Three key questions about how AI will augment the patient experience

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In just a few weeks, moviegoers will once again be terrorized by xenomorphic aliens as a new entry in the Alien series hits theaters. So much of the memorable menace of these films are the aliens, but the skepticism related to the franchise’s artificially intelligent characters may be more relatable. Nearly every alien movie has an artificially intelligent character—and much of the time, those characters, not the aliens, are the certifiable villains.

Bottom line: people are skeptical of artificial intelligence, and while we’re openly inviting smart-everything into our homes, we’re still not sure about how actual AI is going to affect our lives in practice. Luminaries from Musk to Ripley are constantly suggesting caution, and much of the technology is still in its infancy.

In healthcare, there is much talk of how AI is going to revolutionize the entire industry. Big ideas include things like more precise diagnosis cancer, AI health assistants that lock onto individual patients’ needs at the genetic level, and new medicines and treatments that are tailored to individuals.

Until robotics catches up with AI, it isn’t likely that you’ll see ACLS certification for robo-nurses as they roll around the ER floor. Nor is it likely that these technologies will mature fast enough for the everyday healthcare consumer to have direct access to them in most patient experiences in the near future.



So what do we need to know and get ready for today?

1) When it will affect patient experience?

Most forecasts say that 2030 is about the time that full-on AI will develop. However, it has been pointed out that this intelligence isn’t going to be android-like in nature. It will remain specialized. A given AI system might be really great at analyzing patient pulmonary data to spot early-stage heart problems. But it won’t be able to read patient genomes and identify cancer markers—that’ll be a different AI from a different company.

So, no need to fear. In a little over a decade, we’ll probably see AI powering some hospital and patient interactions, but it won’t be a Singularity-level occurrence just yet.

2) Where it will impact experience?

Patient experience has been intersecting with technology for decades, particularly in hospitals. Bed-side computer systems and monitors linked into hospital wing IT architecture are completely standard. Over time, these systems have been streamlined down to a few fairly innocuous machines, serving their data to a centralized screen at the nurse station.

Hospital systems and medical practices are most prone to adopt systems that build efficiencies—so we can expect AI to work in the background of the patient lifecycle. Efficiency in terms of knowing when to queue a nurse to visit based on real-time data (no reason to visit—then don’t), and clinical assistance (“hello, I’m your AI and here are five treatment options it might have taken you three hours to fully research”) are the name of the game.

3) What will the impact on medical professionals be?



It’s tempting to jump straight to patient impact, but AI’s effect on medical professionals is actually more important. AI will certainly make processes and data more efficient and accurate, and that in turn should improve patient outcomes and experiences in terms of speed of healthcare delivery.

But, it won’t mitigate the need for well trained professionals. Ultimately, the most radical result on healthcare professionals may be a dramatic shift in the medical community’s attitude toward training and education. If you are an encologist, how much more streamlined might your training and practice be if AI can assist you in genome interpretation, diagnoses and information gathering about uncommon cancer types? You may be able to get through residency sooner, and other practitioners like physicians assistants may be empowered to do more than they could previously with AI-augmented databases and decision-making tools.

Certainly, more questions will develop as AI matures and becomes more readily available. But for now, these questions are key. It will be fascinating to see them answered by the innumerable medical AI startups and established companies in the coming years.

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