Mastering the Tricky Act of Transforming Population Health With Technology

HL: What’s an example of the transformative power of this information, whether it be patient engagement, or just bending the cost curve?

Tomchaney: Patients still strongly adhere to their right to choose what they want to choose. Sometimes they still do it with no real feedback from their primary care physician. So they’re making independent decisions, which is fine, but your only way to have a line of sight to the totality of that patient’s care is having a real broad data feed across clinical, claims, and quality. If you can get those three pieces together, merged into a single set of data resources, it can give us a better picture of the patients, marrying costs and outcomes together to know that, yeah, it really does make a difference to use implant A versus implant B, or whatever is the clinical decision you’re making. That has been totally transformative to care delivery platforms.

HL: You’ve talked about clinical, claims, and quality as a single set of data resources. It’s often called the single source of truth. Has technology made a big difference?

Tomchaney: You need those three redundant sources of information to really be sure you capture the truth about the patient. With the redundancy, you have a greater likelihood of capturing all the realms and data elements that you need. Those tools help us understand how to put together a comprehensive care plan that’s coordinated. It’s still a work in progress because we still have to be able to refine and define quality more discretely than probably what we do today. And it allows the doctors to have a more educated, informed decision on how they make referrals and how they use the resources going forward.

It’s pretty impactful for the doctors when they see it in real time and it’s our patients. That’s the big game-changer: you take full ownership of those patients, because now there’s mostly nothing you don’t know about the patients [whereas], in the past, you made assumptions based on others’ thoughts, feelings, comments, and issues that they had no control over that were brought to the table by whomever. Now, it’s their data. So I think it’s made a big impact.

HL: You’ve been using Cedar Gate analytics technology to unearth these insights for a number of years now. Right before the pandemic, you announced that you had improved your ACO performance by $44 million back in 2018. With the pandemic having now happened, have you seen a continuation of that kind of cost savings?

Tomchaney: Tools like Cedar Gate give us some better clarity about what was the COVID impact on patient care. Patients clearly did less care during COVID, for lots of reasons. The tool can help us quantify and understand where there may be pent-up demand and medical needs for patients that have been left unmet. It helps us understand where we may see surges in utilization. It lets us understand where there’s still a vulnerable population.

COVID was a basically a two-year phenomenon that. when you talk to any of the actuaries, threw all their assumptions aside, and now you have to factor in these unknowns. COVID was an event that changed the pattern of utilization across the population, mostly to the detriment. We’re picking up from that and trying to bring back the resources we need to close the gaps on things that weren’t closed during COVID.

The Medicare population didn’t do as much prevention, so we’re playing a lot of catch-up with outreach. The data systems really helped us understand where that vulnerability was in the population we needed to treat. It helped us stay closer to being on track to where we were prior to COVID. We’re still going to see some shared savings. Our quality scores, which is the measure, when we had our MSSP [Managed Security Service Provider] reconciliation for 2020, we got 100%. It’s not official from [the Centers for Medicare & Medicaid Services] yet, but I can tell you we matched that score for 2021.

HL: What role do payers play in this transformation?

Tomchaney: When you talk about that single source of truth, there’s numbers that we get from our claims pool that we run through Cedar Gate, so we have all that claims information. And then you have the periodic information that comes back from a particular payer. They don’t match. I’ve talked to the payers, saying let’s try to come together so that your data, my data, and the world’s data is all the same, as imperfect as it may be.

I would love to see more confluence of data between the payers and the providers. Sometimes small differences mean a lot. There’s also still a lot of activities that payers do along the lines of risk assessments that fit into some of their proprietary products. We don’t have as much line of sight to that. But we’re all going to be in risk together. We want transparency in healthcare.

The focus today is on the providers. We need to do a much better job supplying the patients and the public with better transparency. There’s nothing that secret I could imagine, in terms of how you calculate it. Honestly, some of the payers don’t have the solutions or the sophistication that some of the providers have.

HL: There is also an effort to expand the traditional role of health information exchanges to encompass claims data. Indiana kind of wrote the book on information health exchanges. Is there a glimmer of hope for getting around proprietary silos that payers possess?

Tomchaney: The good news is we’re having discussions about it. In the past, you wouldn’t even be able to really talk about that. The less-than-optimistic news is that nothing’s really been done to change that. In Indiana, most of the healthcare is through employers. We’re told 70% have self-funded plans. It’ll take a while. The employer base in Indiana is very, very focused on hospital costs and why are they higher than other parts of the country.

HL: If there’s a knock against AI, it’s that it’s filled with black boxes. People are trusting that the tech is doing what it says it’s doing, but maybe not always being able to verify that.

Tomchaney: For most of the cases, it’s going to be still up to the clinician to make that clinical decision. We keep telling the docs AI doesn’t replace your brain. The thing I really get frightened of over the variety of systems I’ve seen is the willingness to accept a solution, from a technological standpoint, that’s the easiest. It’s a one-button push, as opposed to a solution that maybe takes two buttons. I’ve told the docs, you all understand in medicine that we live by the 80/20 rule. Whether it’s through our pattern recognition, when we make a diagnosis, or whatever the experience is, 80% of the patients can go down one of those algorithms that you talked about, but the skill in this new era is identifying that 20% who don’t fit that.

If you look at places like Geisinger, that has ProvenCare, they do a remarkable job on making sure that the person fits the ProvenCare solution before they even put them in there, but you have to continue to reinforce “patient-first.” And while yes, 80% will fit the solution, you’ve got to take probably more time and effort to identify that 20% that doesn’t, make sure there’s checks and balances, and reasons for the clinicians to pause and not push whatever’s the easy button.