By Vadeesh Budramane, Founder & CEO, AlgoShack Technologies
Healthcare is becoming increasingly software-defined. Infusion pumps, pacemakers, wearable insulin-delivery systems, diagnostic platforms and hospital information systems now depend on code for functions that directly influence clinical care. These technologies are built on increasingly complex combinations of deterministic software, connected data and AI-enabled decision support. This shift has delivered real clinical benefits, but it has also introduced a new category of risk: the software failure. Unlike a cracked syringe or a mislabeled vial, a software defect can silently affect thousands of devices at once, evade detection until a patient is harmed, and cross borders in the time it takes to push an update.
Regulatory systems are now being updated to address the speed, connectivity and continuous-change characteristics of modern medical-device software.
The scale of the problem
The numbers tell a clear story. Industry recall data indicate that medical device recall activity remained historically elevated in 2024, including a sharp rise in the proportion of the most serious Class I recalls. For the first time in over five years, device failure overtook manufacturing and process-control defects as the leading root cause of these recalls. Software defects specifically now account for roughly 8% of recall events and grew 31% year-over-year, as firmware bugs, algorithm errors, and interface failures are increasingly classified as device failures rather than manufacturing defects.
Government auditors have also raised concerns about how well this is being tracked. A December 2025 GAO review examined 3,934 medical device recall events initiated between fiscal years 2020 and 2024. It found that 74% of recalls reviewed for termination exceeded the FDA’s policy target of terminating a recall within three months after the manufacturer had completed its corrective action. FDA officials cited limited staffing, manual systems and the complexity of modern devices as constraints on recall oversight.
What “growing risk” actually looks like
The abstract statistics map onto concrete, recent incidents:
- Infusion and dialysis systems. In early 2026, a large-volume infusion pump manufacturer issued a software release specifically to fix a defect that could interrupt treatment mid-therapy – the kind of failure that turns a routine infusion into a clinical emergency without any hardware ever malfunctioning.
- Cardiac devices. A pacemaker manufacturer extended a software-related warning tied to battery failures that had already been linked to seven deaths and more than 800 injuries, illustrating how a single defect class can persist across multiple device generations and recall cycles before it’s fully resolved.
- Connected and consumer-adjacent devices. Cybersecurity, not just code correctness, is now part of the failure surface. Power wheelchairs were flagged by US cybersecurity authorities because their Bluetooth connections lacked authentication, meaning anyone within range could potentially take control of the chair – a vulnerability fixed only by disabling connectivity until a patched version could clear regulatory review.
These aren’t edge cases. They reflect a pattern: as more of a device’s function lives in software, more of its risk does too.
Why the risk curve is bending upward
1. Software is doing more, and touching more. Devices that once had fixed, mechanical logic now run adaptive algorithms, connect to hospital networks, and receive over-the-air updates. Every one of those capabilities is also an attack surface or a failure mode that didn’t exist a decade ago.
2. Interoperability multiplies exposure. A single software defect in a widely used platform – an EHR module, a pump firmware library, a cloud analytics service – can propagate across every facility that uses it. Healthcare has already seen how a single vendor’s flawed software update can take down IT systems across an entire health system at once, even when the vendor isn’t a medical device company at all.
3. AI-enabled devices raise the stakes further. Algorithms that learn or update over time don’t fit neatly into a “lock the design, validate it once” regulatory model. Regulators are actively building new frameworks – such as predetermined change control plans – specifically because traditional validation assumes static software.
4. Oversight capacity hasn’t kept pace. Insufficient FDA staffing has been cited as a direct constraint on the agency’s ability to oversee recalls in a timely way, with real effects on how quickly known problems get resolved in the field. When oversight lags the pace of software releases, the gap between “defect introduced” and “defect caught” widens.
5. Detection is actually improving – which raises the visible numbers. The FDA has gotten better at mining post-market data such as adverse event reports to spot performance trends, which means failures that once went unreported are now being caught and classified. Some of the “growth” in software-related recalls is really a growth in the ability to see problems that were always there.
The regulatory response
Regulators are moving, though unevenly:
- Quality system harmonization. In February 2026, the FDA’s Quality System Regulation transitioned to the Quality Management System Regulation, aligning US requirements with the international ISO 13485 standard and shifting inspection focus toward management responsibility and risk-based decision-making. This transition prompted manufacturers and the FDA alike to reassess risk management documentation, which has in some cases surfaced device-level issues that had previously gone unnoticed.
- Earlier public warnings. The programme allows the FDA to communicate potentially high-risk device corrections or removals earlier, before the agency has completed its formal classification process. The intent is to close the gap between “we know something is wrong” and “the public is told.”
- A harder line on cybersecurity. Connected devices are now expected to demonstrate security controls as a condition of clearance, not as an afterthought – a direct response to incidents like unauthenticated Bluetooth access on connected mobility devices.
- International divergence. Outside the US, frameworks like the EU’s Medical Device Regulation and its emerging AI Act are pushing manufacturers toward continuous post-market surveillance and specific controls for adaptive, AI-driven software – adding compliance complexity for any manufacturer operating globally.
Not everyone believes the response is adequate. Critics have pointed to reduced in-person manufacturing inspections and remote-inspection policies as a contributing factor in the broader recall surge, arguing that oversight has not kept pace with either the volume or the complexity of what’s being regulated. That’s a genuinely contested point – regulators and industry groups differ on how much of the increase reflects real risk growth versus improved detection and reporting.
What this means for organizations operating in regulated healthcare
For manufacturers, health systems and health tech vendors, a few implications stand out:
- Design controls have to treat software as a first-class risk category, not a supporting element bolted onto hardware validation. Secure software development lifecycle practices, rigorous verification and validation, and clear traceability from requirement to test case are no longer optional extras.
- Post-market surveillance needs to be continuous, not periodic. With regulators mining adverse event data more aggressively, organizations that aren’t doing the same internally will be the last to know about their own defects.
- Cybersecurity and safety can no longer be managed separately. A vulnerability and a defect increasingly produce the same outcome – patient harm – and should be tracked through the same risk process.
- Recall readiness is a capability, not a document. Given documented delays in regulatory recall processing, organizations that can act fast and communicate clearly on their own initiative are better positioned than those waiting on agency bandwidth.
- Global manufacturers should expect regulatory divergence to continue, not converge, at least in the near term – meaning compliance strategy has to be built to flex across jurisdictions rather than assume one standard will do.
Conclusion
Software failures in healthcare are not a future risk to plan for – they are a present and measurably growing one, driven by the same forces that make modern medical technology powerful: connectivity, adaptability and scale. The organizations that treat software risk with the same rigour traditionally reserved for hardware and pharmaceutical safety will be the ones best positioned as regulators, patients and health systems all demand more accountability for the code running inside the devices that keep people alive.
In our work with medical device and healthcare software teams operating under IEC 62304 and ISO 14971, the challenge is rarely a lack of awareness. It is the operational difficulty of maintaining traceability, validation evidence and release confidence as software changes become more frequent. The organisations that close that gap will not only be better prepared for audits and recalls; they will be better positioned to prevent safety-critical defects from reaching patients in the first place.
Vadeesh Budramane is the Founder and CEO of AlgoShack Technologies, a Bengaluru-based company building AI-Augmented Autonomous Testing platforms for regulated enterprise environments including MedTech and healthcare software.
