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Top Ten Tech Trends: Analytics for Readmissions Reduction Work: A Long, Complex Journey Ahead

February 18, 2014
by Mark Hagland
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The scramble is on to leverage the IT tools that can help providers effectively reduce avoidable readmissions

The mandate embedded into the Affordable Care Act (ACA) for hospitals to reduce their avoidable inpatient readmissions has proven to be a major—if predictable—shock to the U.S. healthcare system. Major, because already last August, the Centers for Medicare & Medicaid Services (CMS) notified the executives of 2,225 hospitals across 49 states that they would lose somewhere up to 2 percent of their Medicare reimbursement in 2014, based on CMS finding too many avoidable readmissions for heart attack, heart failure and pneumonia patients at those facilities (with hospitals losing forfeiting up to 1 percent of Medicare reimbursement in fiscal year 2013), with 18 U.S. hospitals to see the maximum 2 percent reduction in Medicare reimbursement in 2014. Predictable, of course, because such measures had been cleared by federal authorities as punishments for poor performance when the ACA was passed back in March 2010.

So if hospital executives have known for nearly four years now that these penalties were potentially coming to their organizations (and indeed, the first penalties were already applied in Oct. 2012, based on 2008-2011 data), why does avoidable readmissions work remain one of the biggest challenges facing healthcare leaders now? A complex knot of reasons is involved, say experts, but fundamentally, it all boils down to this: under the fee-for-service reimbursement system, there had never been (prior to 2010) much motivation for hospital executives to try to figure out, let alone fix, the “problem” of avoidable readmissions for common diagnoses, given that all the incentives under FFS payment have always been towards filling beds. As a result, development of both analytics tools and analytical processes, around this issue has until recently been severely delayed.

Now, of course, there is a scramble underway to figure out how to harness the analytics and report-writing tools and the data warehouse infrastructure, to reduce and eliminate avoidable readmissions. On the Medicare side, hospitals are receiving publicly reported data from CMS to help them sort things through, while on the private side, health insurers are beginning to share claims data with hospitals and physicians, while ramping up their plans to emulate the ACA readmissions reduction program in their contracts.

Meanwhile, the stakes continue to be raised on the federal side, with CMS preparing to raise the maximum penalties to a 3 percent reduction in overall Medicare payment for admissions beginning Oct. 1, 2014, and preparing to expand the number of conditions covered to include chronic obstructive pulmonary disease (COPD), and elective hip and knee replacements. At 3 percent of Medicare revenues, some hospitals operating on very slender margins to begin with, and also facing penalties under the value-based purchasing program and healthcare-acquired conditions program also mandated by the ACA, could ultimately face shuttering. As Chas Roades, the chief research Officer at The Advisory Board, told Kaiser Health News last August, “The financial penalties aren’t huge right now, but hospital leaders recognize that the penalties will get bigger, and that scrutiny over readmissions rates will continue to grow.”

An uphill climb, even for pioneers

So why is this all so hard? Just ask the leaders of pioneering organizations in this area, like the 25-hospital, Arlington-based Texas Health Resources, which has been using data analytics for readmissions work for at least a few years already, and which has been working with neighbor Parkland Hospital on a collaborative initiative. Ferdinand Velasco, M.D., THR’s chief health information officer, puts it this way: “I do think it is going to be a journey. And this will be a Top Tech Trend for many years. I think this will be a similar transition around data analytics, as the EHR transition was. We now have a tremendous amount of data, but it’s going to take a long time” to consistently be able to apply analytics, using that data, to readmissions work.

Up in Philadelphia, Stephen J. Klasko, M.D., president and CEO of Thomas Jefferson University and the Thomas Jefferson Hospital System, says of his health system, “We’ve recognized the burning platform to get this done. We have to promote not over-utilization or under-utilization, but optimal utilization, for the first time. And we’ve recognized at Jefferson, and what David [David Nash, M.D., founding dean of the Thomas Jefferson University Jefferson School of Population Health] in his school has recognized, is that 90 percent of the reason that people get readmitted is that they have symptoms and don’t know what to do.” Connecting patients with their physicians electronically through mobile connectivity, Klasko believes, will be one of several keys to reducing readmissions, as will increasing patient engagement through such motivators as enrollment in high-deductible health plans.