After complicated surgical procedures, patients struggle to understand the exact steps post-surgery, which is often exacerbated in medically underserved and uninsured populations. This prevents quick recoveries, increases the risk of infection, and leads to hospital readmissions which poses a burden many people, especially those in medically underserved communities, can’t afford.

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Right now in medicine, there exists a technique known as the teach-back method that has been proven to enhance patient comprehension by encouraging patients to seek information from their physicians. However, the capacity to efficiently implement this teach-back approach is restricted due to hospital systems usually being overwhelmed.

 

The goal behind Navigo is to analyze electronic health record (EHR) data in order to generate a list of questions tailored to the patients through AI that can be asked to check for patient understanding of post-surgery instructions. Therefore, healthcare providers will be able to look at correct versus incorrect answers to questions from each patient to determine personalized paths to care. Improving patient health literacy and adherence to the provider's instructions promotes a more effective integration of care for the clinical team.