“We need good data.”
In healthcare, data has always played a critical role in care delivery. But when accountable care organizations first surfaced more than a decade ago, it introduced a seismic shift in how data are collected and utilized by health systems, the ramifications of which are still felt today.
When Fairview Health Services become part of the Pioneer ACO Program in 2010, “We changed a lot,” said Adam Carvel, VP, Data Management & Analytics, during a recent panel discussion. “We shifted our incentive models to be aligned with the external incentives of a value-based care economy.”
The risk paid off, and it remains a core strategy for many organizations.
“We feel like the puck is moving toward value-based care arrangements,” noted Bradley Crotty, MD, Chief Digital Engagement Officer at Froedert Health, who also served as a panelist, along with Don Gray, Chief Enterprise Data & Analytics Officer at Mercy. “We want to meet our patients in that environment and find the most efficient and the most scalable way to make sure their needs are being met.”
By leveraging data, health systems can personalize interactions with patients and “start to change the trajectory of their care,” which can make a significant impact, he added. On the other hand, relying on “blanket campaigns” to prevent adverse outcomes or follow up with patients, “we’re not really hitting the mark as well as we would if we really individualized it.”
Rather, data should be viewed as an “illumination tool” to identify gaps and other problems, noted Carvel. Leaders can then partner with appropriate stakeholders to determine a strategy and utilize data to help shape decisions.
Data collection challenges
For large organizations — and/or those with diverse patient populations — generating the level of analytics needed to drive decision-making can be challenging. At Mercy, “we came up with a unified consumer record that would be consistent across all forms of care,” noted Gray. They also partnered with an outside organization to incorporate social determinants of health, which helped achieve “a more comprehensive view of the person.”
Before any of that can happen, however, leaders must address one of the most significant roadblocks: accurate data collection. Oftentimes, not only do patients have to input their information on paper, but as much as 90 percent of it has already been submitted during prior visits.
For Crotty’s team, putting governance around the data intake process to help alleviate the issue and create a better experience for consumers was a logical step. “We tried to come up with a very modular way of doing it where there’s a base level of information,” which includes key demographics, social determinants of health, and other pieces that are relevant to the clinical data picture.
The other key was to create a standard set of questions based on input from providers. “We said, let’s agree on what we need for everyone to be able to run the business and take care of people,” said Crotty. “It’s a lot of work,” he acknowledged, “but we have to make the experience easier for people. We have to make it easier for our staff. And we have to set ourselves up to be a learning health system and to use data to drive decisions.”
Creating a “holistic view”
Similarly, Fairview has adopted a “layered, fragmented approach” to collecting sets of data variables, according to Carvel, whose team has leveraged its strong relationship with the payer relations department to build out a standardized model for data that flow in through value-based arrangements. “When we get transactional data back from a payer, we ask for the same set of data elements during a patient encounter,” he added. “We don’t always get it, but that’s been really instrumental in helping us build out a longitudinal view of a patient that is buttressed with information that is so much richer.” By collecting outcomes and remote monitoring data and bolting it on to the existing set of information, they’re able to create a more holistic view of the patient.
Fairview took it a step further by sharing the patient data — with their consent, of course — with insurers to identify gaps or find additional programs that can help fill those gaps. “We’re trying to plug in components and data points that help keep our communities and our patients healthier.”
It’s a far cry from the early days of the Pioneer ACO, when Fairview didn’t know which quality metrics were needed, and how those would translate from an operational standpoint. “We jumped into it not knowing exactly what we needed,” said Carvel.
And although the organization has a much better handle on data management, determining whether programs will succeed can still be difficult due to the lack of complete information on care delivered outside of the system. However, “we’ve built some forecasts and models that have allowed us to predict whether we’ll be successful, based on what we do know and on quantifying what we don’t know. Once we got the complete data set from our payers, we were able to identify the blind spots and control them.”
A “better understanding”
Taking it a step further, Fairview is working with HIEs to leverage contemporaneous information alerts for admits, discharges and transfers, and “negotiating with payers to get data explicitly much faster,” Carvel said. “Once we have that mostly complete picture, we’re able to turn around and see if we’re going to be successful with this program, and if not, how we can shift it accordingly. We’re using in ways that we wouldn’t have foreseen 12 years ago.” The difference maker? Having solid analytics and a better understanding of patient populations.
Also critical, according to Crotty, is the ability to “view data as a product that you have to maintain. You have to make sure your product meets the needs of your customers,” which means continuously looking to improve it.
At the same time, however, leaders need to keep an eye on the technical debt that comes with doing things quickly, said Carvel. “If you’re continually trying to balance those aspects of moving fast and getting things done with building something sustainable, you’re going to end up in a good spot.”
Finally, Gray emphasized the importance of storytelling to remind people why it’s so critical. “Keep doing the hard work to articulate a compelling vision of the future that is data and analytics driven,” he said. “We can’t count on anyone else to tell our story.”
To view the archive of this webinar — Implementing Analytics & Technology to Support Value-Based Care — please click here.