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How ChatGPT 4 can be used to transform the healthcare industry

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By Shikha Pillai, Member – Healthcare Working Group, IET Future Tech Panel

Generative AI and Large Language Models (LLMs) like ChatGPT 4 have taken the world by storm and are leading the way for an unprecedented pace of innovation, across industries. The Artificial Intelligence (AI) opportunity in Healthcare is already well established and Generative AI is expected to have a transformative impact in the next years.

Several prospects lie ahead for LLMs to bring about better patient outcomes and experience, augment the capabilities of healthcare professionals, drive efficiencies in processes and workflows, and make healthcare more accessible and affordable for everyone.

LLMs can handle large datasets from diverse sources such as medical imaging, lab, genetic information, wearables, lifestyle factors etc., understand context and perform faster analysis with a higher degree of accuracy. This will enable better detection of anomalies and abnormalities, and more accurate diagnosis and personalized treatment plans. These models can simulate virtual environments that will help in the prediction of outcomes such as disease progression, patient response to different treatment options and thereby help healthcare professionals make informed decisions for individual patients.

In recent years, we have seen an increase in telehealth and remote patient monitoring. However, this comes with the challenge of making sense of large amounts of data that is collected from various health monitoring devices. LLMs can help streamline this and generate actionable insights within a shorter span of time, enabling timely intervention based on early warning signs. This will also reduce the need for in-person consultations and hospitalization: a key benefit for those who live in rural and remote areas.

Skill shortage is a major challenge in Healthcare and the World Health Organization has projected a shortage of 10 million healthcare workers by 2030. Generative AI-based assistants can support clinical decision making and take over routine administrative activities. This will optimize the time spent by healthcare professionals, allowing them to focus on better patient care and reduce stress/burnout. Models like ChatGPT also have promising applications in healthcare education. The access to medical knowledge and vast research, capabilities for assessment and feedback, and the interactive experience through these models can accelerate learning in a safe and controlled environment. Digital training offers the benefit of scale and deploying Generative AI models have potential to address capability gaps in the sector worldwide.

Patient engagement is key to the overall experience of care today. Personal treatment of patients and families, effective communication and education are must-haves for positive experience. The natural language processing capabilities of LLMs, when integrated into patient communication channels through chatbots/assistants, can enable a continuous and personalized interaction. Patients can pose questions and concerns to an AI chatbot and experience an interaction that is human-like. Updates, guidance, and support especially during complex procedures can be made accessible through the assistant, and this would help to alleviate anxieties of patients and their families. Behavioural data can also be analysed to identify risks and offer interventions for patients managing chronic conditions.

In addition to the benefits to patients and healthcare professionals/providers, ChatGPT 4 like models can bring in operational effectiveness as well. The Indian health system is undergoing transformation, enabled by the fast-growing digital ecosystem, investments into expanding connectivity, openness towards technology adoption, and focus on affordable innovations. Ongoing efforts for digitalization and automation are already contributing to improvements in accessibility, affordability and quality. Generative AI “co-pilots” can model complexities in the system, bring context-specific improvements in processes, run standardized workflows and routine activities to drive efficiencies.

The pandemic exposed the fragility of the health system, not just in India but across the world. With increased disease burden, rising costs, staff and skill shortage, there is a strong need for technology-led advancements. The promise of Generative AI and LLMs is very high however it will take time to use them in standard medical care. We need to evaluate all models thoroughly and develop approaches to demonstrate the value to healthcare, especially given that creation and maintenance of these will be expensive. There are several challenges and risks such as lack of interoperability, bias due to incomplete/inaccurate data, potential misuse, concerns from handling of patient data and consent, gaps in compliance with regulatory standards, vulnerability to security breaches etc. Therefore, it is important to ensure that these models are developed and deployed in an ethical and responsible manner to protect patient privacy and ensure safety.

Looking ahead, the integration of LLMs like ChatGPT 4 into the pursuit of clinical excellence, standardization, digitalization and improvement of patient experience, will enable the significant shift in healthcare and enabling health equity for everyone in the world.

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