E-Paper
AI can help India move from reactive to preventive health care
This article is authored by Ankit Modi, founding member and chief strategy & growth officer, Qure.ai.
India has never lacked ambition when it comes to health care. Over the past decade, the country has expanded insurance coverage, strengthened disease control programmes, invested in digital health infrastructure and taken diagnostic services closer to communities that had long remained underserved. These efforts have unquestionably improved access. Yet they have also exposed a harder truth: Access alone does not change health outcomes if diseases continue to be detected only after symptoms force patients into health care.
This is the paradox confronting India today. While our health care ecosystem has become better at reaching people, it still remains largely organised around treating illness rather than anticipating it. Whether it is lung cancer or cardiovascular disease, patients often enter the system at a stage when treatment is more complex, outcomes are poorer and the cost of care, both human and economic, is significantly higher. If India is serious about building a preventive health care model, the conversation has to move beyond expanding access to diagnostics. It must focus equally on ensuring that early signs of disease are recognised and acted upon before they become medical emergencies.
India's disease burden illustrates why timing has become one of health care's most pressing challenges. India continues to account for nearly a quarter of the world's tuberculosis cases and, despite a 21% decline in incidence since 2015, remains far from its elimination target. According to the WHO Global Tuberculosis Report 2025, nearly one-third of the world's drug-resistant tuberculosis cases are in India, largely because the disease often goes undetected until it has already spread. The statistic is not simply a measure of prevalence; it is a reminder that delayed diagnosis continues to undermine years of progress in disease control.
The picture is equally concerning in cancer. The Indian Council of Medical Research estimates that annual lung cancer cases among men will rise from around 63,000 in 2015 to more than 81,000 in 2025. Yet only around 3.5% of patients are diagnosed at an early, treatable stage, while five-year survival for Stage IV disease remains close to 10%. Across major cancers, only around 29% of cases in India are detected at an early stage, a rate that remains significantly lower than in countries such as the UK, the US and China. The difference is not that these countries face less disease. It is that they are often able to identify it earlier, when treatment has the greatest chance of success.
Cardiovascular disease tells the same story. Ischaemic heart disease and stroke account for more than 80% of cardiovascular deaths in India, and the country's age-standardised cardiovascular mortality rate of 272 per 100,000 people remains higher than the global average of 235. India has committed to reducing premature mortality from non-communicable diseases by 25%, but that ambition cannot be realised by improving treatment alone. It depends on identifying risk factors and disease progression before they culminate in medical emergencies. Across these conditions, the pattern is remarkably consistent: Health care often intervenes only after valuable time has already been lost.
India's investment in large-scale screening has changed the health care landscape. Programmes such as the National Tuberculosis Elimination Programme, NPCDCS and Ayushman Bharat have expanded the reach of diagnostics well beyond major cities. The question today is no longer whether more people are being screened, but whether the health care system can convert those screenings into timely clinical decisions. That is where preventive health care succeeds, or falls short.
This is where India faces an increasingly significant challenge. Diagnostic infrastructure has expanded, but specialist capacity has not grown at the same pace. Specialist expertise remains concentrated in metropolitan centres, while district hospitals and mobile screening units continue to generate a growing volume of X-rays and CT scans every day. As a result, images often wait for specialist review, delaying referrals, treatment decisions and, ultimately, patient outcomes. Expanding screening without addressing this gap risks creating a system that detects more disease without necessarily treating it earlier.
Artificial Intelligence (AI) has the potential to change what happens between a scan being performed and a patient receiving treatment. Today, chest X-rays and CT scans taken in district hospitals or mobile screening units often wait for specialist review. AI can analyse these images within seconds, flag suspicious findings and help clinicians identify which patients need urgent attention. In doing so, it shortens one of the most critical intervals in the care pathway, the time between detection and clinical action.
Its value lies less in making diagnoses than in improving the speed and consistency with which clinical decisions can be made. The final judgement will always rest with the treating physician, but AI can help ensure that potentially serious cases are recognised earlier rather than remaining buried in growing diagnostic workloads. Evidence from rural India has already shown that AI-assisted interpretation of CT brain scans can accelerate stroke treatment decisions, where every minute influences the likelihood of recovery. Similar advances in tuberculosis and lung cancer screening are helping clinicians identify high-risk patients sooner, making early intervention possible even in settings where specialist expertise is not immediately available.
Moving from reactive to preventive health care will require far more than technology. Technology can accelerate change, but it cannot drive it on its own. Preventive health care will advance only when AI is embedded into everyday clinical practice, supported by clear regulation, interoperable digital systems and the confidence of the clinicians expected to use it. The challenge before India is no longer whether these technologies are capable, but whether the health system is prepared to adopt them at scale.
What India cannot afford, however, is to rely solely on expanding its specialist workforce to close the diagnostic gap. The demand for imaging and early diagnosis is growing far faster than any country can realistically meet through hiring alone. AI offers an opportunity to amplify existing clinical expertise, ensuring that patients are identified and prioritised earlier within the health care system.
Preventive health care is often described as the future of medicine. For India, it is increasingly becoming an economic and public health necessity. If we are to reduce the burden of tuberculosis, improve cancer survival and prevent avoidable deaths from cardiovascular disease, the health care system must begin intervening before illness becomes impossible to ignore. AI, integrated thoughtfully into existing care pathways, can help make that shift possible, not by changing the practice of medicine, but by ensuring that the right clinical decisions are made when they matter most.
(The views expressed are personal)
This article is authored by Ankit Modi, founding member and chief strategy & growth officer, Qure.ai.
