Breaking the Silence: Can LLMs based Natural Language Processing Impact Unveiling Care Deserts and Health Inequities?
Can LLMs based NLP tools aid better care coordination and informed decision-making for patients residing in healthcare deserts? How can NLP technologies incorporate cultural sensitivity into healthcare practices while serving diverse, multilingual and underprivileged communities?
Access to quality healthcare is a fundamental right for every individual, yet underprivileged communities and care deserts face significant barriers in obtaining adequate healthcare services. Access to healthcare can be defined as having an adequate supply of services to help people maintain or improve their health. These services span many dimensions of healthcare, including medications, primary care providers, hospitals, emergency services, and community health centers. Access is also affected by socioeconomic factors like affordability, internet access, and health literacy.
Underprivileged communities, often characterized by socioeconomic disadvantage, racial or ethnic disparities, and limited resources, experience higher rates of chronic illnesses, reduced healthcare access, and poorer health outcomes. Similarly, care deserts refer to areas where individuals encounter limited access to healthcare facilities, specialists, and essential services.
