India’s states are often criticised for chronically underinvesting in health. Yet, Delhi has long stood apart, consistently allocating one of the highest proportions of its budget to the health sector. In the latest state budget, one of the key announcements is the launch of the Advanced Newborn Monitoring for Optimal Lifecare (ANMOL) initiative — a programme that proposes to conduct as many as 56 blood tests on every newborn.
At first glance, this appears to be a bold decision. The proposed panel includes conditions such as congenital hypothyroidism, phenylketonuria, congenital adrenal hyperplasia, G6PD deficiency, galactosemia, biotinidase deficiency, cystic fibrosis, and a range of metabolic and genetic disorders. Several of these tests are clinically justified in well-defined contexts; however, when applied universally and without prioritisation, they raise serious concerns about scientific validity and policy prudence.
The foundational principles of screening are clear and time-tested. A condition should be sufficiently prevalent to justify population-wide testing; its natural history must be well understood; the screening test should be reliable, affordable, and acceptable; and early detection should offer a clear advantage over later diagnosis. Screening in the absence of assured treatment is not prevention — and could be a source of distress.
Assessed against these criteria, the proposal to screen every newborn for 56 conditions appears excessive. Many of the disorders included are exceedingly rare, with incidence rates so low that the cost of identifying a single case becomes disproportionately high. More troubling is the uneven capacity of Delhi’s health system to provide comprehensive and lifelong care for many of these conditions. Diagnosing a rare metabolic disorder in a newborn may be scientifically impressive, but it offers little practical benefit if families cannot access specialised diets, long-term therapies, or genetic counselling.
There are less visible consequences of large screening panels. False positives are an inevitable by-product. When applied to thousands of newborns, even small error rates translate into large numbers of families being subjected to anxiety, repeated testing, and the psychological burden of uncertainty. For the health system, this results in additional costs, increased workload, and the diversion of scarce resources from more pressing priorities.
Equally relevant is the signalling effect of such a policy. When the government of the national capital territory endorses an extensive panel of tests as part of routine newborn care, it implicitly communicates that all these tests are essential. The private health care market, highly responsive to both policy signals and consumer anxieties, is likely to amplify this trend. Hospitals and diagnostic centres may begin routinely offering similar panels, thereby increasing the cost of deliveries and newborn care without commensurate health benefits. In a country where households already bear a substantial share of health care expenditure, this cascading effect could deepen financial vulnerability under the guise of preventive care.
This pattern is not without precedent. The ongoing policy discourse in India around universal lipid screening for children at ages seven and 17 offers a useful parallel. Advocates argue that early identification of dyslipidaemia can help prevent cardiovascular disease later in life. There is some merit in this argument, particularly for detecting familial hypercholesterolaemia, where early intervention can indeed be life-saving. However, extending this approach to universal screening remains contentious. Lipid levels in children are dynamic, influenced by growth, diet, and hormonal changes, and their ability to predict adult disease is far from definitive. Labelling large numbers of children as “at risk” risks medicalising normal biological variation, leading to unnecessary follow-up tests and, in some cases, premature pharmacological interventions.
The growing use of advanced lipid markers, such as lipoprotein(a) and apolipoprotein A, further illustrates the slippery slope of over-testing. While these bio-markers have a role in specific clinical situations, their repeated use in the general population is not supported by strong evidence. Yet, once introduced into clinical practice, such tests tend to proliferate — driven by a combination of clinical uncertainty, patient expectations, and commercial incentives. The proposed screening policy risks triggering a similar cascade, normalising the idea that more testing automatically translates into better care.
This is not to suggest that newborn screening should be abandoned. On the contrary, targeted newborn screening programmes have been among the most successful public health interventions globally. Early detection of conditions such as congenital hypothyroidism and phenylketonuria has prevented severe disability and transformed countless lives. India would benefit from strengthening and expanding such focused programmes, ensuring high coverage, quality assurance, and strong linkage to treatment and follow-up care. The real question is how much to screen, for whom, and with what purpose.
A more rational approach would ground screening decisions in epidemiological relevance, feasibility of treatment, and health system capacity. Risk stratification — based on family history, regional disease patterns, and clinical indicators — offers a more nuanced and effective pathway than blanket testing. Equally important is transparency. Policymakers must clearly articulate the evidence supporting each test, along with its expected benefits, potential harms, and cost implications. Public health interventions derive legitimacy not from their scale, but from their scientific integrity and ethical soundness.
There remains an opportunity to recalibrate. As the operational guidelines for the ANMOL initiative are developed, they can incorporate a more discerning and evidence-based framework — prioritising essential tests, linking screening to assured treatment pathways, and avoiding unnecessary expansion. Resources thus saved could be redirected towards strengthening neonatal care systems, improving follow-up mechanisms, and supporting families of affected children. In the final analysis, good policy is not defined by how much it does, but by how wisely — and how judiciously — it chooses to act.
Chandrakant Lahariya is a practicing cardio-metabolic physician, health policy expert and specialist in parenting and child development. The views expressed are personal
