In a village clinic in central Kerala, a community health worker once told me about a fancy new diagnostic device that arrived with great fanfare. It could measure a dozen vital signs in seconds, connect to a smartphone, and upload data to a cloud server. The problem? The nearest reliable internet connection was two kilometres away, the device needed daily charging when power cuts lasted eight hours, and nobody had trained the auxiliary nurse on how to interpret the numbers it spat out. Within three months, the device sat in a cupboard, wrapped in its original plastic, while the health worker continued using a manual blood pressure cuff and a thermometer that had served the community for years.
I think about that cupboard often. Not because I oppose innovation — I am a public health researcher who has spent years studying how tools and systems can improve lives — but because it reminds me that technology, on its own, is never the answer. The assumption that a newer gadget, a smarter app, or an algorithm-driven platform will automatically make people healthier is not just naive; it can actively cause harm. It diverts money from what works, erodes trust in simpler systems, and widens the gap between those who can access digital solutions and those who cannot.
The Seduction of the Shiny Object
Health systems around the world, including India’s, are under immense pressure. Public budgets are tight, the burden of both infectious and chronic diseases is rising, and the workforce is stretched thin. In this climate, technology often arrives dressed as a saviour. A pilot project introduces tablet-based screening in urban slums. A hospital chain advertises robotic surgery suites. A start-up pitches an AI-driven chatbot for mental health counselling. The message is consistent: technology will leapfrog the messy, slow, human-dependent processes of the past.
There is a term for this: technological solutionism. It is the belief that for every complex social or health problem, there exists a neat technological fix. The trouble is that health is not a broken machine waiting for a better spanner. It is shaped by income, housing, nutrition, discrimination, social support, and a thousand other factors that no app can code away. When we invest in a device without investing in the conditions that make it usable — trained staff, reliable electricity, linguistic accessibility, community trust — we are not solving a problem. We are decorating it.
When Data Becomes a Burden
Consider the explosion of wearable health monitors. Step counters, sleep trackers, continuous glucose monitors — they promise to put individuals in charge of their own wellbeing. For a certain segment of the population, they may nudge behaviour in positive ways. But for many others, especially those already navigating chronic illness or health anxiety, constant self-tracking can become a source of stress rather than empowerment. A 2022 study in the Journal of Medical Internet Research found that while wearables can modestly increase physical activity, the effect diminishes over time, and there is little evidence they produce lasting health improvements for people with low baseline motivation or limited health literacy.
In clinical settings, the data deluge is even more problematic. Electronic health records were meant to smooth out care, yet studies show that physicians in highly digitised systems now spend nearly half their working hours on data entry. The screen has become a barrier between doctor and patient, not a bridge. In India, where doctor-patient ratios are already abysmal — roughly one doctor per 1,500 people against the WHO recommendation of one per 1,000 — every minute spent clicking checkboxes is a minute lost to listening, examining, and thinking.
This is not a Luddite argument. It is an evidence-informed caution. The question should never be “Is this technology impressive?” but “Does this technology improve outcomes for the people it is meant to serve, in the context where it will actually be used?”
The Evidence Gap
Here is a sobering fact: the vast majority of digital health tools have never been tested in rigorous, independent trials. A systematic review published in npj Digital Medicine in 2023 examined over 1,300 digital health apps and found that fewer than 100 had any published clinical evidence supporting their claims. Among those that did, the quality of evidence was often low — small sample sizes, short follow-up periods, and conflict of interest from developers funding the research.
Even when evidence exists, it is rarely generalisable. A telemedicine platform that works in a controlled trial in Bengaluru, with stable broadband and English-speaking participants, may fail completely in a tribal block of Odisha where the primary language is Kui and internet access is sporadic. Yet the narrative around technology rarely makes room for such nuance. Instead, success stories are amplified, failures are quietly shelved, and the cupboard of abandoned devices grows fuller.
I have seen this pattern repeat across maternal health, tuberculosis care, and mental health programmes. In one district, a mobile app for tracking high-risk pregnancies was introduced with enthusiasm. The frontline workers, mostly women from the communities they served, were given smartphones and asked to enter data during home visits. What the programme designers failed to account for was that many of these workers had never used a touchscreen device, felt awkward pulling out a phone in homes where no one owned one, and found the app’s interface confusing. The result was not better tracking of high-risk pregnancies; it was duplicate work, as the workers continued their paper registers alongside the app, and a simmering resentment toward a tool that made their jobs harder.
Technology and Health Equity
The digital divide is not just about who owns a smartphone. It is about who designs the tools, who decides what problems are worth solving, and who bears the cost when the tools fail. In global health, there is a long history of technologies being parachuted into low-resource settings with the best of intentions — and the worst of outcomes. The PlayPump, a children’s merry-go-round that pumped water while kids played, was celebrated by donors and development agencies before it was discovered that the pumps required constant spinning to produce minimal water, broke down frequently, and were less efficient than standard hand pumps. Communities ended up paying to have them removed.
In health, the equivalent might be a sophisticated telehealth kiosk placed in a primary health centre that has no doctor to staff it. Or an algorithm trained on data from white, affluent populations that performs poorly when applied to Indian patients. Bias in medical technology is well documented: pulse oximeters that overestimate oxygen levels in darker-skinned patients, diagnostic AI systems that fail on non-Western disease presentations, and genetic risk scores that are useless outside the populations they were developed on. When we rush to adopt technology without testing it in the communities it is meant to serve, we risk not just wasting money but actively worsening disparities.
This is not a hypothetical concern. During the COVID-19 pandemic, India’s vaccine registration platform, CoWIN, was hailed as a digital triumph. But for millions of elderly people without smartphones, for those who did not speak the interface languages, and for those in areas with network dead zones, it became a barrier to accessing a lifesaving intervention. Technology created a new layer of exclusion precisely when inclusion mattered most.
What Should We Ask Instead?
If the goal is better health, not just more technology, then the questions we ask must change. Before adopting any new tool, health systems and communities should demand answers to a few uncomfortable but essential questions.
Who does this technology leave out? If a tool requires literacy, internet, electricity, or a certain level of income, it will exclude those without these resources. In India, that is still a significant portion of the population — particularly women, rural residents, the elderly, and Scheduled Tribe communities.
What problem are we actually solving? A common mistake is to start with the technology and then search for a problem it can solve. Instead, we should start with the health need — say, reducing maternal anaemia — and then ask what mix of interventions, which may or may not include a digital component, is most likely to address it.
Has this been tested in a setting like ours? Evidence from a private hospital in a metro city does not translate to a public facility in a remote block. Local validation, ideally through community-partnered research, is essential.
Who will maintain it? Technology is not a one-time purchase. It requires updates, repairs, training, and ongoing support. If the budget does not include these recurring costs, the device will end up in the cupboard.
Does it strengthen or undermine human relationships? Health is relational. It happens between a patient and a provider, a family and a community health worker, a mother and the nurse who remembers her child’s name. Technology should support these relationships, not replace or disrupt them.
The Middle Path
None of this is to say that technology has no role in health. It absolutely does. Vaccines are technology. So are clean water systems, diagnostic laboratories, and SMS appointment reminders. The point is not to reject innovation but to demand a more mature conversation about it — one that respects complexity, centres equity, and remembers that the most profound health gains in history came not from gadgets but from sanitation, nutrition, education, and social justice.
In my own work with community health programmes, I have seen technology used beautifully when it is designed with, not for, the people it serves. In a tribal health project in the Nilgiris, community health workers co-designed a simple audio-based tool in their own language to track child immunisations. No screens, no typing — just a voice interface that spoke Kurumba and allowed workers to record information verbally during home visits. The tool was built on a platform that worked offline and synced data when the worker returned to a network area. It succeeded not because it was advanced but because it was appropriate.
Appropriateness is an underrated virtue in health technology. It asks us to consider the whole picture — the social, cultural, economic, and infrastructural context — rather than just the technical specifications. An appropriate technology may be less glamorous than the latest AI-powered device, but it is far more likely to improve lives.
A Caution for the Future
As India pushes forward with its Ayushman Bharat Digital Mission and other health technology initiatives, the stakes are high. The mission aims to create a national digital health ecosystem, with unique health IDs, interoperable records, and a host of digital services. In principle, this could reduce fragmentation and improve continuity of care. In practice, it will only work if the implementation is grounded in the reality of India’s health system — its workforce shortages, its linguistic diversity, its patchy infrastructure, and its deep inequities.
I worry when I hear policymakers speak of technology as if it were an end in itself. I worry when I see budgets for health worker training cut while spending on digital platforms rises. I worry when communities are treated as passive recipients of innovation rather than as active participants in shaping their own health futures.
The cupboard in that Kerala clinic is not an isolated story. It is a warning. Every abandoned device represents a failure of imagination — the failure to imagine that the best solution might be simpler, cheaper, and more human than the one that came in a sleek box. As we navigate the next wave of health technology, let us carry that warning with us. The goal is not more technology. The goal is better health, for everyone, on terms that respect their dignity and their reality.
Frequently Asked Questions
Does technology ever improve health outcomes?
Yes, but the improvement depends on the context. Technologies that are designed collaboratively, tested locally, and supported with training and infrastructure can make a real difference. Simple tools like SMS reminders for medication adherence or point-of-care diagnostic tests have strong evidence behind them. The key is to evaluate each technology on its merits, not to assume that newer or more complex automatically means better.
Why do so many digital health projects fail?
Many fail because they are designed without deep understanding of the end user’s environment. Common reasons include lack of reliable electricity or internet, insufficient training, language barriers, high maintenance costs, and a mismatch between the problem the technology addresses and the actual needs of the community. When projects are driven by donor enthusiasm or market pressures rather than community demand, failure is almost guaranteed.
How can communities influence the way technology is used in their health services?
Communities can demand a seat at the table when decisions are made about health technology. This might mean participating in needs assessments, giving feedback during pilot phases, or advocating through local governance structures like panchayats and health committees. When health workers and patients are treated as partners in design, the resulting tools are more likely to be useful, used, and sustained.
What is an example of appropriate health technology in India?
One strong example is the use of portable ultrasound devices in remote antenatal care, paired with training for midwives and clear referral pathways. These devices have helped detect high-risk conditions earlier in areas where women previously had to travel hours for a scan. The technology works because it fits the reality of the setting — it is portable, battery-operated, and supported by ongoing mentorship, not just a one-time training session.