Sustainability means making healthcare accessible and affordable to all: SIMATS chancellor

The central message was that healthcare becomes sustainable when it serves people fairly over the long term. N.M. Veeraiyan said this means protecting human life, preserving human dignity, and making quality care accessible and affordable. Sustainability therefore includes social responsibility, not only technology or environmental concerns.

The discussions connected this goal with practical innovation. SIMATS developed an app that helps patients distinguish gastric problems from cardiac problems. Speakers also urged doctors to examine family circumstances, socioeconomic conditions, and the limits of medical data before making treatment decisions.

The current challenge is balancing AI’s power with human care. K. Ganapathy warned against applying Western data uncritically, while Dhanraj Ganapathy highlighted bias, digital hallucinations, and possible threats such as synthetic viruses. The proposed future is collaborative intelligence, where AI supports—not replaces—empathetic professionals.

Healthcare sustainability means building a system that can protect human life and dignity while remaining accessible and affordable. N.M. Veeraiyan presented this as the core meaning of true sustainability at the SIMATS Sustainability Dialogues. The idea places patients and communities at the centre of healthcare planning.

It includes using research to solve practical problems. SIMATS developed an app that helps patients tell possible gastric problems from a cardiac problem. Such work shows how innovation can support earlier decisions and potentially guide people toward appropriate care, while keeping society’s benefit as the research goal.

Sustainability also depends on responsible human judgment. Speakers discussed affordability, family circumstances, compassion, and the risks of biased AI. A sustainable system must therefore combine useful technology with accurate evaluation, ethical behaviour, and care that recognises the patient’s wider human situation.

An app that helps distinguish gastric problems from cardiac problems could improve access by giving patients an initial source of health guidance. It may help them recognise that symptoms commonly interpreted as gastric trouble could require medical attention. This can make healthcare information easier to reach outside a clinic.

The key mechanism is digital decision support. The article says the SIMATS-developed app allows patients to differentiate between gastric issues and a cardiac problem. It does not describe the app’s accuracy, diagnosis process, or clinical outcomes, so it should be understood as a support tool rather than a replacement for doctors.

Its wider importance is affordability and reach. Digital tools can extend useful research to patients who may face barriers to immediate consultation. However, responsible use still requires professional assessment, human judgment, and awareness that technology can have limitations. The article presents the app as part of SIMATS’s goal of benefiting society.

The source article does not state how many people worldwide struggle to obtain healthcare that is both affordable and good quality. Therefore, no exact figure can be taken from the article. The broader issue is central to the event, because N.M. Veeraiyan called for quality healthcare to be accessible and affordable for all.

For context, the WHO and World Bank estimated that about 4.5 billion people lacked full access to essential health services in 2021. This is the closest widely used global measure, but it does not precisely count everyone facing both poor quality and unaffordable care. Different definitions and years produce different totals.

The figure shows why healthcare sustainability matters at global scale. Solutions discussed at SIMATS included socially useful research, digital tools, careful evaluation of AI, and attention to family circumstances. These approaches may support access, but the article does not provide evidence of their worldwide impact or calculate how many people they reach.

Medical AI learns patterns from the information used to train it. If that information is biased, incomplete, or drawn from a different population, the system may produce recommendations that do not fit the patient. Dhanraj Ganapathy described bias and digital hallucinations as important risks, while K. Ganapathy questioned the use of Western data in Indian algorithms.

The mechanism is a mismatch between training data and real-life context. An algorithm may reflect the assumptions, populations, and circumstances represented in its data. It may also generate information that sounds convincing but is wrong. The speakers therefore stressed statistics, careful evaluation, and awareness of AI’s limitations.

The consequences can include poor treatment decisions and reduced trust in healthcare. The article also mentions more serious potential threats, including the creation of synthetic viruses. Responsible human oversight is essential. AI should support doctors, who must consider local conditions, socioeconomic realities, patients, and their families.

Doctors need human judgment because medical decisions involve people, not only measurements. K. Ganapathy said students must understand statistics deeply to evaluate numbers, but he also urged them to treat the entire family. This recognises that illness and treatment affect wider social and economic circumstances.

The key mechanism is contextual decision-making. An AI system may analyse a scan or laboratory result, yet fail to understand whether a family can manage a treatment plan or how its social conditions shape care. Western data may also produce recommendations that are unsuitable for Indian patients. Human clinicians can question outputs and adapt decisions.

This does not make AI useless. The dialogues described AI as powerful but limited, with risks including bias and digital hallucinations. The preferred model is collaborative intelligence. AI can offer analytical support, while doctors contribute responsibility, patience, compassion, ethical reasoning, and knowledge of the patient’s family situation.

A balanced healthcare system begins with clear priorities: protect life, preserve dignity, and make quality care affordable and accessible. These goals define sustainability in the SIMATS discussions. Financial durability matters, but it should serve patients rather than reduce care to costs or technical efficiency.

Practical balance comes from combining tools with human decisions. SIMATS’s app shows how research can offer accessible guidance about gastric and cardiac symptoms. AI can also assist medical work, but doctors must evaluate statistics, question biased data, and consider family and socioeconomic circumstances before choosing treatment.

The future model is collaborative intelligence. Dhanraj Ganapathy said AI’s cold brilliance must be matched by a warm, empathetic human heart. Systems need responsible behaviour, patience, compassion, and ethical safeguards. This approach can help institutions pursue innovation while maintaining trust, widening access, and using resources in ways that support long-term care.