Why Indian healthcare needs a rethink (and how we can fix it)

Trying to do too much under one roof

We talk endlessly about India’s economic growth, our booming startup scene, and our digital public infrastructure. Yet beneath this growth lies a quiet, heavy burden. When a middle-class family faces a major medical crisis like cancer or heart disease, years of savings can vanish in weeks.

For decades, our health debates have focused entirely on financing: asking how to pay the hospital bill, or how to expand insurance. As an early founder looking into healthcare, I have spent time unlearning what I thought I knew, and I have realised we are looking at the wrong problem. India is not just facing a financing crisis; we have a deep structural flaw in how care is delivered.

Walk into any large multi-specialty hospital in Delhi, Mumbai or Bengaluru and you will see an institution trying to be everything to everyone. From a business standpoint this is extremely hard to manage, because general hospitals mix two totally different types of work under one roof.

• Complex investigative care: specialised medical detective work, diagnosing rare or ambiguous conditions. It requires substantial resources and trial-and-error testing.
• Standardised procedures: routine, predictable work like dialysis, knee replacements or cataract surgery. It rewards strict safety rules, high volume and efficiency rather than guesswork.

When hospitals mix complex detective work with routine assembly-line procedures under a massive shared overhead, tracking true value becomes nearly impossible. The system struggles to achieve financial efficiency because it never separates custom care from routine care.

We do not have a diabetes problem. We have a categorisation problem.

This structural bottleneck is clearest in how India manages chronic illness. India is often called the diabetes capital of the world, but the core issue is a failure to properly categorise the disease.

According to the ICMR-INDIAB study published in The Lancet Diabetes & Endocrinology, an estimated 101 million people in India live with diabetes, alongside another 136 million in the pre-diabetes risk zone.

Our current approach treats all of those cases much the same. Take Type II diabetes: we handle it as a single lifestyle condition when, in reality, it is a mix of up to twenty different metabolic disorders that happen to share one symptom, high blood sugar.

Type I diabetes is easier to manage because its cause is clear, which allows rules-based digital and self-care. Type II remains stuck in a cycle of guesswork. Until we can identify the exact biomarkers behind these variations, treatment stays an expensive trial-and-error loop managed by high-priced experts in Tier 1 cities.

The historical lesson for the future

The good news is that we have a historical playbook for fixing this. Over the last century, the cost of treating bacterial and viral illness plummeted because medical progress followed a clear path: stop using vague labels and identify the exact microbe, use standardised tests such as cultures, then develop targeted treatments that kill the pathogen safely.

Consider how tuberculosis was managed a century ago with long, expensive stays in isolated sanitariums. Once the bacterium was isolated, diagnosis shifted from guesswork to precision, and standardised drug regimens moved out of specialised centres and straight into local health posts.

India’s burden of out-of-pocket spending

The macro numbers show why this change is urgent. According to National Health Accounts estimates, the government has increased its share of total health spending to 48%, up from 29% in 2014-15, and out-of-pocket expenditure has fallen from 62.6% to 39.4%. Schemes such as Ayushman Bharat PM-JAY have lowered financial barriers for vulnerable groups.

Even so, an out-of-pocket share of nearly 40% remains a heavy load for middle-class households. When families pay out of pocket, nearly 40 of every 100 rupees spent comes straight from savings. They are forced to sell assets or borrow heavily, not because care is inherently expensive to produce, but because they are paying retail prices for unstructured, trial-and-error medicine at the wrong tier of the system.

Learning from specialised outcomes

To see why traditional setups fail, look at how we consume everyday services. When I book an on-demand cab for an early-morning airport run, I am buying predictability, a zero-cancellation ride that gets me to the terminal on time. The product is a ride; the outcome I am actually buying is peace of mind.

General hospitals try to offer every possible outcome to every patient, which produces a one-size-fits-none result. Contrast that with Narayana Health, which transformed cardiac care by designing pathways around expert teams, standardised protocols and focused execution, dramatically reducing cost while delivering strong clinical outcomes.

Lenskart did something structurally similar in retail, building an end-to-end vertical model with automated factories and precision robotics. By standardising production it cut out retail markups and delivered high-precision eyewear at a fraction of the usual cost.

Healthcare delivery needs this exact shift, away from bloated general complexes and toward focused nodes optimised for specific outcomes.

How AI and technology can unbundle the system

Technology is the tool that lets us unbundle massive hospital systems and move care to the right tier.

• AI diagnostics at the edge: models can screen retinal scans or X-rays with high accuracy at local clinics and pharmacies, removing the need to visit a central hospital for an initial diagnosis.
• Remote monitoring and wearables: connected devices let clinicians track vital metrics at home, catching problems before they become expensive emergencies.
• Affordable molecular sequencing: falling genetic testing costs let us categorise disease precisely, moving conditions like Type II diabetes into targeted, predictable plans.
• Vernacular health LLMs: language models localised for Indian languages can bridge health literacy gaps and act as daily health guides in Tier 2 and Tier 3 cities.

An open question

India’s economic future depends on whether we can move healthcare out of expert guesswork and into standardised, rules-based care.

By embracing AI, molecular diagnostics and digital records, we can unbundle heavy general hospitals and build focused models that match the right care venue to the exact outcome a patient needs. Are we ready to rethink how we deliver care, so that health becomes genuinely affordable for everyone?