Access Care Navigator

Inspiration

People with disabilities often face additional challenges when trying to access healthcare. Finding a medical provider is already difficult, but finding one that can accommodate specific disabilities, treat a patient's medical conditions, and accept their insurance can make the process even more complicated. Patients often have to spend hours researching different clinics, contacting providers, and figuring out which facilities can actually meet their needs.

We wanted to address this problem by creating a platform that simplifies the entire healthcare search process. Our goal was to use AI to make healthcare more accessible by helping people find providers who understand their individual circumstances and can properly support them.

What It Does

Access Care Navigator is an AI-powered healthcare navigation platform designed to make finding appropriate medical care easier for people with disabilities.

Users can communicate with our AI chatbot through voice or text to explain their disabilities, symptoms, and existing medical conditions. They can also upload medical documents and PDFs to provide additional context about their medical history.

Using this information, the platform searches for nearby medical clinics and evaluates how well each facility can accommodate the user's specific disabilities. It also considers whether the clinic has qualified professionals who can address the user's symptoms or medical conditions and whether the facility accepts their insurance.

Rather than simply providing a list of nearby clinics, Access Care Navigator helps narrow down the options to providers that are actually suitable for each individual. The chatbot can also analyze the information provided, identify potential medical concerns, and offer general guidance and suggestions to help users manage their symptoms while seeking appropriate care.

Once a suitable clinic is identified, the platform confirms the recommendation with the user before proceeding. It can draft and send emails to clinics, assist with appointment scheduling, and even book appointments directly when supported by the provider. If direct booking is unavailable, it guides users to the appropriate website or contact information.

Our goal is to reduce the time, frustration, and uncertainty involved in finding accessible healthcare by allowing users to explain their needs once and letting AI handle much of the research and coordination for them.

How We Built It

We began by identifying a real-world problem and developing an idea for how AI could help address it. After establishing the main features and requirements of our platform, we used Claude as a development assistant to help generate and refine the code.

However, building the platform involved much more than simply asking AI to write code. We spent considerable time planning the functionality, explaining our requirements, testing different features, identifying errors, and repeatedly revising the implementation to match our original vision.

We worked on bringing several interconnected features together, including the voice chatbot, medical document analysis, symptom analysis, disability-specific clinic matching, insurance compatibility, and appointment coordination. Making sure these features worked together properly required multiple rounds of testing and troubleshooting.

Throughout development, we continuously evaluated the results, adjusted our instructions, and worked through problems until the platform better reflected what we wanted to accomplish. It was a process of constant refinement, and each stage helped us improve the overall functionality and user experience.

Challenges We Ran Into

One of our biggest challenges was getting AI to understand exactly what we wanted to build. Since our platform included several different features that needed to work together, giving general instructions often resulted in code that did not fully match our expectations.

We frequently had to go back, explain specific requirements in greater detail, identify what was missing, and request changes. Sometimes fixing one issue created another, which meant we had to repeatedly test different parts of the platform and troubleshoot problems.

Another challenge was making sure that our features worked together as one connected system rather than as separate functions. We had to spend a significant amount of time refining the code and adjusting the implementation to create a more complete experience.

Although the process was sometimes frustrating, it taught us the importance of patience, clear communication, and persistence when developing a complex project.

Accomplishments That We're Proud Of

We are especially proud of turning an idea focused on a real-world accessibility problem into a functioning AI-powered platform. Instead of creating another basic medical chatbot or clinic finder, we wanted to build something that could assist users throughout the entire process of finding appropriate healthcare.

One of our biggest accomplishments was bringing together multiple features into one platform. Access Care Navigator considers a user's medical needs, disabilities, required accommodations, insurance coverage, and location when recommending healthcare providers.

We are also proud of developing a system that goes beyond simply recommending clinics. It can help users understand their potential medical concerns, find suitable professionals, communicate with clinics, and navigate the appointment scheduling process.

Most importantly, we are proud of the amount of effort we put into developing and refining our original idea. We encountered several technical challenges, but we continued testing, troubleshooting, and improving the platform instead of settling for an incomplete first version. Seeing our original concept develop into something that could potentially make a meaningful difference in people's lives has been one of our greatest accomplishments.

What We Learned

One of the biggest things we learned throughout this project is that while AI is a powerful tool that can do a lot of the work, it still requires human guidance. We realized that simply giving AI a general idea of what we wanted was not enough to get the best results.

We had to be specific about our requirements, continuously provide instructions, and make adjustments whenever something did not work as intended. AI does not always recognize its own mistakes or know how to improve something in the way we envision, so it was our responsibility to identify problems, evaluate its results, and guide it toward a better solution.

This taught us that AI works best when combined with human creativity, critical thinking, and problem-solving rather than being relied on to do everything independently.

We also learned more about web development, debugging, integrating different technologies, and the importance of designing technology with accessibility in mind. Most importantly, we learned that technology can be used for more than convenience; it can help address real-world problems and make important services more accessible to people who need them.

What's Next for Access Care Navigator?

We hope to continue expanding and improving Access Care Navigator by increasing the number of medical providers available in its database and improving the accuracy of its recommendations.

In the future, we would like to expand its ability to recognize different disabilities and match users with more specific accommodations. We also want to improve its medical document analysis, integrate with more insurance providers, and make appointment scheduling available through a wider range of clinics.

Another important goal is improving the chatbot's ability to maintain context throughout the user's experience, allowing people to explain their circumstances once without having to repeatedly provide the same information.

Ultimately, we envision Access Care Navigator becoming a reliable healthcare navigation tool that removes unnecessary barriers for people with disabilities. We want to make finding appropriate healthcare less stressful, more efficient, and more accessible so that people can focus less on searching for care and more on receiving it.

Built With

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