Ketaki Muthal has spent more than 18 years working with hospital technology, clinical engineering and medical device development. Throughout her career, she has focused on a practical question: how can technology help clinicians make faster, safer decisions without adding more complexity to their work?
Her experience includes medical device product management, connected monitoring systems, alarm management and international product releases. She has also contributed to patented technology designed to help clinicians identify which patients need attention first by bringing together information from several medical devices.
In this interview, Ketaki Muthal explains why alarm fatigue remains a serious problem, even as hospital technology continues to advance. She discusses the need to design systems around the way clinicians actually work, the challenges of bringing new medical devices through regulatory approval and the role artificial intelligence may play in patient monitoring. She also shares why gradual, carefully tested innovation may be more effective than trying to transform hospital care through one large technological change.
You’ve spent more than 18 years working across clinical engineering, biomedical technology and medical device product management. What hospital problem has most shaped the way you approach innovation?
Clinical engineers uniquely understand hospital goals beyond bedside care – cost efficiency, staffing optimization, patient throughput, sustainability, and revenue performance. While clinicians focus on clinical excellence, it is clinical engineers who deliver the technologies and workflows that enable hospitals to achieve these broader organizational outcomes.
One of the critical metrics hospitals tracks is length of stay.
My approach to innovation is simple and targeted: integrate devices, unlock real‑time data flow, and apply intelligent tools to surface actionable alarms, triage critical patients, direct care where it’s needed, and improve the overall patient stay. The goal is to streamline care, strengthen operational performance, and-when appropriate-shorten length of stay. As organizational priorities evolve, this same engineering approach will extend to additional hospital‑wide goals in the coming phases.
Alarm fatigue remains a serious challenge in high-acuity care. Why has this problem persisted despite major advances in monitoring technology?
Alarm fatigue remains a core point‑of‑care challenge. As new parameters emerge and the number of devices operating in parallel has multiplied, each device generates its own alarms for every parameter it monitors. Device growth has far outpaced alarm‑mitigation strategies, which is why alarm fatigue continues to be a persistent, unresolved burden in critical care.
You developed patented technology for prioritizing and aggregating patient alarms. What gap did you identify, and how does the solution improve clinical decision-making?
Clinicians seldom had an automated way to prioritize patients, and they don’t have the time to manually review each patient one‑by‑one. This forces reactive care for patients who need proactive attention. The patented technology fills that gap by letting clinicians set patient-specific priorities-using presets or customizing them based on condition, parameters, medications, and acuity.
Because clinicians routinely manage 3–7 patients at a time, a single template cannot fit every case. But consolidating the right parameters for each patient enables clear, dynamic prioritization. This directs care where it has the highest clinical impact, reduces overload, mitigates alarm fatigue, and strengthens overall hospital performance.
How can hospitals reduce unnecessary alarms without creating the risk that an important warning is suppressed or overlooked?
Customizing alarms on individual devices is standard practice because OEM thresholds rarely fit every patient. That helps reduce noise at the device level, but modern care now relies on data from multiple devices-monitors, pumps, and other systems operating in parallel. Integrating this information enables proactive alerts, tighter controls for high‑risk patients, and relaxed thresholds for stable ones. It’s challenging, but incremental, intelligent automation is how the industry will absorb innovation while maintaining safe, high‑quality care.
Your work brings together engineering, human factors and clinical workflow design. Why do medical technologies sometimes fail when they don’t account for how clinicians actually work?
Clinical environments are volatile, and human life is always on the line. No medical technology can cover 100% of use cases – and it doesn’t need to. If a solution reliably addresses 80% of real‑world scenarios, it is already delivering meaningful value. Care delivery itself is a creative, adaptive practice that cannot be reduced to rigid templates, and innovation happens at the bedside every day. The goal is to solve the broad, high‑impact problems while leaving room for clinicians to innovate at the edges. Medical technologies don’t “fail”; they simply don’t cover every niche or outlier scenario – and that is exactly where human expertise continues to lead.
You’ve led FDA-cleared technologies and international product releases across several regulatory regions. What are the biggest challenges in bringing a medical device from concept to routine clinical use?
There are multiple reasons. It heavily depends on the scope of the release. Traditional regulatory requirements include design controls and risk management which the manufacturers understand and have incorporated in their processes. Modern FDA expectations-skin‑tone equity, cybersecurity, interoperability, alarm management, software validation, and AI/ML transparency-demand far more rigor than traditional reviews. Every algorithm, code module, or intelligent feature now requires multi‑site validation, and OEMs must run studies across diverse regions under legally binding contracts that take months to negotiate as they are risk‑based. Patient recruitment adds another layer of delay. Combined, these requirements significantly extend development and regulatory timelines.
Artificial intelligence is becoming increasingly important in patient monitoring and clinical decision support. Where do you believe AI can deliver the greatest benefit, and where should healthcare organizations remain cautious?
ML‑driven tools aren’t new in healthcare, but historically they only sampled data and produced estimates. What’s new is the shift toward algorithms that suggest actions and support clinical decisions, not just display information. That level of influence requires time for hospitals to adopt, assess risk, validate outcomes, and build trust. AI clearly has potential, but its true impact will only emerge over time.
Before hospitals implement these tools, FDA evaluates them through a strict, risk‑based lens. Healthcare organizations will adopt AI iteratively small, controlled steps to gain confidence and ensure no unintended clinical harm. Caution is appropriate, and only real‑world experience will reveal both the benefits and the boundaries of AI in care delivery.
Looking ahead, what changes do you expect to see in hospital monitoring, remote care and medical device innovation over the next five years?
Over the next five years, hospital monitoring will shift sharply toward remote monitoring. Critical‑care beds are limited, so patients who are stabilizing will increasingly move to med‑surg floors supported by a mix of in‑person and remote vigilance. This transition will force hospitals to redesign clinical workflows and address ongoing staffing shortages. It will also drive investment in infrastructure that supports remote monitoring and deeper device‑to‑EMR integration, which in turn strengthens billing accuracy and revenue performance.
Clinically, we will see a rise in non‑standard‑of‑care parameters that offer richer insight into patient condition. These emerging parameters will be integrated into monitoring systems to enhance early detection and clinical decision‑making.
Beyond five years, the real question becomes how AI‑driven solutions reshape monitoring. Adoption will be iterative-small, safe steps that build confidence while ensuring no adverse impact on patient care. Continuous improvement will guide where innovation pivots next, but the end goal remains unchanged: safer, smarter, more responsive patient care.
From the editor…
For Ketaki Muthal, the future of hospital technology is not about replacing clinicians or introducing automation for its own sake. It is about giving healthcare teams clearer information, reducing unnecessary distractions and helping them respond sooner when a patient’s condition changes.
That will require better links between medical devices, monitoring platforms and hospital systems. It will also require patience. New tools, particularly those using artificial intelligence, need to be introduced carefully and tested in real clinical settings.
Ketaki Muthal’s message is clear. Progress in healthcare does not always come from a single breakthrough. Often, it comes from smaller improvements that solve real problems, earn the trust of clinicians and gradually lead to safer and more responsive patient care.
