As challenging as it is for the leaders of hospitals, medical groups and health systems to strategize broadly around the plunge into risk-based contracting, strategizing around the information technology foundations and data analytics to support that journey is turning out to be equally challenging. That is the verdict of leaders from across the spectrum of U.S. healthcare, and from the hospital, physician group, integrated health system, and health plan sides of the table.
Fundamentally, says Shawn Griffin, M.D., vice president, clinical performance improvement and applied analytics, at the Charlotte-based Premier Inc., “The response to risk is trying to increase control, and our data systems have not been organized to give us total control over processes. The challenge,” Griffin says, “is that your insurance company you’re contracting with controls and owns the data; data ownership is an important concept. And even doctors aren’t all on the same EHR [electronic health record], who are in the same network. And now that the system of care isn’t just hospitals, but outpatient and post-acute as well, you have to build data and IT governance” around participation in value-based healthcare contracting. “You have different metrics for different claims and clinical data types; and the fact that we’re trying to bring in different types of data and tell the same story with them, is difficult. And the lack of interoperability is a huge challenge," he says.
“I feel like we’re making progress on the claims data, because organizations are getting better at doing claims analytics; we’re now beginning to be able to use claims data to identify, for example, who the high-risk and high-cost patients are,” says Joe Damore, Griffin’s colleague and a vice president at Premier Inc. “But I still see a huge challenge in the lack of interoperability among EHRs. I don’t see anyone who’s mastered the situation yet of networks that are using multiple EHRs.”
“We have a sketch of interoperability that often involves dumbing down the information you share among EHRs. Almost nobody talks about claims interoperability,” Griffin adds. “Medicare Advantage versus commercial plans, multiple Medicare Advantage plans, all are different versions of claims data. We all have a phrasebook for a foreign language,” he adds.
Health plan leaders agree that there are some very fundamental challenges involved, including on the payer side. Speaking of the challenges for providers partnering with health plans, in marrying clinical and claims data, as well as simply in getting data to providers in a timely way, Chris Jaeger, M.D., vice president of accountable care innovation and clinical transformation at the San Francisco-based Blue Shield of California, says, “Having been on both the provider and plan sides, those are definitely real hurdles. It speaks to immaturity in master data management. And even when there’s more mature enterprise master data management, it will vary across organizations, so that’s a huge problem. And with respect to data timeliness, one challenge relates to plans sharing adjudicated claims data, where inevitably there’s a lag. On the provider side,” he adds, “my last experience was with PPO shared-savings contracts, and we had problems with timeliness and accuracy of data from plans, and sometimes just in terms of the master data management.”
Chris Jaeger, M.D.
What’s more, Jaeger says, data integrity remains a core challenge, in all situations involving health plans sharing data with provider organizations. “We were seeing data integrity issues that we needed to fix, before we could marry the plan data with our clinical data. And a lot of vendors will say they have the capability to deal with that, but the devil is in the details. So, we’ve been partnering with some of our provider partners, sitting down with them, with their resources, as well as with the partnering population health vendors, to improve how the data is moved and used, so they can do a better job.” What’s more, he says, “Data management doesn’t sound like a sexy value proposition, but it ends up being of incredible value. So really, if an organization is able to cleanse and aggregate data from multiple sources and bring the data into its analytics, you get better results.”
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