Inclusive Development Through AI: Enhancing Healthcare Access for the Disabled with Large Language Models

Abstract

People with disabilities(PwDs) are often faced with barriers that contribute to their inability to access healthcare services. This directly translates to a deepened sense of inequality for people who fall within this demographic. It’s imperative to provide equitable protective measures in the health care system, especially in regards to areas such as communication, treatment, and diagnosis. New technologies, including Large Language Models (LLMs) like OpenAI, GPT-4, promise to eliminate many of these barriers to provide enhanced articulation of health symptoms and accurate responses to medical queries. This research proposes the first known initiative to incorporate LLMs into existing telemedicine systems. The goal is to improve the initial symptomatic assessment process and provide inital diagnoses that can be followed by triage to the appropriate medical professional. The improvements are called the Telemedicine Triage Module that works like a chatbot which can describe the patient’s symptoms as well as their past medical history, enabling a more effective discussion during the consultation. Some of the additional enhancements target broader public needs, like multilingual use, prioritization based on the urgency, and self-adjusting algorithms to improve accuracy over time. A practical example and pseudocode illustrate how these systems can support effective telemedicine for many people. Solving systemic problems, this study builds the foundation of the first truly AI-powered, inclusive healthcare system. This allows people with disabilities to receive faster, more specialized, and more accurate treatment without being limited by a language barrier or geographic location.