Anatomy of a Readmissions Master Plan
Memorial Hermann leaders have been able to reduce preventable readmissions by closing care continuum gaps. They've tackled poor communication among disjointed or unaligned providers, a lack of systemic accountability and follow through, and inadequate human and IT resources.
This article appears in the November issue of HealthLeaders magazine.
Memorial Hermann in Houston is fortunate in some ways that it had a preview of the pain of readmissions almost a decade ago and decided to do something about it. Years before the Centers for Medicare & Medicaid Services started to penalize hospitals for preventable readmissions, Memorial Hermann had pain of its own: hundreds of millions of dollars in annual uncompensated care for a population that reached as high as 33% uninsured.
"We see a tremendous number of uninsured patients," says Memorial Hermann Chief Medical Officer Michael Shabot, MD. "We run 10 emergency departments, seeing over a half million patients a year, and we take care of everybody without regard to ability to pay. But what we found was that those individuals who weren't insured had a very high rate of readmission to the hospital or to our EDs or to observation. So we were actually paying for their admission and for every readmission. I mean literally just the hospital was paying for it."
It was decided that the right thing to do—as well as the most cost-effective—would be to undertake a comprehensive program to better manage high-risk patients. This program would close gaps in the care continuum that historically have led to readmissions: poor communication among disjointed or unaligned providers, a lack of systemic accountability and follow through, and inadequate human and IT resources.
The first step was to understand which patients were at higher risk for readmission. When the program began, risk stratification was based simply on a patient's number of previous hospital admissions. The team began to use a software program in conjunction with the Cerner-based electronic health record that scans the daily patient census and uses an algorithm to flag patients who may be at higher risk—based on their disease type or condition, as well as other demographic or clinical data. Those patients are added to a list that case management contacts for more follow-up.