You: “Oh great, another buzzword.”
The Industry: “Yeah you’re right :)”
It’s a buzzword that describes all that’s going on with artificial intelligence in healthcare.
More specifically, the fact that everyone is trying to use AI for everything all at once.
See any problems with this?
Here’s a big one: AI isn’t the solution to every problem in existence.
Historically, two things have happened any time a revolutionary technology has reached the public:
- We thought it was going to solve all of our problems.
- We panicked that it was going to take all of our jobs.
Yet, neither of those things has ever come true.
That doesn’t mean AI won’t change the world – it certainly will.
It will replace millions of jobs, even in healthcare, but it will create millions more.
However, it probably won’t happen in the way you’re thinking.
Sure, highly-repetitive jobs like checking out at a grocery store will get replaced by robots.
But positions where you rarely do routine work, or have to emotionally connect with other human beings (a.k.a healthcare), won’t be completely “automated”.
Rather, certain parts of the job will be.
As an example, in 10 years, physicians spending hours documenting patient visits will be a thing of the past.
And this is where a lot of AI’s utility lies: in specific use-cases.
Most AI products that are currently being developed, whether it’s LLMs or diffusion models, are focused on a particular disease or condition.
You’ll definitely find companies building AI-based diagnostic assistants for detecting breast cancers, but probably not one that’s building a robot to replace psychiatrists.
Based on this, it’s clear that the overwhelming nature of the “AI-ification” of healthcare, really just comes down to there being so many use-cases for AI.
Every treatment, every operation, and every professional has the potential to do better using AI.
So why should you care? And why now?
Well, there are obvious reasons like:
- Scalable delivery
- Early disease-detection
- Increased operational efficiencies
- And many many more
But you already know that.
Let’s instead zoom out for a second, and answer this question: “What does every artificial intelligence have in common?”
Data.
We have an abundance of it in healthcare – in fact, it’s usually a complete mess.
But when we’re able to extract meaningful insights from it, the ROIs are incredible – both for patients and bottom-lines.
AI models are just operationalized agents of data that yield these incredible ROIs.
In other words, by using all the information you collect from patients, payors, employees, etc. you can dramatically improve patient-care and skyrocket business, simultaneously.
If that’s not enough to convince you of how important it is to use your data well, here are 3 industry trends that will:
Private equity on the rise
As more PE firms invest in healthcare, whether that’s consolidating practices or selling medical devices, the bottom-line matters, and data-driven decisions can increase yours.
Consolidation allows groups to pool their resources (including their data). As a result, they can hire employees dedicated to squeezing the most out of their data to drive business decisions – that’s part of the way they stay ahead.
And if you don’t adopt a data-driven approach, there’s a good chance that you’ll get outcompeted by those who do.
AI in other industries
Healthcare is just one of many moving parts in the global economy.
Right now, most sectors are pouring resources into collecting more data, analyzing it, and building AI models to operationalize it.
When a shift of this scale happens, problems arise for those industries that don’t follow suit, and interdisciplinary ventures become that much more challenging.
And like any process, change can only move as quickly as its slowest link.
That means, in order to allow healthcare to keep pace with other industries, more organizations need to embrace change.
Consumer Education
As patients become more educated and consumer-savvy they question providers about treatment decisions, they read studies, and more. Overall, the level of awareness is increasing.
This is awesome!
It’s been proven that the more educated patients are, the more they benefit from the care they receive.
Also, having interpretable data at your disposal can help explain to patients why you’re doing what you’re doing, giving them more confidence in the treatment you’ve recommended.
Furthermore, such data acts as a form of security in the case of the lawsuits. Having evidence to back up every decision, clinical or non-clinical, that affects patients can protect you.
Hopefully by this point you’re convinced that:
- You need to invest more in data-driven approaches
- You need to leverage AI in specific use-cases to make the most of it
Where’s the proof?
Oracle’s AI-enabled EHR
Oracle previewed their new EHR at the company’s annual summit. It’s the first version of their cloud-based EHR which leverages AI as one of its core functionalities.
The tool offers secure automation across clinical workflows, easier information sharing between payers and providers, AI-enabled chart summaries for faster review, and much more.
Since making its $28,000,000,000 acquisition of Cerner back in 2022, Oracle Health has been pumping out AI-enabled automation solutions.
A new C-suite: CAIOs and their $1,000,000+ annual packages
The role of Chief AI Officer (CAIO) demands an exceptionally rare combination of skill sets.
More specifically, a deep understanding of IT, policy, business strategy, cybersecurity, and many more.
Businesses in all industries, not just healthcare, are on the hunt for individuals with these skills.
It makes sense that CAIOs have such high compensation packages.
Elevance’s CareBridge acquisition plan ($2,700,000,000)
Elevance wants to position itself for long-term growth, especially through the AI-driven solutions that are increasing metrics across the board.
They believe CareBridge will serve as the foundation for subsidiary Carelon’s home health, a pillar Elevance expects to play a much larger role in the future.
The $2.7 billion cost was estimated by Nashville Business Journal.
Druid AI Product Director cuts through AI-investment noise
During an interview with HIMSS, Elena Branch provides four very feasible use-cases for AI in healthcare:
- Healthcare Personal Assistant
- Symptom Checking
- Appointment Scheduling
- Health Tracking
For each of these use-cases, agentic AI increases the productivity of a single healthcare provider while simultaneously improving patient care.
Premise Health saves patients over $2000 (avg) with new data analytics
Premise Health chose vendor Cedar Gate Technologies to help them with data ingestion (namely claims data) and building custom analytics solutions to track impactful metrics, such as ER visit frequency, chronic care management, etc.
The decision has yielded Premise members significant ROIs:
- $2,434 for primary care
- $10,693 for high-risk management
That’s A Wrap!
See you next Saturday 🙂
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