This article was originally published on psqh on May 14, 2024

May 14, 2024 PSQH

By Matt Phillion

How care teams work has never been a one-size-fits-all concept and with the growing complexity of healthcare, changes in the workforce, and the evolution of patient needs, there is an opportunity for healthcare organizations to adapt their models to enable teams to personalize care for every patient at scale.

Opportunities exist for organizations to respond better and faster to the needs not only of their patients but also to the clinicians providing that care.

“The problem as I see it is that care, when delivered on the one-on-one level—at a small scale—is highly effective, and generally speaking, the mark of a really great physician or practitioner is a deeply personal care experience,” says Robbie Hughes, CEO of Lumeon. “In this scenario, the patient gets exactly the care they need. The problem is when you try to do that at substantial scale, you get the opposite effect: standardized or factory medicine.”

At scale, you lose the personalization that is the hallmark of great care, Hughes explains, which means you end up with providers who are either providing too much care to those who don’t need it or not enough care for those who do.

“The challenge, and the opportunity, is how do you scale personalization of care in a way that’s effective, durable, and brings all the benefits you’d expect to ensure the right care, the right time, for the right patient?”

The answer for sure, Hughes notes, is not more of the same.

“You can’t throw more physicians or care team members at a problem,” he says. “The problem is more pernicious than it first seems. When organizations scale, you create systems and processes and try to seek to standardize what you’re doing. But in medicine, in particular, because every patient is different, those processes need to be personalized.”

There comes a point, he says, when that personalization will create reliability issues, delivery issues, and at that point people will do two things. Either standardize everything so every patient gets the same type of care—which is not unreasonable from a practical standpoint as organizations work to ensure they’re practicing safe care. Or, alternately, they go in the opposite direction and go over the top with care management.

“But this tends to suffer from the same issues: every care plan is different, and it can’t reliably scale, so that doesn’t work, either,” says Hughes. “I think there’s an opportunity from a technology perspective to rethink how we consider what a care plan is, and what a care plan should do. Rather than a physician saying, ‘I’m going to authorize what we’re going to have the patient do. Follow steps A through F, in that order.’ But when the patient leaves, maybe they don’t pick up their meds, maybe there’s no follow up, and it’s not the same plan anymore. You end up in a doom loop.”

Instead, Hughes suggests, why don’t we look at the care plan as more of a framework, authorizing steps discretely in a dynamic fashion that reacts based on factors like lab results so you can proactively personalize the plan as you go. This kind of reactivity isn’t necessarily possible with humans but can be automated.

“You can look at what good practice looks like, what the pathways are, and use that to bring in data in real time to recalculate what happens next,” he says. “This creates a kind of personalization engine that means every patient will be guided toward the right thing every time. It’s very different from how we think of care delivery today.”

The process is, in fact, what care teams instinctually do, Hughes notes.

“Teams will naturally do this kind of personalization, but as soon as you start doing it at scale, the reliability breaks down. Things get dropped. The challenge is how to keep that personalization through digital technology?” says Hughes.


Steps to success

For anything like this to work, Hughes says, there needs to be a common understanding of how it works. More than just a clinical protocol, it needs operational factors subject to time constraints or executed by a particular role. And secondly, you need the stakeholders to agree to that.

“Many people have a strong opinion about how they’ve always done things, and as soon as you get into a conversation about this level of precision, it begins to invite questions that have never really been asked,” says Hughes.

For example, in many cases it may be better to see a patient remotely than face to face, which, at face value, may sound counterintuitive.

“But if you see a patient remotely, you can see their home environment, what’s going on behind them, and collect all kinds of information you wouldn’t get if they got dressed up to go into your office to see you,” says Hughes. “This doesn’t mean either is right or wrong, it’s just different, and may be more useful to have that kind of consultation than another. Once you have an opportunity to start defining some of these things, it gives you the chance to ask new questions and then the ability to measure outcomes and impacts.”

And thirdly, you need the technology to make it happen.

“What the technology has to look like is some kind of real-time processing engine, taking in data, comparing it to what’s supposed to happen, and instantly returning a decision that can be relied upon 100% of the time,” says Hughes. “Not just with standardized protocols. Something that brings reliability with that level of personalization that addresses side effects, multiple disease state, conflicting diagnoses.”

That technological lift is the part Hughes is most interested in right now.

“I think the crux of the question is what is the value the human being brings to the equation: they bring the care, the intuition, the feel, the judgment,” says Hughes.

Comparatively, a machine can do the routine, repetitive tasks that the human does not bring value to— for example, when a patient presents with a certain condition, 100% of the time these tests are ordered.

“We’ve reduced the job of the human in so many cases to be focused on those routine, repetitive tasks that are often prescribed by care pathway systems that tell you, you must do this,” says Hughes. “Without that personalization and the ability to understand the specific context, we’re actively harming the practice of medicine. If we can eliminate the routine, then it creates space for humanity, for judgment and caring, and everything else.”

If you ask any physician in the world, Hughes suggests, if they spend 100% of the time doing the part of medicine they love, the answer is no. So much of that patient time has been monopolized by administrative or computerized tasks.

“The reason they’re doing this is because they’re spending time following standardized protocols that are for generic patients and chasing delayed orders because the processes are not reliable,” says Hughes. “It’s the classic problem of well-intentioned decisions being made for reasons of safety and efficiency. We’ve kind of made that the job, but it’s not the job. We start fragmenting the job into these overlays and take away decision-making opportunities. And then we add technology on top of that to enable better communication between people when we shouldn’t need it in the first place.”

A challenge to overcome in developing this kind of technology in many ways comes down to reimbursement, Hughes says.

“We have defined specific reimbursement for activities related to clinical care provided that they’re done in a particular way, so that’s how they’re done,” says Hughes. “You’re rewarded for providing a particular service and need to constrain that service in a particular way, and I understand that, but it radically reduces the ability for people to think outside the box.”

The U.S., in particular, has coupled services so tightly to reimbursement that innovation can lag behind. But a cultural shift could help healthcare providers get back to doing what they do best and step back from the routine, administrative tasks that could be managed through the appropriate automation.

“I think every provider has their hands full with staffing challenges, and I think there’s a happy version and sad version of how this could progress,” says Hughes. “The happy version is that staffing challenges could force organizations to rethink their care delivery models and innovate in ways that are creative and different. The unhappy version is regulation and reimbursement constructs such as staffing ratios and reimbursement codes prevent you from realizing that level of innovation. I don’t know which way it’s going to go, but these are challenges we’ve got to wrestle with.”

Matt Phillion is a freelance writer covering healthcare, cybersecurity, and more. He can be reached at