If you’re a medical device developer, you need to understand how AI may impact your next product design. There’s a good chance your competitors already do.
Artificial intelligence is impacting every industry, including healthcare. And as a technical leader charged with bringing new medical devices and products to market, you need to get ready for the inevitable disruption that’s coming your way.
This might feel overwhelming given that you develop products for a highly regulated, risk-averse field. Data privacy and security are real concerns — as is liability. And AI platforms will need to address any systemic shortcomings in these areas before widespread adoption will be possible.
Beyond that, you may simply feel dubious about how much AI will truly affect your product development roadmap. After all, “game-changing innovation” has been widely touted before and hasn’t always lived up to the hype (we’re looking at you, IBM Watson 1.0).
But the reality of AI is different today than it was in years past, and you can’t afford to adopt a wait-and-see approach. To put it bluntly, if you don’t figure out how to harness AI’s power to cut costs and improve the patient experience now, your competitors will.
To help you get ahead, we’ve identified three areas where we see the potential for AI to revolutionize healthcare. As you review each one, consider the products you could create or redesign to get your company into the AI game.
As staffing shortages make it increasingly difficult for healthcare organizations to keep up with the demand for services, products that improve efficiency will become more and more attractive to your customers.
AI is already capable of reducing the level of skill and time required to perform routine (but time-consuming) administrative tasks, and its functionality will only get better as the technology evolves. That means the sky’s the limit for developing innovative new solutions that will free healthcare workers up to focus on patient-facing activities.
Doctors and nurses spend a significant amount of time taking or reviewing patients’ medical histories. With the right tools, medical personnel could use AI-powered software to record and transcribe conversations with patients and then transfer that information to an electronic record.
AI tools could also review patient files prior to a visit and generate a summary to elevate causes for concern. This would potentially mitigate the risk of doctors and nurses missing any critical details — while simultaneously enabling them to see more patients in the course of a day.
Regulatory, legal, and insurance coverage documents are structured to be comprehensive, but they’re certainly not designed for ease of use.
Generative AI like ChatGPT, Bing, and Bard are able to quickly consume dense, jargon-heavy, and difficult-to-read documents and distill the key takeaways. As such, they could help providers stay compliant and locate answers to urgent questions more quickly.
However, it’s important to emphasize that these tools are not HIPAA compliant, nor are they secure. Providers must not use these open-AI tools in conjunction with proprietary data.
AI’s usefulness goes beyond simply reducing the paperwork providers deal with. It also has the potential to become an invaluable tool in prevention, diagnosis, and treatment. And though qualified humans will need to double-check AI’s recommendations and findings, AI’s ability to interpret data far exceeds the average human’s. That means in many cases it could perform better than providers can and greatly improve patient outcomes as a result.
We see the potential to put AI to work in the following ways:
When integrated with robotics and automation, AI-infused equipment could perform patient imaging independently and then analyze the results to identify areas for further review (e.g. breaks, fractures, tumors, cancer). Of course, even without the robotic aspect, AI could be used to screen images from X-rays, CT scans, and MRIs and flag potential problems.
If combined with some sort of AR technology, doctors could also contextualize necessary procedures through an overlay of a patient’s unique anatomy.
As data is entered into patients’ medical records over time — e.g. vitals, test results, family history — AI will be able to analyze the results and identify trends/patterns to:
This would require a large set of digitized, anonymized records to group individuals into similar risk groups. The most effective technologies would base future prognosis modeling on documented progressions in similar individuals.
We also predict that doctors could begin relying on AI to quickly analyze patients’ symptoms, family history, and medical data to diagnose a variety of conditions. This will be particularly helpful when a patient presents with tricky symptoms for which an obvious diagnosis is elusive. Because AI can crawl large databases quickly, it will reduce the time it takes to find answers and begin appropriate treatments.
Furthermore, in critical care scenarios, AI could be used to monitor patient vitals and compare data to historical records of other patients in similar situations. Again, using predictive modeling, AI could then alert medical personnel to the eventuality of a heart attack or other serious event minutes before it happens.
And of course, there are already a number of smart devices on the market (e.g. knee and hip implants) that monitor patients’ activity and provide data that doctors can use to track progress and address concerns.
The healthcare industry is in an arms race toward using robotics to automate surgical procedures. AI integration could round out these emerging capabilities by providing real-time analysis, thereby allowing providers to monitor and mitigate risk. Many companies have already begun building robotic operating room assistants, and adding AI will be a natural next step.
Accessing healthcare can be intimidating for many patients. AI has the potential to remove (or at least reduce) the barrier to care by providing consumers with self-service options.
A sophisticated AI-powered self-service portal could function like WebMD’s symptom checker, but in a more tailored and accurate way. For instance, if the AI tool had the capability to connect to the patient’s healthcare portal, it could obtain a big-picture view of a patient’s health history and offer personalized courses of action. (Of course, AI-related privacy and security concerns must again be addressed. For example, the patient might be required to opt-in or sign a waiver to utilize this technology.)
A robust AI tool like this could:
For example, say a patient learns she is at risk for Type 2 diabetes. Her doctor tells her she should make dietary changes and begin an exercise regimen. An AI tool could supplement that advice with cold, hard facts, like:
Quantifying each patient’s unique health situation using actual data and predictive modeling just might motivate individuals to take actions they otherwise would not. And in turn, this has the potential to significantly decrease the costs associated with treating lifestyle-induced conditions.
AI isn’t just another fad, and there’s no doubt it will change the medical profession in ways we haven’t even imagined. The only real question is this: Will your company boldly lead the way as healthcare technology and products evolve? Or will you wait and see what happens — and watch opportunity pass you by?
Infusing your product development roadmap with the power of AI doesn’t mean you have to start from scratch with a brand-new product idea. (Although hey, if you do come up with a revolutionary concept, now’s an ideal time to jump on it.)
Rather, look at what you do well now. Think through the possibilities and opportunities AI brings to the table. Then, look for ways to merge them together. By putting building blocks in place now, you can ensure your business is at the forefront of the upcoming AI revolution.