings
- Patients in low-resource areas with limited access to clean water, sanitation, and hygiene facilities
- Populations that are at high risk for infection due to their health conditions or environment.
We are committed to developing a solution that is tailored to the unique needs of these groups. This is why we place such a strong emphasis on understanding and engaging with them throughout the development process.

My solution provides several public goods. First, it generates new knowledge about the relationships between diseases, symptoms, and treatments. This knowledge can be used to improve diagnosis and treatment and to better understand the causes and consequences of disease. Second, the model itself is open-sourced and available for anyone to use. 

This allows other researchers and organizations to build on the work I have done and to create their applications and solutions. Third, the results of my solution are shared publicly in the form of a dashboard that anyone can access. This allows for increased transparency and accountability in the field of health.

One example of a white paper that I could use to share the results of my solution is the "AMR Cross-Sectoral Data Sharing Framework and Roadmap," which was published by the World Health Organization in 2020. This white paper provides a framework for sharing data on antimicrobial resistance across different sectors

My solution will create tangible impact by improving the diagnosis and treatment of diseases, and by reducing the burden of antimicrobial resistance. By analyzing health data, my solution can provide more accurate diagnoses, leading to better health outcomes for individuals. Additionally, by reducing the overuse of antibiotics, my solution can help to prevent the development of drug-resistant bacteria, which can have a significant impact on public health. 

This impact will be particularly important for vulnerable populations, who are often disproportionately affected by infectious diseases and have limited access to high-quality healthcare.
To provide evidence for these outcomes, I plan to track the number of correct diagnoses made using my solution, as well as the number of antibiotic prescriptions that are avoided as a result of my solution.

 We also plan to compare the health outcomes of patients who receive treatment based on my solution with those who receive treatment based on traditional methods. This data will help to quantify the impact of my solution on both individuals and the population as a whole. Additionally, I will conduct interviews with both healthcare providers and patients to understand their experiences using my solution and the impact it has had on their lives.

To scale my solution over the next year, we will focus on three main areas: expanding my dataset, increasing the accuracy of my algorithm, and building partnerships with healthcare providers and institutions. First, we will expand my dataset by partnering with additional healthcare providers and increasing the number of electronic health records I am able to access. 

This will help to increase the accuracy of my results and to provide more comprehensive insights. Second, I will continue to fine-tune my machine learning algorithm to ensure that it is as accurate as possible. Finally, we will work with healthcare providers and institutions to integrate my solution into their systems and processes, which will help to increase adoption and utilization of my solution.

Over the next three years, we will focus on expanding my impact at the national and international levels. we will work to expand my dataset to include data from multiple countries, which will allow me to provide insights that are relevant to a broader range of populations. we will also work to integrate my solution into national and international public health surveillance systems, which will allow for a more comprehensive approach to combating antimicrobial resistance.

To measure success against our impact goals, we will use a combination of quantitative and qualitative metrics. Quantitatively, we will track the number of infections prevented, the number of antibiotic prescriptions avoided, and the amount of healthcare costs saved as a result of my solution. Qualitatively, 

we will collect and analyze feedback from healthcare providers and patients, as well as track the satisfaction of users of my solution. we will also track the amount of engagement with our solution, such as the number of users and the frequency of use. These metrics will help me to understand the success of my solution in achieving my impact goals.

we are currently in the process of piloting our solution, based on our initial testing and feedback, we are confident that it has the potential to make a significant impact on reducing infections and improving the appropriate use of antibiotics. As we continue to gather data, we will be able to more accurately measure the impact of our solution and make adjustments as needed.

There are a few barriers that may impact my ability to achieve my goals in the next year and the next three years. First, there is a lack of access to electronic health records in many developing countries, which can limit the amount of data that I am able to collect and analyze. 

Second, there is a lack of awareness and understanding of antimicrobial resistance among healthcare providers and the general public, which can make it difficult to convince them to adopt my solution. 

Third, there is a lack of funding for research and development in the field of antimicrobial resistance, which can make it difficult to secure the resources needed to scale the solution.

I am applying to the Trinity Challenge because I believe that it is a unique opportunity to receive funding, support, and visibility for my solution. I am facing several barriers in my journey to bring my solution to market, including a lack of funding, limited access to data, and a lack of awareness of my solution among potential users. 

The Trinity Challenge can help me overcome these barriers by providing financial support, access to data, and a platform to share my work with a global audience.

Specifically, the Trinity Challenge can help me to raise the funds I need to develop and scale my solution. The financial support will allow me to hire additional staff, purchase necessary equipment and infrastructure, and cover the costs of ongoing operations. The funding will also allow me to focus on building my solution, rather than on raising money.

In addition, the Trinity Challenge can help me to access data from a variety of sources, which will improve the accuracy and usefulness of my solution. I am especially interested in accessing data from hospitals, research institutions, and government agencies. The Trinity Challenge can also help us raise awareness of my solution among potential users, which will increase its impact.

- The National Institutes of Health, which has a large database of medical research and healthcare data.

- IBM Watson Health, which has expertise in machine learning and natural language processing.

- The Mayo Clinic, which has a large database of patient records and medical research.

- The Stanford Center for Biomedical Informatics Research, which has expertise in data analytics and machine learning.

- The University of Washington's Institute for Health Metrics and Evaluation, which has expertise in health data analysis and modeling.