New Delhi, June 3 -- As artificial intelligence (AI) alters how virtually every industry operates, almost nowhere are the risks and rewards as high as in healthcare. Healthcare is unique in how it directly impacts human lives, leaving no room for experimentation. Unlike other areas where engineers have some leeway to fail fast and fix things as they go, healthcare offers no such room for error. The costs of such experiential learning are simply unthinkable!
The massive growth in digitisation and AI has had a disproportionate impact on how technology can determine healthcare outcomes. As a result, healthcare engineers can no longer afford to operate in isolation. The work being done by them is at the front and center of the work being done by healthcare enterprises. Technical excellence alone isn't enough for any AI led development, but more so in the healthcare due to the inherent risks. If healthcare engineers do not take clinical context into account when designing tools or solutions, then they lose an opportunity to create something that can truly make a difference to the outcomes for the industry and patients.
Consider an AI system that's been trained to generate an alert when a patient could potentially go into sepsis. It's a highly sophisticated, accurate system, but generates an alert no different from dozens of other alarms that go off in an ICU setting. Even though this is a critical alert, there is a high probability of it being missed in a high-stress environment where several alarms are constantly going off. While the system works well in a controlled environment, it fails to take into account the real-world setting where it would be deployed where clinicians are under immense pressure and need something distinct that alerts them to a high-priority situation.
As healthcare systems increase their reliance on technology to deliver better patient care, associated outcomes and streamline operating systems, engineers can no longer operate on the periphery of the industry. Understanding the context within which it will be deployed is foundational to designing an effective system or tool. This could mean an understanding of how medicine is practiced in the real world or how care is delivered or recognizing the role technology plays at different stages, as well as the risk factors involved. Healthcare Is Different
Unlike other sectors where technology failures can result in operational disruptions or financial losses, in healthcare, the impact is on human lives. An incorrect software code can result in a misconfigured alert, resulting in treatment delays. Even if the error is noticed, the consequences may not always be easily and entirely reversible.
This ties back in to how engineering decisions should be made. The product design must leave no room for ambiguity, as decisions about performance, automation, and data presentation can influence diagnosis, adoption, treatment pathways, and patient safety.
Technology Alone Is Not Enough
Healthcare systems rarely function in isolation. Beyond technology, they must also be guided by an awareness of how doctors and clinicians function, as well as regulatory requirements and ethical constraints. This is integral, not merely cosmetic to designing a robust system, and these aspects should be a part of the design and development process. Having a technically sound or advanced system counts for nothing if these aspects are not considered. A well-engineered solution which is not designed to seamlessly fit into how a facility operates can disrupt clinical workflows. Likewise, if it's not sensitive to how clinicians operate in the real world, it may introduce cognitive burden which can impair how they act under pressure.
The key lies in optimizing the system for clinical behavior, not just system dynamics. The reality is that clinicians rarely operate in ideal, stress-free environments. Any technological intervention which adds complexity to their normal workflows could result in unforeseen errors, impacted care and an increase in risks.
Clinical Context Shapes Better Engineering
No healthcare engineer will ever be involved in a clinical decision-making process. However, what they do can directly impact this process. Understanding clinical context, thus, helps design better solutions where workflows nudge behavior in the right direction. Data visualization tools, alert systems and product design and interface all have an impact on care pathways.
Once engineers understand clinical workflows, how diagnoses are made and outcomes assessed, there is a shift in how they build products. The focus then is on creating a solution that is technically sound but also optimized to create smoother workflows. This also helps engineers build more stringent safeguards and guardrails to ensure that a misfiring system doesn't have an adverse impact on human lives.
AI Increases the Need for Context
Artificial intelligence is making inroads across different parts of the healthcare industry. AI built into healthcare models can scale decision making, but a flawed assumption or error can then potentially be scaled across thousands of patients or users. If an AI model identifies statistical patterns and triggers an action without domain awareness, these patterns could be misinterpreted or misapplied. Effective AI in healthcare depends on informed human judgement at every stage. Clinical context acts as a safeguard by distinguishing between correlation and causation, between theoretical improvement and practical risk.
Learning Healthcare Is Foundational
Healthcare is a dynamic industry where care pathways, clinical procedures, and compliance requirements are constantly evolving. Healthcare engineers too must continuously learn and remain abreast of changes in clinical guidelines and the regulatory environment in order to create relevant solutions. Learning must become an ongoing endeavor, not a one-off activity.
This also means understanding healthcare beyond medical terminology. It requires a deeper understanding of how clinicians and doctors operate in real-world situations, how different parts of the healthcare system work together, how constraints shape decision-making and how outcomes are defined.
In healthcare, depth of knowledge and experience can be game-changing when designing effective products and solutions. Once engineers start understanding the nuts and bolts of the system, they get better at recognizing possible risks while designing tools and use this judgement to build better products.
Engineering With Responsibility
Unlike several other industries, speed, efficiency or cost savings alone do not define how successful or effective a solution is. While important, these aspects must be evaluated in conjunction with safety, improved patient outcomes and trust.
If clinicians continue to rely on a system even under pressure, it signals that the system is both effective and trusted. Responsibility, too, is essential. When engineers understand the real-world clinical implications of their technical choices, they are better equipped to decide when not to automate a process or when to prioritize explainability over sophistication.
In healthcare engineering, responsibility is not just about innovation, but about enabling better decisions and outcomes. As healthcare becomes more digitised, engineers will play a defining role in shaping the quality of care provided. The Way Forward
The future of healthcare technology will not be defined by tools alone. For healthcare engineers, understanding clinical context is a prerequisite for ensuring relevance, safety, and impact. Designing without being cognizant of how the solution will be deployed in the real world makes it far more likely that it will not find widespread adoption among healthcare practitioners. This then has a clear business impact, in addition to affecting downstream users of the system.
A truly effective healthcare engineer will be someone who can combine technical excellence with clinical awareness to create innovative and effective solutions. The successful firms of the future will be those having engineers who can internalise this and create solutions that reflect this awareness.
Published by HT Digital Content Services with permission from TechCircle.