Strategic Integration of Generative AI in Telehealth: Enhancing Equity and Access in Australia and India

Project description

This project explores the transformative potential of generative AI, particularly large language models (LLMs), in enhancing telehealth services to improve accessibility and healthcare equity in regional and remote areas of Australia and India. Generative AI technologies such as LLMs are revolutionizing numerous sectors, and their integration into telehealth can potentially enhance diagnostic accuracy, patient engagement, and overall healthcare outcomes.
However, the adoption of these technologies raises significant governance, legal, and ethical implications that need to be rigorously examined and addressed. Ensuring patient data privacy, managing AI-driven decision-making accountability, and developing ethical frameworks to prevent biases and ensure fair access are critical aspects of this project. By investigating these issues, the project aims to provide a comprehensive understanding of the safe, responsible, and effective integration of LLMs into telehealth services, ensuring that technological advancements translate into tangible benefits for healthcare delivery in underserved regions.
The project will investigate the capabilities of LLMs within telehealth, focusing on quality, safety, and regulatory needs, and engage with healthcare providers and patients in both Australia and India to gather insights on the use and acceptance of LLMs. Educational materials will be developed to enhance understanding and facilitate the safe use of LLMs, fostering mutual learning and collaboration between the two countries.
The research will also develop guidelines and frameworks to address ethical, privacy, and governance issues associated with LLM use in telehealth and implement and evaluate pilot projects showcasing LLM-enhanced telehealth solutions. This includes evaluating the current state of telehealth and the potential for integrating LLMs in rural and remote areas, conducting interviews and focus groups with healthcare providers and patients, performing detailed case studies of existing GenAI telehealth applications, and implementing and assessing LLM-enhanced telehealth solutions through demonstration projects.
By partnering with health services and telehealth startups, the project aims to harness the similarities in healthcare challenges and solutions while addressing unique aspects specific to each country to enhance the overall effectiveness and impact of telehealth services.

Outcomes

1. LLM Integration Analysis: Analysis of LLM integration into telehealth services to enhance accessibility and healthcare equity in remote areas.
2. Ethical and Governance Frameworks: Review and recommendations of ethical, privacy, and governance frameworks for the responsible use of LLMs in telehealth.
3. Stakeholder Engagement Report: Insights from healthcare providers and patients in both countries on the acceptance and use of LLMs in telehealth.
4. Educational Resources: Creation of materials to facilitate understanding and safe use of LLMs in telehealth.
5. System Dynamics Modelling: Development of system dynamics models to understand and predict the impact of LLM integration on telehealth services in rural and remote areas.
6. Policy Recommendations: Recommendations for industry stakeholders and policymakers on integrating LLMs into telehealth services effectively and responsibly.
7. Case Study Documentation: Documentation of case studies on existing generative AI telehealth applications, highlighting success factors and challenges.
8. Interdisciplinary Collaboration Network: Establishment of a network with health services, health networks, and telehealth startups to support ongoing research and implementation.
9. Conference Presentations and Publications: Dissemination of findings through conference presentations and peer-reviewed publications to contribute to the academic and professional discourse on telehealth and generative AI.

Essential capabilities

High proficiency in English language (reading and writing), evidence of previous experience, field work and published conference papers preferred.

Desireable capabilities

Strategy, healthcare and Digital Technologies domain knowledge

Expected qualifications (Course/Degrees etc.)

Bachelor’s degree (honours) with a first class or Masters degree with a research study.